Data Evaluation and Methods Research Series 2Number 86

Computer-Assisted$pirometry Data Analysisfor the NationalHealth and NutritionExaminationSurvey, 1971-80

The equipment, procedures, and data reduction methods employedin the National Health and Nutrition Examination Survey for thecollection and analysis of spirometric data are described. Data vari-ability and testing methodology are discussed, as well as the influ-ence of milieu and technician training. The computer programs thatdrive the data reduction and calibration are detailed, as are the algo-rithms used in the calculation of various spirometric parameters.The algorithms chosen for the determination of certain criticalparameters are documented and validated.

DHHS Publication (PHS) 81-1360

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICESPublic Health Service

Office of Health Research, Statistics, and TechnologyNational Center for Health StatisticsHyattsville, Md. October 1980

Library of Congress Cataloging in Publication Data

United States. National Center for Health Statistics.Computer assisted spirometry data analysis for the Health and Nutrition Examinatiurt

Survey, 1971-1980.

(Vital and health statistics : Series 2, Data evaluation and methods research ; no. 86)(DHHS publication ; no. (PHS) 81-1360)

Written by David P. Discher et al.Includes bibliographical references.1. Spirometry–Data processing. 2. Health and Nutrition Examination Survey. 1. Dis-

cher, David P. II. Title. III. Series: United States. National Center for Health Statistics.Vital and health statistics : Series 2, Data evaluation and methods research ; no, 86.IV. Series: United States. Dept. of Health and Human Services. DHHS publication ; no.(PHS) 81-1360.RA409.U4’5 no. 86 [RC734.S65] 312’.0723s 80-607930ISBN 0-8406 -0195-6

NATIONAL CENTER FOR HEALTH STATISTICS

DOROTHY P. RICE, Director

ROBERT A. ISRAEL, Deputy Director

JACOB J. FELDMAN, Ph.D., Associate Director for Analysis

GAIL F. FISHER, Associate Director for Cooperative Health Statktics Systems

ROBERT A. ISRAEL, Acting Associate Director for Systems

ALVAN O. ZARATE, Ph. D., Acting Associate Director for International Statistics

ROBERT C. HUBER, Associate Director for Management

MONROE G. SIRKEN, Ph.D., Associate Direc tor for Mathematical S tatistics

PETER L. HURLEY, Associate Director for Operations

JAMES M. ROBEY, Ph.D., Associate Director for Program Development

GEORGE A. SCHNACK, Ph.D., Associate Director for Research

ALICE HAYWOOD, Information Officer

DIVISION OF HEALTH EXAMINATION STATISTICS

ROBERT L. MURPHY, Director

JEAN ROBERTS, Chiej Medical Statistics Branch

KURT MAURER, Acting ChieJ Survey Planning and Development Branch

COOPERATION OF THE U.S. BUREAU OF THE CENSUS

Under the legislation establishing the National Herdtb Survey, the Public Health Service isauthorized to use, insofar as possible, the services or facilities of other Federal, State, or privateagencies.

In accordance with specifications established by the National Center for Health Statistics,the Bureau of the Census, under contractual agreement, participated in planning the survey andcollecting the data.

Vital and tlealth Statistics-Series 2-No. 86

DHHS Publication (PHS) 81-1360Library of Congress Catalog Card Number 80-607930

CONTENTS

Introduction ......................o........................o..................................o........................................................

llac~ound ............................................................................................................................................Spirometry Data Variabtity ..............................................................................................................Testing Methodology ..... ...................................................................................................................

Instrumentation .....................................................................................................................................Spirometcr and Support Electronics .................................................................................................Calibrators ........................................................................................................................................Data Acquisition System ...................................................................................................................

Spiromctry Data Analysis: Program Description ....................................................................................Calibration Factor Computation (First Stage) ...................................................................................Volume and Flow Rate Signal Data Corrections (second Stage) .......................................................Spirometer Trial Parsmeter Computation (lhird Stage) ....................................................................

“Spirometry Data Analysis: Validity of Alternative Algorithms ...............................................................Methodology .....................................................................................................................................Zero-Time and FEV1.0 Calculations .................................................................................................End-of-Trial, FVC, and F~~25.75% Cakdations ..............................................................................

Summary “and Conclusions .....................................................................................................................

References ..............................................................................................................................................

List of Detailed Tables ...........................................................................................................................

AppendixesL Glossary ....................................................................................................................................H. General Spirometric Test Proced&es Used by NHANES ....... ...................................................

1.

2.

3.

4.

5.

6.

7.

s.

9.

LIST OF FIGURES

Typical subject flow-volume curve set ............................................................................................

Sample spirograrn dcmon@rating the short baseline procedural error .............................................

Sample spirogmm demonstrating the no end-of-test plateau,procedural error ................................

Sample oscilloscope tracing demonstratingthe premature termina tion artifact procedural error ....

Sample oscihxcdpe tmcing demonstrating the inhalation artifact prowdurid error .......................

Sample oscikscope tracings, one normal ana one demonstrating the Venturi artifact proceduralerror ..o.........................................................................................................................................

A depiction ~f the mechanics of a spirometric Venturi artifact ..... ................................................

Sample oscilloscope tracing demonstrating the low peak flow artifact procedural error .................

sample oscilloscope tracing demonstrating the hesitation artif~ot nr~~dural error .................... ....

1

224

10101112

::1415

19192428

31

35

36

45%7

6

6

7

7

7

8

8

9

9

...Ill

10. Schematic of the NHANES spirometry system ............................................................................... 10

11. Spirometer data-calibration sine wave ........................................................................................... 12

12. Digitrd data array from a calibration curve showing trough (B) and peak (C) ................................. 14

13. Schematic of flow-volume curve showing the relation of zero time to time of peak flow .. .. .. .. ... ... . 15

14. Data output sheet for a normalsubject showing a set of 5 spirograms ............................................ 17

15. Data output sheet for an abnormal subject showing a set of 5 spirograms ...................................... 18

16. Example of a normal time-volume spirogram ................................................................................. 20

17. Normal spirogram (time-volume and flow-volume curves) with noise signals superimposed ............ 22

18. Abnormal spirogram (time-volume and flow-volume curves) with noise signals superimposed ........ 23

19. Manual calculation of to showing a reproduction of the 4 alternative methods .............................. 26

20. Example of an abnormal time-volume spirogram ............................................................................ 27

21. Manual calculation of end of trial showing the 4 alternative methods ............................................ 30

22. FEV1 analysis-means and standard deviations (3u) of paired differences from triangular cx-“! .trapo ation (method 2) measurements ......................................................................................... 32

23. PVC analysis-means and standard deviations (3u) of paired differences from negative flow(method S) measurements ........................................................................................................... 33

LIST OF TEXT TABLES

A. Procedural error codes and their definitions ................................................................................... 9

B. Methods for zero-time and end-of-trial determinations ................................................................... 21

SYMBOLS

I Data not available .-. ICategory not applicablc— . . .

Quantity zero

Quantity more than O but less than 0.05— 0.0

I Figure does not meet standards ofreliability or precision * I

I I

COMPUTER-ASSISTED SPIROMETRY DATA ANALYSIS

FOR THE NATIONAL HEALTH AND NUTRITION

EXAMINATION SURVEY, 1971-80

David P. Discher, M.D ?; Alan Palmer, Ph.D}; Gregory Hibdonc; Terence A. Drizd, M.S’.PJ3!

INTRODUCTION

The wide acceptance of the Forced Expiat-ory Spirogram pulmonary function test in respi-ratory epidemiologic studies is evidenced byrecent efforts of the Division of Lung Disease ofthe National Heart, Lung and Blood Instituteand the American Thoracic Society to bringgreater precision to this important test.1$2Spi-rometry provides both medical practitioners andepidemiologists with a simple yet objectivemethod of following the course of chronic ob-structive lung disease from its early inception toits more advanced states, thereby permitting theapplication of intervention measures and themonitoring of results. Furthermore, epidemio-logical studies can indicate early changes in func-tion that can be related to various aspects ofenvironmental pollution thus permitting devel-opment of control strategies to mitigate furtherdegradation of function.

Unfortunately, spirometric testing is ham-pered by a lack of sound and sensitive data ob-tained from rigorous testing procedures on gen-eral population groups. These data are necessaryfor derivation of performance standards.

ach~rmm, Department of Industrial and EnvironmentalMedicine,SanJose MedicalCliiic,

kienior Epidemiologist, Center for Community HeaIthStudies, Stanford Research Institute International.

cComputer Application Analyst, Stanford Research Insti-tute International.

dstatisticim, Di~sion of He~th

NationalCenterforHealthStatistics.Examination Statistics,

The National Health and Nutrition Examina-tion Survey of the National Center for HealthStatistics is the largest ongoing examination sur-vey in the world. Thus the National Health andNutrition Examination Survey offers an oppor-tunity to collect lung function data on variouspopulation groups representative of all socioeco-nomic groups, races, ages, sexes, and geographicareas. Because additional data are also collectedon examinees that may be significant variablesfor spirometric function, this survey will lead toresearch on other variables.

Aware of the limitations of existing spirom-etry data, the staff of the Division of Health 13x-amination Statistics, which conducts the Na-tional Health and Nutrition Examination Survey,have undertaken an extensive review of theexisting spirometry data collection proceduresand computer processing program criteria toensure that data sensitivityy is maximized.

This report details each of the steps taken toensure the collection of optimal data. An identi-fication of the multiple source of variabilityknown to reduce the sensitivity of the data, adescription of the subsequent operating proce-dures to minimize each of these sources of vari-ance, a review of spirogram measurement criteriaas currently used in the National Health andNutrition Examination Survey program, and acomparative analysis of various alternative algo-rithms for increasing the accuracy of the meas-urements are presented. The development ofalternative spirogram measurement techniques

1

was undertaken to further validate those tech-niques suggested in the recent National Heart,Lung and Blood Institute reportl and, most im-portant, to provide testable, documented logicfor the National Health and Nutrition Examina-tion Survey (NHANES) criteria used in qualitycontrol calibration, and measurement pro-cedures.

These documented measurement criteriashould provide a foundation for the analysis ofcurrent and future NHANES-collected datafrom which new regression equations will bedeveloped for prediction on normative values.

BACKGROUND

Spirometry testing has been an integral partof the National Health Examination Survey(NHES) since 1963. During NHES Cycle II(1963-65), spirometry data were obtained by aCollins water-sealed spirometer, using the stand-ard operating test procedures recommended inthe spirometer instruction manual. Generally,technicians had little training in the theory andphysiological meaning of spirometry. Measure-ments were made manually at great expense intime and money, and the limitations of this levelof data collection became obvious.8 DuringNHES Cycle III (1966-70), a spirometry testingmodule that used computerized data collectiontechniques was developed. Rigid standard oper-ating procedures (SOP’s) were developed, andconcurrent technician and data surveillance pro-grams were run to control for procedure and testdata variability. Data were analyzed using thespirometry computer program4$ developed bythe Public Health Service (PHS).

Further refinements were made in the spi-rometry data collection module in 1970 beforethe beginning of the National Health and Nutri-tion Examination Survey (NHANES I). The dataacquisition hardware system that was used inNHANES I to collect spirograms is described in‘this report. Digital tape equipment was installedto replace the analog data systems used in NHESIII, and general refinements of the SOP’s weremade to reflect the current methodology (e.g.,the use of a standard set of five trials to ensure

maximal values). While NHANES I data werebeing collected, the latest version of the PHScomputer spirometry program was reevaluatedand extensive program changes were made incalibration and quality control procedures andthe logic used to define and compute the variousspirometric measurements. Recently, new cri-teria have been developed and adopted by theNational Heart, Lung and Blood Institute(NHLBI) to standardize the criteria used tocompute and analyze spirometric data in epi-demiologic studies.1 The NHLBI criteria arecomparable with those used by the NHANESprograms except in “zero-time” and the “end-of-test” computations. These methods are com-pared and their strengths and weaknesses aredocumented.

The initial discussion in this report relates tononsampling data errors that are caused by thehost of variables that the NHANES planninggroup delineated as obstacles to collecting opti-mal data. This discussion is followed by a de-scription of the instrumentation and the qualitycontrol programs that were developed to controlfor these errors and of the test procedures usedduring NHANES I. Finaliy an analysis of the testprocedures is presented and various alternativemethods for obtaining spirometric measure-ments are compared.

Spirometty Data Variability

In establishing testing uniformity, the vari-ables that must be considered include selectionand training of technicians, testing techniques,testing environment, spirometry equipment se-lection, data measurement and computation,and quality control.Gj7 Each of these areas is apotential cause of nonsampling error that di-minishes or obscures any differences beingsought in epidemiological studies as well as thevalidity of spirometry as a clinical-diagnostictool.

Examinee sources of variance. –Submaximalexpiatory effort during the performance of theForced Expiatory Spirogram (FES) is attribut-able to a variety of factors. A common cause ofpoor test data is failure of the subject to com-prehend the test instructions; in children thisproblem is often referred to as testing imma-

turity. This condition is a behavioral-social phe-nomenon exemplified by a lack of school readi-ness; the commands “Sit down and be quiet,”“Raise your hand when you want to speak,”“Pick up your pencil and copy the picture andthe words in your book” all require understand-ing, willingness,and enough self-control for thepupil to perform properly and effectively?Older children and adults of various ethnic andsocioeconomic groups can also present problemsof language and comprehension, and these fre-quently combine to frustrate meaningful datacollection. Examinees with such problems areoften performing the spirometry marieuver forthe first time and this situation, coupled withanxiety regarding any medical procedure or itsimplications, often results in an unacceptabletest despite the best efforts of the technician.

Tcchnkian sources of variance.–Spirometrytesting requires maximum subject participationand an astute technician. Current practice dic-tates that vigorous verbal encouragement begiven to the subject to stimulate maximal effort.An experienced technician is a combination ofbully and cheerleader as he or she strives to elicitthis maximal response from the subject. Thetechnician must first explain the test, demon-strate the procedure, cheer on or goad thesubject into putting forth his or her best effort,and evaluate the degree of cooperation obtained.

The methods used to administer the test notonly vary from one technician to another, butalso vary from trial to trial with the samesubject. Not all technicians have equal abilitiesto perform all tasks well. Some work well onlyunder supervision; if supervision is varied, tech-nician performance also can Vary.g

Any individual who is well motivated, inter-ested, and reasonably intelligent and who hasthe equivalent of a high school education can betrained in spirometry.7 Only 2 weeks of inten-sive training are required to learn how toadminister the spirometry test, handle and cali-brate the instruments, and perform the calcu-lations. However, learning to obtain the bestpossible performances from examinees of alltypes and ages takes much longer–at least 6months gnd perhaps a year. Such experiencedevelops the many approaches necessary toinstruct the exarninee in a series of unfamiliar

maneuvers, such as, taking in the deepest breathpossible, inserting the mouthpiece and keepingthe lips tightly around it, and exhaling into thespirometer as quickly, forcibly, and completelyas possible.

The most important quality of a pulmonaryfunction technician is the motivation to performthe very best test on every examinee. Initialenthusiasm after a while may turn into lack ofinterest. The intellectual ability of the techni-cian becomes particularity important in discer-ningperformance deficiencies of examinees andcorrecting these errors in maneuver.

The qualifications of personnel being hiredto do spirometry are difficult to judge. Thisprocess may be accomplished though a personalinterview with the prospective employee inwhich previous and related work experiences arereviewed and discussed. Each new technicianshould be evaluated to determine the level oftraining that will be required; and, if furthertraining is needed, it should be done under theguidance of an experienced physician or pulmo-nary physiologist in a laboratory where ampletesting is being performed with the higheststandards of accuracy and quality control.

Equipment sources of van”ance.—Spirom-

etem-much data are available on puhnonaryfunction sensors that point to a basic set of de-sirable characteristics. The spirometers should beaccurate and precise, have linear volume andflow rate response, be electronically (in elec-tronic models) and pneumatically calibratable,have a frequency response of the signal beingrecorded (FES, 15 Hz), and have low inertiawithout oscillatory fluctuations.2

Portability and compactness, although de-

sirable, should not be considered at the expenseof any of the preceding characteristics.

Automation. –Hand measurements of spiro-metric data have been shown to be less precisethan automatic systems. Studies have shownthat when two trained pulmonary techniciansanalyzed a number of spirograms, interobserverdifferences were statistically significant.1 0 Epi-demiologic studies often require the combinedefforts of two or more observers for the study ofa large population; thus should one observer bemore precise than the other, the quality of thebetter effort is diluted when the results are

3

pooled. The ability of measurements to discrimi-nate between a normal and abnormal populationis vitiated under such circumstances.

The expenditures of time and people forroutine computations is no Ionger justifiable.The use of automated techniques conservestime, improves accuracy and precision, increaseswork capacity, and reduces cost. Through thesemeans, the professional and technical staff be-come free to pursue more challenging activities.

Testing Methodology

The need for calibration. –Although spjrom-etry equipment is extremely accurate, even thebest equipment requires both careful attentionand routine maintenance. For the electronic sig-nals generated by moving the piston in the spi-rometer to be related to known volumes andknown flows of air, the technician must performperiodic calibration checks. To detect minor sig-nal fluctuations between pneumatic and elec-tronic calibrations, the technician must performa calibration as required by the SOP’s.11 Preciseadjustments of the equipment are made thatalter the volume-to-voltage relationship whichare based on observations that the technicianmakes by using the pneumatic calibrations. Thetechnician becomes aware of the need for elec-tronic service to the equipment when the elec-tronic calibrations show wide fluctuations of thestandard electronic signal. Thus the first consid-eration in obtaining valid data on forced expiat-ory maneuvers by electronic spirometry is anunderstanding of the electronic principles inher-ent in calibrations and maintenance.

The need for technician-examinee rapport. –The second concept that the technician mustunderstand is the requirement that the forcedexpiatory maneuver be correctly performed bythe subject under the close observation andguidance of the. technician. The technician canenhance this communication by developing aninitial rapport, performing a good demonstrationof the maneuver, and clearly stating the standardtest instructions. The technician’s skill is mani-fested by the subject’s comprehension of theinitial standard instructions, motivation to pro-vide a maximal effort on a minimum of two ofthe five expiatory trials, and correct notation of

procedural errors and redirection of test instruc-tions accordingly. A number of barriers to asuccessful test can be identified as follows:

●

●

●

●

Testing immaturity–the subject cannotfollow directions.

Inability to communicate–the subjectcannot speak the language or dialect ofthe technician or any availableinterpreter.

Pain or disability-the subject cannottake in a deep breath and/or rapidlyexhale down to full expiration.

Voluntary refusal–the subiect will notparticipa~e because of f~ar or otherreasons.

Instructions to subjects, therefore, are stand-ardized for the initial trials and follow standardvariations for subsequent trials depending onobservations of the technicians-observationsmade by watching the subject perform themaneuver and by monitoring oscilloscope dh-plays of the flow and volume signals of allcompleted trials for that subject. The skilledtechnician quickly perceives difficulties fromthese two sources and redirects the subject toperform a correct maneuver. A number ofexaminees tested in NHANES I did exhibit painor discomfort while performing the test orindicated the presence of an upper respiratoryinfection. With the assistance of the residentphysician, such subjects were disqualified fromthe examination. Regarding those who refusedto take the test, their reasons were fully docu-mented and will be examined for nonresponsebias.

In summary, the test requires both atechnician-spirometer interaction to achieve ac-curate’ and reliable signals and a technician-subject interaction to achieve subject compre-hension and motivation. These two interactionareas define technician skill. A review of techni-cian performance in the field, however, revealedoccasional drift in performance; therefore, re-training procedures were routinely implementedto reduce this source of error.

Spiromet~ data quality control.–The at-tending technician is responsible for spirometric

4

data quality: Direct observations can be madeduring the performance of the test and observederrors can be corrected during the procedure.Clearly, the technician has the cardinal role indata quality control because he or she providesclear and concise test instructions, coaches theexaminee to perform a maximal expiatorymaneuver, and provides an initial judgment ofthe acceptability of the data obtained.

The technician can carry out this role byproper use of the monitoring equipment andcareful observation of the subject. A memoryoscilloscope with an X-Y axis is regarded as areasonably precise tool for monitoring patient’sspirometric effort. Flow is registered on the Y(vertical) axis, and volume is measured on the X(horizontal) axis. Each respiratory effort resultsin a flow-volume curve, which is displayed onthe oscilloscope and compared with subsequentcurves (figure 1). The technician can thusmonitor discreet changes in patient effort andcooperation by observing the shape of the curveand the height of the peak flow deflection. Thismonitoring information must be integrated withsubject performance observations. Appendix I isa glossary of terms relating to this technicianfunction and includes a diagram of the threephases in a normal spirogram trial (appendixfigure I).

The following paragraphs describe the cur-rent criteria used by the NHANES technicians tojudge data quality.1 1

Procedural ewor detection.–As a matter ofconscientious workmanship, a technician ex-amines each trial within a test set during itsrecording to identify the presence of any partic-ular procedural error. Errors are a signal to thetechnician that the examinee is experiencingsome problem with the test instructions eitherbecause the instructions were unclear or compre-hension was inadequate. When a proceduralerror is identified, such as the absence of a ter-minal decay curve (as seen on both the flow andvolume signal), the subject is reinstructed, withemphasis on that part of the instruction wherethe problem occurred, and a clear demonstrationof the test procedure is given.

The common procedural errors that alert thetechnician to the possibility of an invalid trialare described below.1 1 The best trials are those

with the largest forced vital capacity (FVC) ac-companied by the highest flow rates. Proceduresfor identifying the best trkd are described withinthe section entitled “Reliability Error Detec-tion.”

Short baseline. –A short baseline can resultwhen the technician starts the recording equip-ment too late, thereby not permitting establish-ment of a sufficient baseline, or when the sub-ject initiates expiration before instructed to doso, thus obviating the baseline. A short baselinecannot be observed on the flow volume displaybut it is evident on the strip chart, as shown infigure 2.

No end-of-test plateau. –Dunng the test pro-cedure, subjects who have large vital capacitiescoupled with low terminal flow rates continueto increase their expired volumes beyond thepreset recording time (9.19 seconds after thetechnician initiates the NHANES I recordingsystem). This phenomenon typically occurs insubjects with chronic obstructive lung disease(COLD), although it can occur in subjects withno known disease. The strip chart, not the visualdisplay, shows this phenomenon because theformer is a 9.19-second record whereas the latteris a flow volume display that is independent oftime (figure 3). The recording equipment de-scribed here does not have a manual override topermit recording volumes beyond 9.19 seconds;thus, the presence of a terminal flow is referredto as premature termination by the recorder.

Premature termination artifact.–The prema-ture termination artifact is manifested by theabsence of a typical phase 111morphology of thespirometric curve, that is, a slow decay curveuntil residual volume is reached. Unlike a prema-ture termination by the 9.19-second recorder,this phenomenon occurs within 9.19 secondsand is due to premature termination of theeffort by the subject; thus the phenomenon isfound on both the visual display and the stripchart (figure 4).

Inhalation artifact.–lnhalation artifacts areidentified either by the flow-volume loop mor-phology depicted in figure 5 or by review ofthe flow signal on the recording paper andobserving that the flow rate decreases below thebaseline, which is followed by an increase offlow greater than 1 liter per second (1 1 per

5

VOLUME

Figure 1. Typical subject flow-volume curve

Figure 2. Sample spirogram demonstrating the short baseline procedural error

Figure 3. Samplq spirogram demonstrating the no end-of-test plataau pro&dural error

8ii!

Suddencessaticmof flow rate

/((__~%VOLUME VOLUME

Figura 4, Sample oscill’oseope tracing demonstrating the Drama. Figure 5. Sample oscilloscope trtwing demonstrating tha inhala-

RJre termination artifact procedural error

second). (These trials are automatically dis-carded as totally invflld and are not consideredin a set of five.)

Venturi artifact. –The Venturi artifact isevident when FVC volumes and/or flow ratevalues are greater than clinically expected (fig-ure 6). This phenomenon is caused by trumpet-ing into the mouthpiece with pursed lips, whichcauses room air to be drawn into the spirometeralong with the expired air (figure 7). This situ-ation occurs because of a vacuum effect fromthe high velocity of air movement from thepursed lips. The typical morphology of a Ven-turi trial is a rapid rise of How rate to a highlevel that is sustained until residual volume is

tion artifact procedural error

attained, followed by a rapid decrease to thezero line. Such an uncharacteristic trial is readilyidentified by a trained technician by review ofthe flow-volume display.

Because some members of the population(such as highly trained athletes) have extra largelung volumes and flow rates, large values can beobtained without any artifact; however, cautionis required before accepting these readings.Again, if reliability criteria are met, whichincludes a careful review of the flow and volumehistories, the test is valid.

Low peak ji?ow artifact. –Peak flow rates of50 percent of predicted value are sought as ameasure of inital expiatory thrust. Lower values

7

WITH VENTURI

—.—

WITHOUT VENTURI

.—— —— ——— — —-

VOLUME

Figure 6. Sample oscillosoopa traoings, one normel and one demonstrating the Vanturi artifact procedural arror.

?

THE VENTURI

Nrtdn \ . Ounkbdrdmwnhrmm

mcuul—_ —

--— SpirmwwWtm

Figure 7. A dapktion of the maotmnics of a spirometrk Venturiartifact

would indicate the possibilhy of malingering,not achieving total lung capacity before begin-ning to blow, trouble understanding the testinstruction, Qr severe obstructive lung dkease(figure 8). This possible error check is discardedif applied reliability criteria are met. No compu-ter check is used for detecting this artifact:Detection is left to the technician who must

observe both subject effort and Peak flow esti-mates on the mo~itoring equipme;t.

Hesitation artzfact.-The hesitation artifactshould not occur during the three phases of thespirogram. If it does occur, the test may beconsidered acceptable only if the reliabilitycriteria have been fulfilled and flow and volumehistories are similar. This artifact (figure 9) isgenerally identified by the technician, and com-puter identification is limited to detection of arelatively large hesitation only at phases II andIII.

Table A describes the output codes andcriteria used by the computer program to flagthe described procedural violations.

Reliability ewor detection. -Acceptablespirograms result in reproducible curves.1’ J12The technician makes an initial determination ofreliability by using the monitoring equipment tosuperimpose one flow-volume curve over theother or, alternatively, to compare them side byside. At the conclusion of the fifth trial, thetechnician also examines the paper record forthe two best trials. These trials are deemedreproducible if the estimates of the FVC andforced expiatory volume at 1 second (FEV1.0 )are within 5 percent, assuming that these vol-umes exceed 31 or 10 percent for FVC andFEV1.0 volumes of less than 31. If reproducibiI-

VOLUME

Figure 8. Sample oscilloscope tracing demonstrating the low

Code

o...................

1,,,,,. ,,...,, !,,..,

2 ,,,,,,..,..,,.,.,..

3 ......... ..........

4 ,,,.,...,Oas.......

5 ...................

6 ,..,,,,,,..,,,,.,,.

7 .,,,,,,,,., .......0

8 ..,. ,., .,, .,,.,,.,.

peak flow artifact procedural error

vOLUME

Figure 9. Sample oscilloscope tracing demonstrating the hesita-tion artifact procedural error

Table A. Procedural error codes and their definitions

Definition

No violations occurred.

Onset of volume cuwe occurred lessthan 150 ms after the baginning of the record (short baseline).

End of trial (EOT) was not identif ied in the 9.19-second record (premature termination by recorder).

A volume increment of less then 4 percent between 0.5 second and 1 second aftar onset of the curve, or an incrementbetwean 1 and 2 seconds lessthan 4 percent (midtrial premature termination by subject), occurrad.

A negative flow occurred followed by post.EOT positive flows in excess of 50 ml per second over any 0.50-secondinterval following EOP (inhalation artifact).

Peak flow was greater than 3 standerd deviation units above subject’s predicted peak f low (Venturi artifact).

Computed FVC was lessthan 0.2 i (invalid trial).

Post-peak flow but pre-EOT signal showed e marked decrease (25 percent of peak flow) in flow for a time intewal of0.1 second or more and was followed by a marked increase (25 percent of p?ak flow) in flow (habitation artifact).

The 0.50 second of a trial after EOT had a slope in excess of 50 ml/second (premature termination at end of trial bysubject).

ity cannot be demonstrated within that test set,the five-trials test sequence is repeated after thesubject has rested.* ~g

The need for technician monitoring andsurveillance. —Uniformity of testing procedureswas achieved in the NHANES by the use of

appropriate operational procedures, care in theselection and training of technicians, ahd per~-odic retraining.

Because data collection in NHANES I ex-tended over a 5-year period, problems of drift in

technique were anticipated.b This drift was “overcome in part by a surveillance program inwhich spirometry data obtained by each techni-cian were perio&lcally reviewed for trends inprocedural and reliability errors. From thisinformation, corrective actions were taken toreduce the continued collection of technicallyunsatisfactory data. This procedure was accomp-lished by directly observing the technician as heor she performed the testing in order to identifypossible errors in technique. One aspect of this

9

on-site surveillance was to compare the instruc-tions given to the subjects with the standardinstructions shown in appendix II. Anotheraspect was the on-site review of the subjects’tracings to determine whether the technicianscould make accurate judgments from the recordand were able to correctly observe the flow-volume loop.

INSTRUMENTATION

The instrumentation used in the NHANESprogram to acquire and store the spirometrysignals in a format suitable for computer analysiscomprised an electronic spirometer, a storageX-Y oscilloscope to display the ‘flow-volumecurve for monitoring purposes, a single-channellinear strip chart recorder to provide a perma-nent record of the volume signals, and a dataacquisition unit to encode, convert, and recordon digital tape the spirometry volume signals.

Figure 10 is a schematic representation of thesystem.

Spirometer and Support Electronics

Spirometry examinations were performed onan Ohio Medical Instruments Corporation model800 electronic spirometer. This spirometer dif-fers from the more widely used volume displace-ment “wet” system in that it consists of a drymetal cylinder containing a plastic-faced piston.A silastic rolling membrane forms an air-tightseal between the piston and the cylinder. Thepiston ‘connecting rod is attached to a low-voltage potentiometer, which varies a fixedvoltage signal in a linear manner proportional tothe piston displacement.

Expired air from the forced expiatorybreathing maneuver flows down the connectinghose, into the spirometer, and displaces thepiston, causing the output of a signal from thepotentiometer. This signal is transferred to the

Flow

I I [

Flaw-Spirometer Wlume Storage Strip chart

converter mcillmcqw recorderVolume

IVolunb? I 1

r —. —— —— . . . . —— —1

IAmconvener I

I 9.trackmagnetic I

*Wmcor&r

I.

badselstor I

switch

I

Encoder[EBCDIC)

I12

Iselectorswitches Digimrdw I

L- —. . . .— . . —. —— __ .— -J

Figure 10. Schematic of the NHANES spirometry system

10

flow-volume converter where the signal is fil-1tercd, amplified, and is also differentiated togenerate the flow signal. The outputs from theflow-volume converter are two signals of varying

I voltages, one of which is directly proportional tothe amount of piston displacement (volumesignal) and the other directly proportional to therate of piston displacement (flow signal).

Calibrators

The spirometer is calibrated by means of aninternal volume pump operated by a smallelectric motor that drives a single-lobed camthrough a gear reduction train. When the calibra-tor yoke is attached to the connecting rod of thespirometer piston, and when the electric motoris engaged, the cam rider pushes the piston backand forth, causing the in-and-out movement of aknown volume of room air at known flow rates.When the output volume signal is recorded on apaper tracing, as shown in figure 11, the knownair movement is represented by a graphic sinus-oidal signal, with the trough-to-peak distancerepresenting the volume of air displaced. Forexample, if the calibrator movement causes5,000 milliliters (ml) of air to flow in and out ofthe spirometer, the trough-to-peak distance onany paper recording of the volume signal willrepresent that 5,000 ml. The volume dkplace-ment shown in figure 11 is representative of amidrange calibration.

The Ohio spirometer electronics are presetto convert 1 ml of volume to 1 millivolt (mV);therefore, the trough-to-peak signal will berecorded on the magnetic tape as a difference of5,000 mV from the baseline voltage. Anyvariation from the 5,000-mV calibration signalthus indicates either a change in the calibrator ora change in the volu’me-to-voltage ratio. Forpreliminary data processing purposes, any suchobserved change was assumed to be caused bythe latter. For example, if the mean trough-to-peak difference was found to be 4,950 ml, acalibration factor of 1.01 was used for thesubsequent spirometric analysis. Likewise, amean difference of 5,050 ml would produce acalibration factor of 0.99.

Finally, a manual check of the program-computed standard deviation is performed, and

the coefficient of variation is computed. It isassumed that a coefficient of variation greaterthan 3 percent indicates a daily variation greatenough to warrant the use of different calibra-tion factors for different periods of testing.Specifically, if the coefficient of variation isgreater than 3 percent (that is, *150 ml on a5,000-ml calibra~ion), hardware maintenance is

performed and the affected data set is manuallydivided into smaller batches until the variation isless than 3 percent; a different calibration factoris computed manually for each batch (from thelist of trough-to-peak differences printed out bythe program). Spirometric analysis is performedseparately for each batch. If the coefficient ofvariation is within the 3-percent limit, the dataon that tape are considered to be a single batch.

Before conducting a spirometry test on asubject, the technician electronically calibratesthe spirometer through the use of the signalgeneration capability of the flow-volume conver-ter. This calibration involves switching thevolume-calibration switch from its normal “op-erate” position to the zero position. The techni-cian then s@tches between this position and a+5,oOO mV (d.c.) position. This switching backand forth between O and +5,000 mV activatestransmission of a signal that displays graphicallyas a square wave function, with the bottom steprepresenting O mV and the top step representing+5,000 mV.

The difference between electronic and pneu-matic calibrations follows. A pneumatic calibra-tion involves all parts of the spirometry datacollection system—the mechanical action of thespirometer piston, the mechanical and electronicaction of the potentiometer, the amplifier andfiltering circuits of the flow-volume converter,the analog-to-digital (A/D) converter and filter-ing circuits of the data acquisition unit, and thenine-track tape recording device. Conversely, theelectronic calibration only tests the electronicportions of the instrumentation system. Thus anevaluation of the pneumatic calibration signal isan evaluation of the accuracy of the entire datacollection system, whereas the evaluation of theelectronic calibration signal assists the examinerin locating the source of any variation. Forexample, should the pneumatic variation deviatebeyond certain preset limits on a given magnetic

11

10,OOO

r

8,M0

6,000

4,W0

‘/ —3,320 mV

8 D F

I ,4#XhnV,Ae

o I I I I Io 1 2 3 4 5 6 7 8 9 10

EI.AFSED TIME IN SECON03

Figure 11. Spirometer data-calibration sine wave

ta~e. the troubleshooter would first examine theelectronic calibration output for that tape. Ifthis check revealed a consistent step-functiondifference of 5,000 mV, it could be assumedthat the electronic portion of the system wasfunctioning normally and that the problem layin the pneumatic system (i.e., the Spirometer

itself). Conversely, should the electronic calibra-tion show a significant step-function differencefrom 5,000 mV, it could be assumed that thespirometer was functioning normally and thatthe problem emanated from the electronic cir.cuits somewhere in the line after the spirometer,The pneumatic calibration procedure used inNHANES I (1971-75) was not that which wasrecommended by the American Thoracic Soci-ety (ATS) in its Snowbird Standardization Proj.ect.2 NHANES II (1976-80) practice did, how.ever, follow that procedure.

DataAcquisitionSystem

Spirometry data are recorded on a BeckmanDigicorder Model No. DRS-1OOO digital tapeacquisition system. This unit encodes each signalwith a series of pulses entered by thumbswitches that the computer program identifies asthe recording location, subject identificationnumber, age, sex, race, height, technician code,barometric pressure in millimeters of mercury,and temperature in degrees Celsius. The com-puter uses temperature and pressure to develop aBTPS correction factor that adjusts volume fromambient temperature and pressure saturatedwith water vapor (ATPS) to body temperatureand pressure saturated with water vapor (BTPS).A record of the machine identification numberis also encoded.spirogram to be

This encoding permits eachtraced to the machine it was

12

recorded on and a code (lead) number that’.,indicates to the computer whether the signal wasa calibration or .an FES. Because this 14-leaddata acquisition system is also used to collect a12-lead electrocardiogram on the same subject,unique lead numbers are assigned to the spi-rometry examination. Data are recorded on anine-track digital tape after conversion fromanalog form via an A/D converter. The tape isprocessed directly by a digital computer at alater date.

SPIROMETRY DATA ANALYSIS:PROGRAM DESCRIPTION

The analog spirometric signal is converted todigital data and encoded by the Digicorder andthen recorded on a digital magnetic tape. Eachindividual data record (subject trial, calibration,etc.) consists of 18 digits “representingthe headerand identification information, followed by4,599 data points representing voltages (thespirometer volume curve). AU data are recordedat a rate of 500 samples per second. Asdescribed below, the number of data points isreduced by computer processing to 100 samplesper second, and each resulting data point has asignal resolution of approximately 2 ml ofvolume.

The automated computation of spirometertrial parameters is performed in three stages. Inthe first stage the Digicorder data tape isunpacked (reformatted) and the calibration fac-tor (which corrects voltage-to-volume ratios) tobe applied to the volume data is computed. Inthe second stage the flow data are computedfrom the volume data, the calibration and BTPSfactors are applied to the volume and flow data,and the baseline is computed and removed. Thethird stage is the computation of spirometricparameters from the corrected data.

Calibration Factor Computation(I%@ Stage)

A calibration data record is recognized bytwo conditions in the l%digit header. Thenumber 14 must be found in the channel leadindicator (digits 5 and 6) and at least nine 9’smust be found in digits 7 through 18. The actual

calibration is a sinusoidal wave with the trough-to-peak voltage difference corresponding to a 5-1volume. By computing the average trough-to-peak voltage, a ratio is formed (the calibrationfactor), which is later used to scale all thevolume data.

When a calibration data record is found, thesinusoidal wave data are first reduced from 500samples per second to 100 samples per secondby a five-point average:

Fn=(vm +vm+~ +vm+2+ vm+3+vm+4)/5,

where

m=5(n-l)+ landn = the number of the averaged data point,

1-919.

This averaging reduces the data from 4,599points per record (trial) to 919 points perrecord. Once the data have been averaged, thefirst differences (flows) are computed by therelation

C@n =Fn+l - Fn.

Because the sinusoidal curve may begin witha positive or a negative flow, a starting pointmust be determined. This point is located by ob-serving the first negative flow with a voltage ofless than 4.5 volts (V) (i.e., a point from whichto start looking for the first trough). If no suchpoint is found, the record is ignored and thenext record is read. When the starting point islocated, a search is made for the first positiveflow. From this positive flow, the next 175 vol-ume data points are retained (1.75 seconds;because the sine wave period is 3 seconds, thistime will contain a minimum and maximumvoltage). The trough-to-peak difference is com-puted and the next cycle is checked, beginningwith a positive flow (minimum).

The trough-to-peak differences are com-puted cycle by cycle and record by record untilthe end of the data is reached. If no pneumaticcalibration signals were found on the data tape,processing is terminated. If one legitimate cali-bration is found, the calibration factor is com-puted (cal = 5.0 l/.D volts, where D is the averagetrough-to-peak voltage difference).

13

Figure 11 shows a typical calibration sinewave. At A, the first negative flow is encoun-tered; however, the voltage level is above the4,500-mV threshold. At A’, ‘the first negativeflow with a voltage less than 4,500 mV is found.The search for the next positive flow proceedsto B, where the minimum threshold of 3,320mV is recorded. The search then continues to C,where the maximum of 8,510 mV is found. Thetrough-to-peak difference (B to C) is computedas 5,190 mV. A like difference is computed be-tween D and E, and the average is 5,190 mV or5.190 V. Thus the calibration factor is

5.0 litersCal=

5.190 volts= 0.9634 liters/volt.

Figure 12 shows the data taken from an actualcalibration trial where both the trough and peak(B and C) were examined for stability of the sig-nal. As shown in the figure, 9 data points wererecorded at 3,330, which preceded the trough,and 9 similar data points were recorded, which

I

—— —

/6iA/ : \\i’ 8,5jo+ J:;g,

\:

\ /’. \

\ MoO(n-11) \

\ / \\ / \\\ ;

\

\\

\/ \

\\

\i \

\ i\

\\

\1’

\ 1’ ‘\\\

/

\ ;\ ,’

u&

3,330(n-9).:

3{20—TROUGH

(I I=36J.

3,330:bl = 9)

Figure 12. Oigital data array from a calibration curva showing

trough (B) and paak (C)

~ollowed the trough; moreover, the trough volt-age of 3,320 mV appeared as a continuous stringof 36 samples. The figure also shows a similarstability at the peak end.

Volume and Flow-Rate Signal DataCorrections (Second Stage)

The corrections applied to the spirometrictrial volume and flow rate data consist of a cali-bration factor, a BTPS factor, a reduction of thedata sample rate from 500 samples per second to100 samples per second, and the subtraction ofthe baseline (from the volume data).

BTPS comection.–The BTPS factor is com-puted by using the following formula:

BTPS =“(BP- PH20) ~ (310.16)

BP -47.067 (tk)

where

BP= the barometric pressure (obtainedfrom the header data)

tk = the spirometer temperature in de-grees Kelvin (derived from theheader data)

PH2O = a temperature-dependent water va-por pressure.

A combined correction factor is then com-puted by multiplying the BTPS and calibrationfactors.

Sample rate reduction. –The sample rate forthe 4,599 volume data points (voltages) is re-duced from 500 to 100 samples per second bythe five-point averaging technique applied to thecalibration data. The volume data are then con-verted from centivolts (cV) to liters, and thecombined correction factor is applied to theaveraged volume data. Finally, the flow rates arecomputed by taking the first differences of thevolume data as was done with the calibrationcurve.

Basehize removal. –Because a volume of zeroliters is not generally represented by a zero-voltage signal from the spirometer, a baselinemust be determined and removed from the vol-ume data. This baseline is defined as the averagevalue of the points preceding the estimated be-ginning of the trial.

14

A flow threshold of 1 1 per second, plus anoise tolerance, is used to estimate the beginningof a trial. (The noise tolerance is defined as 30,where o is the standard deviation of all baselinedata being processed and is determined as a sepa-rate computation.) The flow threshoId is basedon the minimum step size in the spirometer sig-nal-which is 1 CV or 10 mV. With a combinedcorrection factor of 1, this method would con-vert 10 ml at 500 samples per second. When thesample rate reduction is performed (five-pointaveraging), the minimum step size would be re-duced to 2 ml. At a sample rate of 100 samplesper second, a volume change of 2 ml would pro-duce a flow rate of O.2 I per second. The l-l-per-second threshold allows for a small deviation ofthe baseline above the 0.2-l-per-second minimumstep size. The noise tolerance is used to increasethe size of the flow threshold if the baseline dataare noisy. Therefore, the first flow rate toexceed the flow threshold marks the end of thebaseline. (This initial estimate of zero time isrefined during the third stage). The baselinedigits are then averaged with the weighted aver-age technique at the net volume point, Avgn= (Avgn- 1,+-Voln )/2. Once the average baselinevolume has been determined, it is subtractedfrom all volume data to remove the recorderbias. If the baseline is less than 15 points long(150 milliseconds (ins) worth of data), the trialis rejected and the data quality code is set to 1,indicating a short baseline.

Spirometer Trial ParameterComputation (Third Stage)

Peak jlow determination. -After the volumeand flow curves have been corrected, the flowdata are searched and the largest value is re-corded as the peak flow, with the correspondingvolume. Predicted peaks are computed on thebasis of the following formulas:

Predicted peak flow for males =-1.0028+ (0.0474 X age) i- (0.2150 X height)

Predicted rseakflow for females =-0.5532

whereyears,

;“(-o.0331 X age) i- (0.1493 X height),

peak flow is in liters per second, age inand height in inches. The data quality

code is set to 5 (Venturi artifact) if the observedpeak exceeds the predicted peak by at least 3.10(where: u male = 1.9585, and o female =1.3321).

Zero time. –Once the peak flow has been de-termined, the zero-time (beginning of trial) esti-mate can be refined (figure 13). This method fordetermining zero time therefore replaces the ini-tial estimate derived in the second stage. Using atriangular method for the flow curve, the zerotime is corrected by the following equation:

V peakto = tpea~-2 —

F peak ‘

where

to = zero time

‘peak = time of peak (referenced to firstguess zero time)

vpeak=volume at peak flowFpeak = the peak flow rate

with the additional constraint that the correctedto not precede the first guess zero time.

End-o f-trz”al determination and FVC calcula-tion.–After the beginning of trial is determined,the end of the trial (EOT) must be found. TheEOT is found by a two-step process. First, thevolume data are searched for a plateau. The

Asunndflowcum

to h

TIME —

Figure 13. .%hematic of flow-volume cuwe showing the rela-tion of zero time to time of peak flow

15

plateau is said to be reached when, starting withthe zero-time volume and comparing at every10th point (every 0.1 second), the volume hasnot increased from the previous O.1-secondpoint. When a plateau is found, the time of theearliest point is recorded as the first guess ofEOT, and the corresponding volume is recordedas the first-guess FVC. If a 10-point plateau isfound, a search is made from this first-guessEOT to the end of the volume data (919 datapoints or 9.19 seconds) for the maximum vol-ume. Current recommendations are for a mini-mum signal duration of 10 seconds; however,design of this system preceded the developmentof these recommendations and the current sys-tem in use conforms to the 10-second durationof signal. If no volume is found larger than thefirst-guess FVC, the previously recorded FVCand EOT are used, and the data quality code isset to zero. If a larger volume is found, a searchis made of the flow data between the first-guessFVC and the maximum volume. If a negativeflow rate is encountered between the first-guessFVC and the higher maximum volume, the EOTis defined as the point just prior to the negativeflow and the corresponding value is recorded asFVC. A negative flow is defined as any O.O1-second flow rate less than zero when the base-line u is zero; when o is not equal to zero, nega-tive flow is equal to the noise tolerance (orminus 30). If no intervening negative flows arefound, the maximum value is defined as theFVC, and the corresponding time is recorded asEOT.

A hesitation artifact (procedural error 7in table A) is reported if a marked decrease inflow occurs after the peak flow for a O.1-secondinterval, which is followed by a marked increasein flow. If EOT is found after the 10-point pla-teau, a check must still be made for prematuretermination at the end of trial. This check isdone by examining the average flow rate duringthe O.50-second period preceding EOT. If theaverage flow rate exceeds 50 ml per second, thedata quality code is set to 8 (premature terminat-ion at EOT) and no further processing is per-formed on that trial. If the EOT is at 9.19 sec-onds and the average flow rate exceeds 50 mlper second, quality control code 2 (prematuretermination by recorder) is set and no furtherprocessing of the trial is performed. If no prema-

ture termination is found, the entire trial be-tween zero time and EOT is searched for inhala-tion artifacts (negative flow rates greater thannoise tolerance). If any are found, the dataquality flag is set to 4 (inhalation artifact), butthe processing continues on that trial.

Calculation of other parameters and qualitycontrol checks. –Once the beginning and endingof the trial have been defined and the peak flowand FVC have been determined, the other trialparameters can be computed. The forced expiat-ory flow rates at 25,50, and 75 percent of FVC(FEF25%, FEF50%, and FEF75% ) are computedfrom the FVC. The volume data are thensearched for a forced expiatory volume of atleast 0.2 L If none is found, the trial is declaredinvalid (procedural e~or 6 in table A) and nofurther processing is carried out. If a volume ex-ceeding O.2 1 is found, the corresponding time isfound by linearly interpolating between thatvolume and the previous one. The same pro-cedure is followed to determine the time for anFEV of 1.21. The FEF200-1zoo ~le is then com-puted as:

W1.2 - ~o.2)lj’J3Jj’200.1 zoo ml = (~, ~“ - to*)

.

In a like manner, the times are determinedfor FEV’S at 1,, 2, 3, 4, 5, and 61. Any volumesthat are not reached have their correspondingtimes set to 99.99. The flow rates are also re-corded at the times of the various FEV values.Finally, any FEV’S that exceed the FVC75%have their corresponding flow rates set to 99.99.

The times and flows for 25, 50 and 75 per-cent of FVC are determined by locating the firstvolume that exceeds that value and recordingthe corresponding time and flow rates. TheFEF25.75% measurement (maximum midmpka-

tory flow rate (MMEF)) is then computed as:

FVC75% - FVCZS%

FEFZ$7S% =‘75%. - ’25%

cForced expiatory flow rate between 200 and

1,200 ml on the volume Curve (FEF200.1 ,200), form-erly known as the maximum expiatory flow rate(MEFR).

16

SUBJECT NO!BER 12-345 SEX U4LE AGE=41 .YEARS HEIGHT=70.Ir4cliEs UEIGHT=178.LBS.

TRIAL* VOLU4E(L)TECH. NO. 2

TIIE(SEC) FLW(L/S) * TIHE(SEC] VOLIE(LJ FLW(L/S) ● TI14E(SEC) VOLWE(L) FLCt4(L/S)*--------------------------------------------------- --------------- ------------------------------------------------------------------ +-------------------

* 0.2 .02 10.31 * 1/4* 1.0 .09 10.74

2.32 6.02 *PEAK* 1/2

.03 .31 12.46 ●

* 1.23.22 *

.11 10.74 $97.10

*-3/41.43 8.81 ●

● 2.01.29 ●

.21 6.66 * 1.0.50

4.233.47

99.992.58 *

* 3.0*

.40 3.65 * 2.0 4.754.26 99.99 ●

1 * 4.099.99 *

99.99 * 3.0M 4.76 99.99 *

● 5.0 3:%4.97 99.99 ● 3.0 4.97 99.99 *

● 6.0 99.‘-)9.99 ●

* .25FVC .11 9.24 - ZERO TINE= 1.54* .50FVC .29 4.73 - FVC= 5.06 HEFR= 11.48

ENO TIME= 5.04 TINE OF FVC= 3.50

* .75FVC .67F#lEF= 4.43 RELIABILITY CO02(S)= 87

1.50

99.99 * 4.0 5.06 99.99 *.YY 99.99

4.0 5.06 9----------------- ----------------------------------------------------- -----------------------------

,-------------.01.09

,--..,--.-. --------11.8210.31

-------------------------------- .* 114 2.28* 1/2 3.26* 3f4 3.88* 1.0 4.22* 2.0 4.75* 3.0 4.95

,-------- --------------------------------- ------------------------●

✍✛ ☛

97q *

I**

.4 ●

I*

5.16 *PEAK .03 .403.22 ●

11.82.10

1.721.42

*8.3~

. so 3.3599.99 ●

-.. .4.25

99.9999.99

● ::: 4.7599.99 *

99.993.0 4.95

99.99 *99.-.

4.0 5.06 99.99

.11

.21

.43

.833.3299.99.11.31

9.456.663.44

99.9999.9999.99

8.384.08

* 3.02 * 4.0

* 5.0● 6.0* .25FVC* .50FVC● .75FVC

* 4.0 5.OG------------------------------ ZERO TINE= 1.06- FVC= 5.06 NEFR= 10.45

------------------------------- . . . . . . . . . ..-- .. . . .. . . . . . . . . . -------ENO TINE= 4.76 TIME OF FVC= 3.70

NNEF= 4.15 RELIABILITY CODE(S)= 87.71 1.93

--------------------------- ---------------------● 0.2 .01 11.82

----- -----------------------------------------------------------------------------------------------------* 114 2.21 6.02 ●PEAK .04 .50 12.25 ●

* 1.0* 1.2

.09

.11

.22

.43

.802.84

99.99.12.31.70

9.029.026.453.4499.9999.9999.997.954.511.93

● 1/2● 3f4● 1.0

3.27 3.01 + .103.90 2.15

1.46 7.52 ●

* .504.26

3.39 2.79 ●

99.99 ●

4.814.30

99.99 ●

99.99 ●

M 4.82 99.99 ●

● 2.0* 3.0

3 ● 4.0* 5.0● 6.0* .25FVC* .50FUC* .75FVC

* 2.0● 3.0 5.03 99.99

----●

* 4.03.0

5.065.04 99.99 *

99.99 * 4.0 5.06 99.99 ●

--------------------------------------------------------------------------------------------.-------- ZERO TINE= .88- FVC= 5.06 MEFR= 10.27

ENO TIME= 3.98 TIW OF FVC= 3.10IWEF= 4.27 RELIABILITY COOE(S)= 87

---

4

,--------- --------------------------- -----------● 0.2 .01 12.25● 1.0 .09 9.67● 1.2 .10 8.81● 2.0 .21 6.88* 3.0 .41 4.08* 4.0 .79 99.99● 5.0 2.83 99.99* 6.0 99.99 99.99● .25FVC .11 8.38* .50FVC .30 4.73● .75FVC .69 1.93

-------------------● 1/4* lj2* 3f4● 1.0* 2.0● 3.0* 4.0

,----,-----------------------------2.28 5.373.30 3.443.93 1.934.31 99.994.83 99.995.03 99.995.06 99.99

---------------------*PEAK .04* .10* .50** i::●

* ?;

.521.513.414.354.835.045.06

12.68 *8.81 *2.79 ●

99.99 ●

99.99 *99.99 *99.99 *

----------------------------------------------------------------------------------------- ---------.- ZERO TINE= .93 ENO TIME= 4.03- FVC= 5.06 MEFR= 10.89

TIME OF FVC= 3.10~EF= 4.27 RELIABILITY COOE(S)= 87

------------------------------ -.----------- .* 114* 1/2* 314* 1.0* 2,0* 3.0* 4.0

------------- --------- ---------------------------------------------- .6.02 ●PEAK .03 .333.22 * .10 1.331.72 * .50 3.3299.99 ● 4.3099.99 * ::: 4.8399.99 * 3.0 4.9699.99 ● 4.0 4.96

------,-----.- .-. ..-******●

.02

.10

.11

.23

.44

.8299.9999.99

.12

.31

2.143.223.884.274.814.964.96

12.897.623.22

99.998.596.453.2299.9999.9999.998.595.372.36

* 3.05 * 4.0

* 5.0* 6.0* .25FVC● ‘ .50FVC* .75FVC

99.9999.9999.99

---------------------------------------------------------------------------------------------------- ZERO TIME= 1.36 ENO TIME= 4.16 TIME OF FVC= 2.80- ?VC= 4.96 MEFR= 10,89 MMEF= 4.44 RELIABILITYCOOE(S)=87

.68

d

-1 Figure 14. Data output sheet for a normal subject showing a set of 5 spirograms

mSUBJECTNUMBER 12-345 SEX t44LE AGE=41.YEARS HEIGHT=70.1NCHES WEIGHT=178.LBS. TECH. NO. 2

TRIAL*VOLUME(L) TIME(SEC) FLOW(L/S) * TIME(SEC) VOLUME(L) FLOW(L/S) * TIME(SEC) VOLUME(L) FLON(L/S)*--------------------------------------------------------------------------------------------------------------------------------------------------.-------

*****

1******

0.21.0

:::3.04.05.06.0.25FVC.50FVC.75FVC

.07

.57

.752.4199.9999.9999.9999.99.25.64

1.36

1.721.50.86

99.9999.9999.9999.9999.991.721.07.43

* 1/4 .55 1.72 *PEAK .06 .18* 1/2

2.79 *.92 .86 * .10 .39

* 3/4 1.20 .% * .501.72 *

* 1.01.00 .86 *

1.40 .86 ** 2.0

1.44 .86 *1.90 99.99 * ;::

* 3.01.91

2.1299.99 *

99.99 * 3.0 2.13* 4.0 2.17

99.99 *99.99 * 4.0 2.17 99.99 *

---------------------------------------------------------------------------------------------------- ZERO TIME=3.47 END TIME= 6.87 TIME OF FVC= 3.40- FVC= 2.17 MEFR= 1.46 MMEF= .97 RELIABILITYCODE(S)=87

----------------------------------------------------------------------------------------------------------------------------------------------------------* 0.2 .08 1.72 : :; .51* 1.0 .62

1.93 *PEAK .051.07

.14.86

2.79 *1.50 * .10

* 1.2 .82 .86.34

* 3/4 1.141.07 *

.86 ** 2.0 2.53

.5099.99

.92* 1.0 1.33 1.97 *

1.50 *

* 3.0 99.99 99.991.0 1.37

* 2.0 1.85.86 *

99.99 *2

2.0* 4.0 99.99 99.99

1.86* 3.0

99.99 *2.10 99.99 * 3.0 2.11 99.99 *

* 5.0 99.99 99.99 * 4.0 2.16 99.99 ** 6.0 99.99 99.99

4.0 2.i6 99.99 *---------------------------------------------------------------------------------------------------

* .25FVC .26 1.72 - ZERO TIME=2.01* .50FVC .69

END TIME= 5.41 TIME OF FVC= 3.40.86 - FVC= 2.16 MEFR= 1.34 MMEF=

*.87 RELIABILITYCOOE(S)=87

.75FVC 1.50 .64 . -----------------------------------------------------------------------------------------------------------------------------------------------------------

* 0.2 .07 1.72 * 1/4 . .52 1.93 *PEAK .05 .15 2.79 ** 1.0* 1.2* 2.0* 3.0

3 * 4.0* 5.0* 6.0* .25FVC* .50FVC* .75FVC

.63

.832.3899.9999.9999.9999.99.26.72

1.48

,86.86

99.9999.9999.9999.99

* 1/2* 3/4* 1.0* 2.0* 3.0* 4.0

.851.131.341.862.132.18

1.501.071.07

99.9999.9999.99

******

.10 ,35

.50 .911.38

H 1.893.04.0

2.142.18

1.93 *1.50 *.21 *

99.99 *99.99 *99.99 *

99.99 ---------------------------------------------------------------------------------------------------1.07.86.43

- ZERO TIME= 1.47- FVC= 2.18 MEFR= 1.31

ENO TIME= 4.77MMEF= .89

TIME OF FVC= 3,30RELIABILITYCOOE(S)=87

-------------------------------------------------------------------------------------------------------------------------------------------------- --------* 0.2 .08 1.93 : ;;; .52 1.72 *PEAK .02 .08* 1.0 .61 .86 .87 1.50 *

3.44 *.10 .29

* 1.2 .80 .86 * 3/42.15 *

1.16 .21 * .50 .90* 2.0

.86 *2.35 99.99 * 1.0 1.36 .86 * 1.0

* 3.0 99.991.38 .64 *

99.99 * 2.0 1.88 99.99 *4

2.0* 4.0 99.99

1.89 99.99 *99.99 * 3.0 7.15 W3.w * 3.0

* 5.0 99.992.15 99.99 *

99.99 * 4.0---- -----2.28 99.99 * 4.0

* 6.0 99.992.28

99.9999.99 *

---------------------------------------------------------------------------.-------_---------------‘k .25FVC .28 1.50 - ZERO TIME= 1.61* m cur 7K 91

ENO TIME- 5.81 TIME OF FVC= 4.20- !=Ilr=? 21 McED= 1 7!2 MMC!=. !M DKI lLIRTI lTV fYIn!=(C\. R 7

..J”, .“ .,- .-. . ,“ -. .,. ,,L, ,. ..#v ,,, ,., . . . .

*

, ..-. ,,- ..., , ---. ,-, - ,

.75FVC 1.65 .21-----------------------------------------------------------------------------------------------------------------------------------------------------

* 0.2 .08 1.72 * 1/4 .72 .86 *PEAK .31 .79* 1.0 .51 .86 * 1[2 1.00 .86

2.58 ** .10 .90

* 1.2 .71 .86 * 3/4 1.24 .861.50 *

* .50* 2.0 2.27

1.29 .86 *99.99 * 1.0 1.42 .43 * I.m

* 3.0 99.99.64 *

99.99 * 2.0 1.92 99.99 * :::5 * 4.0 99.99 99.99 * 3.0 2.17 99.99 *

* 5.0 99.992.i8

99.9999.99 *

* 4.0 2.18 99.99 * ::: 2.18 99.99 *

----2.01

.99.99 *

* 6.0 99.99 99.99 ---------------------------------------------------------------------------------------------------* .25FV( .13 1.50*

- ZERO TIME= 3.06.50FVC .60 .86

END TIME= 6.16 TIME OF FVC= 3.10- FVC= 2.18 MEFR= 1.11

* .75FVCFV4EF= .87

1.37 .64RELIABILITYCOOE(S)=87-

Figure 15. Date output S.heeiforan abnormal subjectshowing a setof 5 splrograms

The volumes and flow rates are recorded at thefollowing time points: 0.25, 0.50, 0.75, 1.00,2.00, 3.00, and 4.00 seconds from zero time.For the times 1, 2, 3, and 4 seconds, if the cor-responding volume is less than FVC75%, thecorresponding flows are set to 99.99. Using thepeak time as the reference time, volumes andflows are recorded similarly for 0.1, 0.5, 1.0,2.0, 3.0, and 4.0 seconds after peak flow. Again,whenever the volume is greater than FVC75%,the corresponding flow rate is set to 99.99.

A final data quality check is performed usingthe FEV’S at O.5, 1.0, and 2.0 seconds from zerotime (FEV03, FEV1 , FEV2 ). If FEV1 is not atleast 4 percent larger than FEV03, or if FEV200is not at least 4 percent larger than FEV1.0, thedata quality code is set to 3 (midtrial prematuretermination artifact).

Figures 14 and 15 are examples of five trialsof normal and abnormal subject data,respectively.

SPIROMETRY DATA ANALYSIS:VALIDITY OF ALTERNATIVE

ALGORITHMS

Methodology

Five separate analyses were performed toevaluate the accuracy, consistency, and validityof the logic selected for calculating five spiro-metric parameters: zero time, EOT, and thethree most commonly used ventilator para-meters (FVC, FEV1.0, and FEFZ5.75%). Thecalculation of the latter three parameters de-pends directly on the determination of the firsttwo, and in this section the ventilator param-eters are used to evaluate the performance ofvarious algorithms for those determinations,both in the presence and absence of electronicor physical noise in the volume signal. Thealgorithms that were chosen as best, and thesubsequent calculation of FVC, FEV1.0, andFEF25 -75%, are described in the previoussection entitled “Spirometer Trial ParameterComputation (Third Stage)”.

The first analysis consisted of comparingcalculations obtained on 19 trials; the compari-

sons for each of the five parameters were basedon three independent measurements:

1. Computer methods as described in theprevious section

2. Manual calculations by technician no. 1

3. Manual calculations by technician no. 2.

Differences between the computer-derived pa-rameters and each of the manually derived val-ues were obtained, aswell as differences betweenthe values obtained by the two technicians onthe 19 trials. The manual calculations wereobtained from curves plotted from the samedigital data that were introduced into thecomputer program and were adjusted by thecorrection factor after subtracting the baselineand averaging to 100 four-figure (nearest milli-liter) digits each second. Figure 16 shows 11 and1 second measuring 11.4 and 16.8 millimeters(mm), respectively. This figure also shows vol-ume and time-base sensitivities reasonably closeto recommended minimums2 of 10 and 20 mm,respectively.

The second analysis was a comparison ofcomputer-derived parameters in which severalalternative algorithms were used. As indicated intable B,f four computer methods were devel-oped for determining zero time and four weredeveloped for EOT identification. The initialmethods for determining zero time and EOTreferred to in the preceding section, entitled“Spirometer Trial Parameter Computation(Third Stage),” constitute methods 1 in table B;moreover, the definitive zero time and EOT timegiven in that section are methods 2 and 3, re-spectively. The extrapolation method (method3) for zero time differs only slightly from thetriangular method (method 2) in that the formerassumes that flow from time zero to the timewhen peak flow occurs is equal to the peak flowrate, whereas the latter method assumes thatflow averages one-half of peak flow during thisshort time interval and that the flow increases in

fTables 1-17 showing the results of these analyses

are grouped at the end of this report, preceding appen-

dix I.

19

—

—

o 1 2 3 4 5 6 7 8 9

ELAPSED TIME IN SEIXNOS

Figure 16. Example of e normal time-volume spirogram

a linear manner between zero time and time before. The methods to determine EOT timewhen peak flow occurs. Both methods are rela-tively easy to use in graphic analysis of spiro-grams, as well as in computer analysis. The ex-trapolation method for zero time has been rec-ommended previously, 13-15 and the volumethreshold (method 4) for determining zero timealso has been considered previously!3 The selec-tion of 30 ml as the threshold (see table B) wasbased on the assumption that one can readgraphic records within 0.5 mm with reasonableaccuracy and that for most spirograrns this incre-ment would be no less than 30 ml when ampli-tude is converted from millimeters to milliliters.Thus zero-time comparisons include both algo-rithms given in the above-mentioned section plustwo similar methods that have been examined

also consisted of two methods described in theabove-mentioned section plus method 2 (slopethreshold method) previously recommendedfor determining EOT time and method 4 (max-imum volume method), which disregards anynegative or zero-flow events from zero time toEOT time.

The third analysis was a comparison of thesealgorithms when a noise signal at each of twolevels of amplitude was superimposed on the 19trials. The first noise signal was a sine wave withan average amplitude of 2 CV (0.02 V) superim-posed on the original 500-samples-per-seconddigitized volume signal. The sine wavelength was0.017 seconds (60 hertz (Hz)). This superim-posed noise did not significantly increase the

20

Table B. Methods for zero-time and end-of-test determinations

Method number and name

ZERO TIME (tn)

Method 1, flow threshold ..................... ...................

Method 2, triangular (triangular extrapolation) .......

Method 3, extrapolation (rectangularextrapolation) . ....................................................

Method 4, volume threshold ....................................

END-OF-TIME (tEOT)

Method 1, Ukpoint plateau ....... .............................

Method 3, negative flow ....................... ...................

Method 4, maximum volume ...................................

Cuwe used

Flow

Flow andvolume

Flow andvolume

Volume

Volume

Voluma

Flow

volume

Critical value(s)

Flow> (1 I parsacond + t),where tis noise toleranca(liters par second)

Flow peak (largest value onflow curve)

Volume at peak

tpaak

Flow peakVolume peak

Volume >30 ml

NOlj+lo - VOlj) <0

(Volj+50 - volj) <25 ml

Flow (-t) liters par secondwhare t is noise tolerance(liters per second)

Maximum (voluma)

Method description

Search flows from beginning of data (baseline) avary 0.01second. Record to as time when critaria are rnati par-cent of flow> 1 + tin liters per second.

Determine peak flow from flow data every 0.01 second;compute to based on following formula

to= twak-2 V p-k, where flow peak is largestvaluaT-@W

on flow curve, V paak is corresponding volume, andtpeak is corresponding time to naarast 0.01 second.

Determine peak flow from flow data every 0.01 second,and compute to based on following formula

to= tmak - V peak, where flow peak is largest valueF peek

on flow curve, V peak is corrasporrding volume, andtpaak is corresponding tima to nearest 0.01 second.

Search voluma every 0.01 second for criteria to be met.Record to as first voluma to equal or exceed 30 m!.

Starting with to,compara volumes every 0.1 second(lOth point). Record tEOT estima of Wfi whankOlj+lo - VOlj} C O.

Starting with to, compare volumes every 0.01 secondwith an intarval of 0.5 second (50th point). RecordtEOT as time (COWNpOdk’Ig’tO VOlj) when(volj+50 - volj) <25 ml.

Starting et to,compare flows every 0.01 second. RecordtEOT as timO COrreSpOfIdhlg tO flOWj -1, whanflOWj < -t.

Starting at to, compere volumas avery 0.01 second.Record tE~T as time corresponding to Voimax.

8,OOO

6,0C0

4,001

2,CQ0

o

NORMAL SPIROGRAM-NO NOISE

‘5 r

ELAP3EDTIME IN SECONDSEXPIATORY VOLUME IN LITERs

NORMAL SPIROGRAM -2 CV OF NOISE

8,fJwr 1s -

o 1 2 3 4 5 e 7 s 9

ELAPSEO TIME IN SECONOS

NORMAL sPIROGRAM-4 CV OF RANDOM NOISE

8,OOU

%?? r

-1

10

/

s

o

-s

15

0 2 4 6

EXPIATORY VOLUME IN LITER$

1-

o 2 4 6

ELAPSEO TIME IN SECONDSEXPIATORY VOLUME IN LITERs

Figure 17. Normal spirogram (time-volume and flow-volume curves) with noise signals superimpoti

22

calculations for either the flow threshold forzero time (method 1) or EOT time (method 4);however, the noise tolerance (t) was equal to 11per second when the second noise signal wassuperimposed—a 4-cV amplitude random sinewave with the same wavelength. Thus the flowthreshold for to was defined as 41 per secondwith the 4-cV noise and the cutoff for asignificant negative flow was -31 per secondwith the 4-cV noise when using method 3 fortEoT. Figure 17 shows the results of two levelsof noise on a spirometry signal displayed as atime-volume curve and as a flow-volume curve.Note the increased visual sensitivity of theflow-volume representation to detect noise.

Because the 19 trials were obtained fromfour well-trained subjects with normal ventila-tor parameters, the second and third analyticroutines were also applied to a set of abnormalspirograms that were derived from the 19normal spirograms by computer manipulation ofthe time and volume variables. Therefore, thefourth analysis was a comparison of algorithmsfor abnormal spirograms with superimposednoise signals. Figure 18 shows an example of atime-volume and flow-volume representation ofan abnormal spirogram with superimposed noise.

The electronic spirometry system was care-fully adjusted to present as noise-free a signal as

possible. This entire baseline signal was ex-amined by visually reviewing a computer listingof all 19 trials; when no noise signals wereobserved, it was concluded that the spirometrysignal was noise free. This conclusion that thesignal was relatively noise free should be under-stood in terms of the necessary 2-ml thresholdfor a trigger of one bit evident on the computerlisting of the 500-signals-per-second data. (Thisone-bit trigger was described in the sectionentitled “Baseline Removal.”) The computerlisting showed a constant 1,050 digital voltagereading for all 44,000 digits examined at 500samples per second over a baseline signal totalingalmost 30 seconds. AU four persons used in thetests were symptom free, and each entered intoa brief training session on forced expiatorymaneuver. Each of the four persons performedthe maneuver correctly and no trials wererejected because of subject error or poor motiva-tion. With an excellent or relatively noise-freesignal and carefully trained and apparentlyhealthy subjects, one would expect to find fewquality control flags and computed values simi-lar to manual values, especially when usingrigorous algorithms for zero time and EOT.Alternative algorithms might be more suitablefor “abnormal” subjects tested on equipmentwith a random-noise problem. For example,

8,000

e,ow

4,000

2,0W

o lu6_u_ ‘_rL_o 1 2 3 4 5 6 7 6 9 0 2 4 6

ELAPSEO TIME IN SECONDS EXPIATORY VOLUME IN LITERS

Figure 18. Abnormal spirogram (time-volume and f low-volume curves) with noise signalssuparimposad

23

when calculating zero time, a 1,OOO-ml-per-second flow threshold (method 1) was usedinitially. Zero time was defined as the intervalpreceding the first nonzero flow by examiningeach 0.0 1-second interval. This determinationimplies that a volume difference of 10 ml ormore adjusted for BTPS would be the firstnonzero volume when comparing successive vol-ume signals (5 volume signals averaged to 100signals per second). When a noise signal issuperimposed on a noise-free signal, this flowthreshold might be expected to be too rigorous,and an extrapolation or volume method mightbe preferred. Thus four alternatives, includingthe triangular method (method 2) describedpreviously, were compared to determine zerotime and the impact of noise signals. Similarly,various end-of-trial alternatives were comparedto a rigorous negative flow algorithm (method3), as indicated in the following section. Thefour end-of-triaI alternatives included in thisanalysis include the two approaches described inthe section entitled “End-of-trial determinationand FVC calculation .“

Zero.T’ime and FEV1.0 Calculations

Zero time was initially identified as the first0.0 l-second signal achieving or exceeding a1-1-per-second flow. For manual readings, thetechnicians were asked to identify the firstdetectable departure from baseline. The techni-cians then measured the l-second time and thevolume at this specific elapsed time. Both timeand volume measurements were attempted tothe nearest 0.1 ml, recognizing that the fractionsof a millimeter were only rough estimates. Thecomputer labeled the zero-time signal as theO.01 second that was previous to the flowthreshold signal and identified the FEV1.0volume as the 100th baseline-corrected digitalsignal after zero time.

For the first trial (figure 16), the computercalculated a value of 1.50 seconds for zero time,indicating that the first significant departurefrom baseline occurred with digitized flow signal151, located on the 100-sample-per-second arraythat had been derived by averaging the previous500-sample-per-second array. Technician no. 1examined the visual display of the same 100-

sample-per-second digits and estimated that thefirst significant departure from baseline hadoccurred at a point measured as 1.52 seconds, or25.5 mm of baseline from the initiation of asignal on the plot. Technician no. 2 estimatedthis point at 1.56 seconds, or 26.2 mm ofbaseline. The paired differences of zero time forthis first trial were calculated as follows:

● Computer minusseconds

● Computer minusseconds

. Technician no. 1= 0.04 seconds

technician no. 1 = 0.02

technician no. 2 = 0.06

minus technician no. 2

The average paired differences and standarddeviations of the 19 differences for the abovecomparisons are given in table 1. The conclusionwas that the two technicians had sets of zerotimes the means of which were not statisticallydifferent when compared as paired differences;however, technician no. 2 identified a mean zerotime at an elapsed time significantly later com-pared with the computer-calculated mean zerotime.

The FEVI.0 manual calculation began fromthe manually identified zero time, and then thevolume was estimated at 1 second from thispoint. If the manual readings were slightlybiased to late zero-time estimates compared withthe computer, the expectation would be thatmanual FEV1.0 values would be slightly greaterthan the computer values. The mean computerFEVI o value for 19 trials was 3.9741 (standarddeviation = 0.471), whereas technician no. 1 andtechnician no. 2 had measured mean values of4.002 and 3.9771, respectively. These pairedmean differences were not significantly differ-ent. Although the manual calculations by onetechnician disagreed slightly with the zero timeobtained by the computer program, both techni-cians were in remarkable agreement (with anaverage difference of less than 30 ml) with thecomputer-calculated FEV1.0 for 19 trials, andboth technicians agreed on FEV1.0 within amean of 30 ml. Note that 30 ml is considerablymore than one bit (2 ml) when the computer is

24

used to calculate the FEV1.0, but only aboutone-third of a millimeter when volume is meas-ured from the visual display.

The second test compared the computer-derived values for FEVl.9 when three alterna-tive methods for determming zero time wereused (see table B for description of methods). Asjust indicated for trial no. 1, the zero-time valuefor the flow threshold, as defined above, was1.50 seconds of elapsed time of baseline signal;if the triangular method had been used, it wouldhave placed zero time at 1.52 seconds. More-over, by the extrapolation method, zero timewould have been at 1.54 seconds, and by the30-ml volume threshold method it would havebeen 1.53 seconds. Table 2 presents meandifferences of zero-time values for all 19 trials.Thus the extrapolation method (method 3)resulted in a significant shift toward later times,but no significant differences were found for thetriangular and the volume threshold methodswhen compared with the threshold method. Itwas predicted that the extrapolation methodwould result in excessive mean FEV1.0 valuesfor the 19 trials when compared with the otherthree methods. Table 3 presents the meanFEVI.0 results. The paired mean FEVI.0 differ-ences and standard deviations were calculated;significant differences from the flow thresholdmethod were obtained for both the volumethreshold (p < 0.01) and the extrapolation(p< 0.05) methods, as indicated in table 4.This first comparison of methods indicates that(1) zero time and FEVI.0 are in remarkableagreement for the flow threshold method andthe triangular method as well as in agreementwith manual calculations, (2) the volume thresh-old is of intermediate agreement with the flowthreshold method, and (3) the extrapolationmethod would appear to yield a sizable bias fortrial estimates of zero-time and FEV1.0 testingfor subjects with normal spirograms and anoise-free spirometry system. Figure 19 illus-trates each of the four zero-time computations,showing a representative delay in zero time thatresults from the extrapolation method. As indi-cated from data in table 4 this del,ay results in anaverage error in FEV1.0 in the range of 1-2percent.

After the four methods were compared byusing the same 19 signals, a third set ofcomparisons with a noise signal superimposed onthe test signal was performed. For trial no. 1,table 5 gives the shifts in FEVI.0 that occurredwith a 2-cV amplitude sine wave (slight noise),and with a 4-cV random-amplitude sine wave(greater noise). No significant shift occurred inthe mean FEV1.0 for 19 trials with increasingnoise when the flow threshold method was used;that is, the no-noise FEVI.0 was 3.974, theslight noise FEV1. o was 3.971, and the greaternoise FEV1.0 was 3.979. These differences wereconsidered negligible when the 3.974 value forthe noise-free trial was used as the basis forcomparison; the extrapolation method (method3) showed significant effects on FEV1.0, astable 6 indicates. Methods 1, 2, and 4 werereasonably similar to one another when themean-paired differences were used as a basis forcomparison. A close examination of the spirom-etry curves showed that the noise signal oftenincreased the magnitude of peak flow anddelayed its occurrence; thus the extrapolationmethod would yield increased FEV1.0 values.

The fourth test was an attempt to have thecomputer create abnormal curves from the 19trials by mathematically reducing the volumes atany one time point by first multiplying thevolume by O.5 and then extending the timerequired for each expired volume by multiplyingthe time scale by 3.0, as figure 20 shows. Forexample, the FEV1. o for the first trial wasreduced as follows:

. Normal–Trial no. 1 computer-calculatedFEV1 .0 =4.191

. Abnormal–Trial no. 1 computer-calculated FEV1.0 = 1.331

The mean of 18 of the 19 values from thetransformed trials was 1.2511. (By performingthis mathematical transformation, the baselinewas also extended in time; in the process, trialno. 7 was rejected because the baseline was tooshort. Analysis of 18 abnormal trials was under-taken, however, because the loss of trial no. 7

1.I

t?.Volume I

t:ehr;d

tO*Trlangulw

method

II

II11IIIIIIII

x2X

to,

Flow

NOT& Tk uppr wrw is a timwo!unw plotwllh a uprimpmd line extmpduhig a tangmt from the pdnlof Inflection to eatinwte zem tbw by Uw exuqmlation metlwd (nwhod 3). Also WI&ml in UM insertii the we of cillnwhg 10 by k Irimgda! method (method 2) by sinw3y doubling the time from @ tlow. The upp+r p30t h a volume.lime ddi d~fi the lower plot ha flw.tbne dlqhy. Fmm the lowr #alone an ree [he CIMCproximity of !0 by k tdmguhr mahod to IIM1 of tk flow thrcdmld method, an intwmedhb position of the volume tbmih.dd method, md the &!ayed zero the of the cxtrap+lilbn nkthod.

Figure 19. Manual calculation of toshowing a representation of the 4 altarnativa methods

would have no bearing on our inferences.) The three mean paired differences and standardzero-time and FEV1.0 calculations used for deviation for zero time and FEV1.0 by using thethese 18 trials again were based on the flow results of the noise-free signal as a basis forthreshold method, and the outcome was com- comparison. Noteworthy differences, in thepared with the other methods. Table 7 gives the range of an error of 3 percent for FEV1.0, were

26

ELAPSED TIME IN SECONDS

Figure 20. Example of an abnormal time-volume spirogram

found when the fIow threshold results werecompared with those obtained by direct extrap-olation from peak flow (method 3); however,the triangular method of extrapolation frompeak flow (method 2) yielded results similar tothe flow threshold results. The volume thresholdmethod (method 4) was compared with the flowthreshold method and produced paired differ-ences that were statistically significant but werenot in the error range as noted above for theextrapolation method.

In the fifth and final test, the introductionof 2- and 4-cV sine wave random noise had noconsistent effect on zero time compared withthe noise-free flow threshold method. Table 8presents the results. The shift in zero time was aconsistent delay in the to from that obtained onthe noise-free signal when the flow thresholdmethod was used as the index for these abnor-

mal spirograms. The extrapolation method(method 3) continued to show the greatestpaired difference when compared with the flowthreshold index; moreover, at both noise levelsthe volume threshold method yielded a smallermean difference for zero time when comparedwith the triangular method of extrapolationfrom peak flow. The flow threshold methodshowed an interesting zero time shift with noise,as follows:

. A’–F1ow threshold method with noise-free si<gnalminus flow threshold methodwith 2-cV noise = – 0.076.

. A“-Flow threshold method with noise-free signal minus flow threshold methodwith 4-cV noise = +0.046.

27

Table 9 shows t. w the shift in zero timeobtained by various alternative methods andsuperimposed noise signals combine to yielderrors in FEV1.0, by using again the meanFEVIOO from 18 abnormal spirograms obtainedby the flow threshold method and a noise-freesignal as the index for comparison. The paireddifferences are expressed in table 9 both in litersand as a percentage of the index mean FEV1.0.The only method that showed an error in excessof 5 percent was the extrapolation method(method 3), which overestimated FEV1.0 in therange of 8-9 percent. The conclusion was thatalthough normal spirograms analyzed by theextrapolation method would result in an error of1-2 percent, much greater errors are found whenabnormal spirograms with or without noise areanalyzed with this method. The only methodthat showed an average error in FEV1.0 lessthan 3 percent was the volume thresholdmethod (method 4). The flow threshold methodapplied to abnormal spirograms showed a muchgreater mean FEV1.0 change with noise (-38and +46 mI for the two noise signals given intable 9) compared with the data given previouslyfor normal spirograms and the same two noisesignals (-3 and +15 ml). By comparing theresults in table I 6 with those in table 9, thegreater impact of noise on the FEV1.0 ofabnormal spirograms is evident for all fourmethods. In table 6, all except the extrapolationmethod yielded errors less than 1 percent of themean noise-free FEV1.0 by the flow thresholdmethod, although the errors shown in table 9 are8-9 percent for the extrapolation method com-pared with approximately 2-4 percent for theother three methods.

In both the normal and abnormal spirogramsin the presence of 4 CV of noise, the volumemethod (4) is affected least since it more closelyapproximates the threshold reference measure-ment (method 1) than methods 2 or 3. A closeexamination of the spirometry data reveals thatthe additional sensitivity achieved by using thetriangular method is jeopardized by the need fora clear peak flow signal. This problem is severelyincreased in the presence of abnormal datawhere flow rates are relatively low and peakflow rates are not well defined. (Usually theflow curve demonstrates several points in close

proximity to each other in the area around thepeak flow.) In many cases, noise caused flowpoints following the peak flow to be elevated toa greater amplitude than the true peak flow rate,which caused the time of peak flow rate tooccur later. This development generally resultedin the zero-time point occurring to the right ofthe threshold reference point. Method 4, whichdoes not rely on any flow rate data to identifyzero time, was relatively unaffected by the highnoise levels. This fkding would suggest that in arelatively noise-free system (< 2 cV of noise),method 2 is superior to all other methods,although in a system with considerable noise (4CV or more) method 4 would be the preferredtechnique. Computerized spirometry data acqui-sition systems with noise levels similar to thatsimulated in this study generally should not beused to collect data because measurement accu-racy would be severely compromised.

End-of-Trial, FVC, and FE F25.75%Calculations

The same five tests were performed for theother end of the spirogram and the volume ofFVC. Because fractions of FVC are used as thefirst steps to determine FEF25.75% volumepoints, the calculation of FVC is critical to the10giC for FEFz&7E%.

The mean value for the initial estimate (10-point method–method 1) of end-of-trial timeand the mean FVC were both considerably dif-ferent from the mean values for end of trial andFVC obtained by the more rigorous negativeflow method (method 3)3 This difference isshown in table 10. A significant difference be-tween these two methods is also evident forFEFZ$7S%. A smaller FVC due to early termina.tion would be expected to result in a muchhigher FEF25-75% because of a shift of this slopetoward the left where flows tend to be greateron normal spirograms (table 10). The two tech-nicians were asked to identify the FVC plateauand mark the beginning of this plateau as theend of test. By using this approach, the twotechnicians next calculated FVC and FEFz&7s%for each of the 19 trials. The end-of-trial time

gRefer to table B for a description of methods.

28

and the FVC values were in remarkable agree-ment (see table 11); however, technician no. 2had a mean FEF25.75% that was significantlyhigher than that of technician no. 1. The datacollected by each technician were initially com-pared with the 19 values obtained by the morerigorous negative flow method that was appliedfor each of the three measurements. The meanpaired difference results are given in table 12.Technician no. 1 reported FEF25.75% measure-ments that were significantly lower than thoseobtained by the computer algorithm consistingof the negative flow method; otherwise, no note-worthy differences were observed.

Two alternative methods to determine theEOT were next compared with the negative flowand the 10-point plateau methods. The firstalternative was to consider the EOT to be theend point of the first O.5-second interval wherethe average flow over this 0.5-second intervalwas equal to or less than 50 ml per second(method 2); the second alternative (method 4)was the same as the first, but extended the EOTto a larger value whenever the maximal FVCvalue. occurred at a later point (irrespective ofany intervening negative flows). Figure 21 illus-trates each of the four EOT computations.

Data previously presented on the 19 trialsin table 13 show the means and standard devia-tions for the four methods plus the results ob-tained by ~ average of the two manual measure-ments for each trial. The calculations by the twotechnicians agreed with the results from boththe negative flow and the maximal volume meth-ods, but were very different from the results ob-tained with the other two methods. It was con-cluded that a choice between method 3 andmethod 4 would be difficult. This conclusion issupported by comparisons of these two methodswith the average manual measurements. Table14 provides differences of less than 1 percent forFVC and approximately 1 percent forFEFZ$T5%. This COIIIpFirkOII suggested that themeans of the average of manual readings are ap-proximately midway between the results of thetwo computer methods, perhaps somewhatcloser to the maximum volume method. Themean FVC by the technicians was 15 ml morethan that determined by the negative flowmethod and 12 ml less than that from the maxi-

mum volume method; in addition, the meanFEF25.75% obtained by the two technicians was0.0541 per second higher (+1.4 percent) for thenegative flow method, but only O.018 1 per sec-ond lower for the maximum volume method.These differences between method 3 andmethod 4 and the average manual readings weresmall and not statistically significant. In a sec-ond analysis, the paired differences from thetwo methods and the data from each technicianwere compared separately (table 15). The sec-ond comparison also showed no statisticallysignificant differences eXCept fOr FEFz$75%,

where three of the four differences were signifi-cant (p <0 .05), the only exception being theO.080-l-per-second difference of the negativeflow method.

The next analysis compared the four end-of-trial methods as related to the effect of the tworandom noise signals that were superimposed onthe normal spirogram. Table 16 gives these re-sults for EOT, FVC, and FEF25.75% by compar-ing the mean paired differences for the noisesignal obtained by the negative flow methodwith the other three methods. The effect on thethree parameters of the 2-cV noise was toshorten the signal, reduce the FVC by a prema-ture EOT, and increase the FEF25-75%. For the4-cV random noise signal, the trend was to pro-long the EOT time, increase the FVC, and de-crease the FEF25-75% for the negative flow andmaximum volume methods; but the trends wereinconsiste~t.

For the final analysis, abnormal spirogramswere created and noise signals were superim-posed, as described previously. Only 15 of the19 trials could be interpreted at the tail end ofthe curve for all noise levels because of the lackof a plateau at the end of the trial when noisewas superimposed. Table 17 shows the meanpaired differences.

Again, the 2-cV noise signals produced con-sistent effects of reducing EOT and FVC and ofincreasing FEF25-7s%; similarly, the 4-cV signalprominently showed relatively small reductionsin FVC and FEF25.7~% when the negative flowand maximum volume methods were used.These two methods most closely simulated thetechnicians’ measurements; the changes in theFVC, when noise was added to the signal, were

29

(A) METHOO 1

10.pOint platmu FVC and EOT

Identified hereFVC and EOT

Volume

‘*

—

0.1 second

8,0C4

6,000

4,0133

2,0W

o

(Cl METHOO 3

(B) METHOO 2

EOT

c+: : ::~:~<25ml

I I /

FvC

AB

o 1 2 3 4 6 6 7 8 9

ELAPSEO TIME IN SECONOS

(0) METHOO 4

~

Negative flow

NOTES

FVC

::::: <26mI

NOTE MetiM2criteria wpmddifh@ervolum fwndmwdlenofprcsmx 0[ my lnwvening IWS6W fkm.

MeIiwd 1 show the WC md EOTfdenlillcds the OmtPint of a 10.poht plateau.Mclhcd2 show the WC and EOTas the flint pwlntwllh[” a OS,econd windowwhere the volumeincrease k 1,s OUn2S ml.Method3 shows the WC and EOT ,, lh, lint point Pd., to the fimt n,gmtivt Ow of O.01I ~,seccmd.Mwh.d 4 lncotpoc*lesmethods 2 and 4 criteria hut cx.mndsEOTand WC to a larger valuewhenetm the highest palm on tie vol.nw CUIVCcccurmd at * later pdnt thmeder, Inupeclhn ortmy

lntmvml”g negmk flow.

Figure 21. Manual calculation of end of trial showing the 4 alternative methods

30

all less than 3 percent when compared with thenoise-free computed values; and for FEF&7ij%the changes were under 5 percent.

The two methods appeared to have a reason-able accuracy when compared with technician-measured EOT time, FVC, and FEF25.75%. Inexamining the graphs of individual trials wherethe results of the negative flow method differedfrom those of the maximum voIume method,locations on the spirographic curve were ob-served where an instantaneous negative flowcould have occurred, and in many of these in-stances the technician may have noted a termin-ation hesitation. The recognition of instantane-ous negative flows is beyond the resolution ofthe human eye; however, if a negative flow con-tinues over a duration of about 0.25 seconds,such an event would likely be identified as anend of test. In an effort to test this hypothesis afifth method for EOT was developed, whichidentified the first point in time followed by anaverage negative flow of O.25-second duration.The analysis is not given in this report; however,it showed no appreciable accuracy advantagewith abnormal spirograms in the presence ofnoise. Another possible method not yet testedthat may yield a more accurate estimate ofrelatively low FVC and FEF25.75% in the pres-ence of noise would be a protracted negativeflow of 0.25 second. Therefore, either of twomethods (negative flow or maximum volume)are recommended with the reservation thatneither are very accurate under conditions of ahigh noise-signal ratio. The slope thresholdmethod recommended in this report is differentfrom recently published recommendations .l’2In this report the spirometry signal was 9.19 sec-onds in duration rather than the recommendedminimum of 10 seconds; however, conclusionswere not affected because all trials of these“normal” persons were terminated within the9.19-second signal duration when the slopethreshold was used. One subject had a terminalflow pattern suggesting that if the signal dura-tion would have been extended to 10 or moreseconds, methods 3 and 4 may have producedFVC values even larger than reported herein andthe differences with method 2 would have beeneven greater.

SUMMARY AND CONCLUSIONS

Because FEV1.0 and FVC are the most im-portant ventilator parameters, three importantconsiderations were: (1) that these two param-eters be estimated accurately by computer meth-ods when compared with manual calculations;(2) that the measurements be reproducible withthe superimposition of noise in the signal; and(3) that the sequence of computational stepsproceed in a logical way, including the determi-nation of significant digits used in the adjust-ment for baseline signals, BTPS conditions, andcalibration information.

With a logical computation of spirometrysignak, FEV1.0 depends most on the accuracyand consistency of zero time, and FVC dependsmost on the accuracy and consistency of theEOT time. For zero time, any of three methods(methods 1, 2, and 4) appeared satisfactory;however, the extrapolation method (method 3)led to excessive FEV1.0 values even withoutsuperimposed noise or when subjects had abnor-mal or low values. Moreover, when the latterconditions did pertain, the error of method 3was shown to be in an 8-9-percent range. A de-fense of the use of the triangular method(method 2) as the definitive method used in theNHANES program can be made because somesubjects have hesitation patterns on forced expi-ration as do certain spirometers with high iner-tia; both would seem to require some form oflinear extrapolation from a peak flow. Method 2was shown to be essentially equivalent to meth-ods 1 and 4, and the triangular extrapolation canbe as easily adapted to manual spirometry as theunacceptable peak flow back extrapolationmethod. One can calculate method 2 zero timeby doubling the time from peak flow to method3 zero time as shown in figure 19. Figure 22provides a summary analysis of the comparativezero-time algorithms used in determining theFEV1.0 in both normal and abnormal spiro-metric data, with and without noise superim-posed on the signal. The means and standarderrors of paired differences from the recom-mended algorithm (triangular, method 2) arepresented as the index in this figure rather thanmethod 1.

31

NORMAL OATA-NO NOISE

Flow thmhold

Triangle

Extrapolation

Volume threshold

NORMAL OATA-2 CV OF NOISE

Flow threthold

Triangle

Extrapolation

Volume threthold

NORMAL OATA-4 CV OF NOISE

Flow threshold

Triangle

Extrapolation

Volume threshold

ABNORMAL OATA-NO NOISE

FIOWthre+old

Triangle

Extmpolation

Volume threshold

ABNORMAL OATA-2 CV OF NOISE

Flow threshold

Triangle

Extrapolation

Volume threshold

ABNORMAL OATA-4 CV OF NOISE

Flow threthold

Trian~ie

Extrapolation

Volume threshold

t--

t

I I

I I

t ii

I II I

b

T

+

+

I

--i

-0,6 -0.4 -0.2 0,0 0.2 0.4 0.6

MEAN DEVIATION IN LITERS

Figure 22. FEV1.0 enelysis–meens and standard deviations (30) of paired differancas from triangular extrapolation (mathod 2)

measuramants

32

NORMAL DATA-NO NOISE

I(f.point plateau

SIOPethrwhold

Negative flow

Maximum volume

NORMAL DATA-2 CV OF NOISE

l&pOlnt plateau

Slope thrmhold

Nq@ve flow

Maximum volume

NORMAL OATA-4 CV OF NOISE

Io.point plateau

.SIOIMthreshold

Nqative flow

Maximum volume

ABNORMAL DATA–NO NOISE

lD.pOlnt plateau

SbPo thrsshold

Negative flow

Maximum volume

ABNORMAL OATA-2 CV OF NOISE

lD.point plateau

SIOPOthmhold

Negative flow

Maximum volume

ABNORMAL DATA-4 CV OF NOISE

lflpolnt plateau

Slope threshold

Negative flow

Maximum volume

1-

t--

It

I

t--

t-

1

t

III

I II

()

bI

I I1---l

II

I

i

-1.6 -1.2 -0.8 -0.4 0.0 0.4 0.8 1.2 1.6

MEAN OEVIATION IN LITERS

Figure 23. FVCanalysis-means andstandard deviations (3u)ofpaired differenms from negative flow (method 3) measurements

33

Similarly, the slope threshold method(method 2) for determining the end of trial wasshown to produce an unacceptable bias in theI?VC by lowering FVC by more than 50 ml com-pared with the negative flow method (method 3)or the maximum volume method (method 4).When either of the latter methods was examined,the FVC accuracy was within 3 percent of man-ual readings, even with a modest superimposednoise and with abnormal trials with FVC valuesin the range of 2 1. Figure 23 provides a sum-mary analysis of the comparative EOT algo-rithms for both normal and abnormal data, withand without noise present on the signal. Themeans and standard errors of paired differencesfrom the recommended algorithm (negativeflow, method 3) are presented. ~

The procedures used to collect spirometricdata during NHANES I represent the state-of-the-art at that time; further improvements havebeen made for NHANES II, reflecting advancesin available instrumentation, such as recordingof flow and volume data on sensitive strip-chartrecorders. In the future, further refinements areanticipated by use of on-line computeriiied tech-

niques that judge data quality and reliability andby use of terminal displays showing data trendsto assist the attending technician with his or heracceptance decisions.

The computer program criteria describedusing the recommended algorithms for determi-nation of zero time (method 2) and end-of-testdetection (method 4) represent the state-of-the-art to date, superseding those recommendationsgiven in the current NHLBI standards.1 (Thesetwo algorithms, as described in the section en-titled “End of trial determination and FVCcalculation,” have been implemented for cur-rent analyses.) More work is required on thedevelopment of quality control criteria to pre-clude the acceptance of questionable data andon development of algorithms to determine thebest trial. Regarding the latter issue, this pro-gram applies the criteria specified by the ATSrecommendations. However, more sensitive pro-cedures must be explored, such as thosesuggested by Discher and Palmer where a 10-parameter procedure was used to determine theoptimal total curve.17

000

34

REFERENCES

1Epidemiology standardization project: III. Recom-,mended standardized procedures for pulmonary testing.Amer. Rev. Resp. Dk. 118:55,1978.

2Reporton Snowbird Work Shop on Standardizationof Spirometry. Amer. Thor. Sot. 3:20, 1977.

9National center for Health Statistics: Methodologicproblems in children’s spirometry. Vital and HealthStatistics. Series 2-No. 72, DHEW Pub. No. (PHS) 78-1346. Public Health Service. Washington. U.S. Govern-ment Printing Office, Nov. 1977.

4Rosner, S, W,, p~mer, A., wad, S. A,, Abr~~, S,,and Cacercs, C. A.: Clinical spirometry using computertechniques. Amer. Rev. Resp. Dis. 94:187, 1966.

5Ayers, W. R., Ward, D. A., Weihrer, A. et al:Description of a computer program of the forced expira-

‘ tory spirogram. Part II. Validation. Comp, Biomedq Res.2:220,1969.

6National Center for Health Statistics: Quality con-trol and measurement of non-sampling error in theHealth Interview Survey. Vital and Health Statistics.Series 2-No. 54. DHEW Pub. No. (HSM) 73-1328. HealthServices mid Mental Health Administration. Washington.U.S. Government Printing Office, Mar. 1973.

7National Tuberculosis and Respiratory Disease Asso-ciation: Chronic Respirator Dkease Screening Manual.New York. National Tuberculosis and Respiratory Dis-ease Association, 1968.

8Natio~ center for H~~tb Stat&tics: Forced vit~capacity of children 6-11 years, United States. Vital and

Health Statistics. Series 1l-No. 164. DHEW Pub. No.(PHS) 78-1651. Public Health Service. Washington. U.S.Government Printing Office, Feb. 1978.

9Discher, D. P., Massey, F. J., and Hallett, W. Y.:Quality evaluation and control methods in computerassisted screening. Arch. Environ. Heofth 19:323, 1969.

10 Rosner, S. W., Abraham, S., and Caceres, C. A.: Ob-server variation in spirometry. Dis. Chest 48:265, 1965.

11 Nation~ center for He~tb Statktics: ~A~Efj Ex-

amination Staff Procedures Manual for the Health andNutrt”tion Examination Survey, 1971-1973. Part 15a.Public Health Service. Washington. U.S. GovernmentPrinting Service, June 1972.

12Dayman, H. G.: Flow control during forced expira-tion. Amer. Rev. Resp. Dis. 95:887, 1967.

13Smith, A. A., and Gaensler, E. A.: Timing of forcedexpiatory volume in one second. A mer. Rev. Resp. Dir.112:882, 1975.

14K_er, R. E. ad MoxT& A. H.: Clinical ~lmonaryFunction Testing. Salt Lake City. Intermountain Tho-racic Society, 1975. p. 1.

15Knudson, R. J., Slatin, R. C., Lebowitz, M. D., andBurrows, B.: The maximal expiatory flow-volumecurve. Normal slandards, variability, and effects of age,Amer. Rev. Resp. Dir. 113:587,1976.

16Discher, D. P,, ~d Palmer, A.: Development of anew motivational spirometer-Rationale for hardwareand software. J. Occ. Med. 14:9, Sept. 1972.

35

LIST OF DETAILED TABLES

1. “Meen, standard deviation, and signif icence level for paired differences between zero-time methods on 19 trials for method 1and manual method, by 2 technicians ........................................................................................................................................ 37

2. Mean, mean paired difference, standard daviation of diffarances, and significance level for zaro-time measuramants, by 4mathods of computation on 19 trials ......................................................................................................................................... 37

3. Mean forced expiatory volume at 1 second (FEVI .CS) for 19 trials, by 4 zero-time methods .................................................... 37

4. Mean paired difference, standard deviation of differences, and significance level for forced expiatory volume at 1 second(FEV1 ..), by zero-time method pairs........................................................................................................................................ 38

5. Mean forcad expiatory voluma at 1 second (FEV1 ..), by 3 Ievals of noise and zero-time method ............................................ 38

6. Mean paired difference for forced expiatory voluma at 1 second (FEV1 ..), by 3 levels of noise and zaro-time methodpairs ......................................................................................................... ................................................................................. 38

7. Mean paired difference, standard deviation of differences, and significance level for zero time and forced expiatory volumeat 1 second (FEV1 ..), by zero-time method pairs on 18 abnormal spirograms.......................................................................... 39

8. Mean paired difference between zero-time methods, by 3 levels of noise for 18 abnormal spirograms....................................... 39

9. Maan paired difference and percent difference for forced expiatory volume at 1 second (FEV1 ..) between zero-time meth-ods, by 3 levels of noise for 18 abnormal spirograms................................................................................................................. 39

10. Mean and standard deviation for end-of-trial time, forced vital capacity (FVC), and forced expiatory f low rata between 25and 75 percent of the FVC (F EF25.75%) with mean paired difference, standard deviation of differences, and significancelevel, by 2 methods of detecting the end of trial ........................................................................................................................ 40

11. Mean and standard deviation for end-of-trial tima, forced vital capacity (FVC), and forced expiatory f low rate bewaen 25and 75 parcent of the FVC (F EF25.75%) with mean pairad difference, standard daviation of difference, and siwif icancelevel, by 2 technicians ................................................................................................................................................................ 40

12. Mean paired difference, standard deviation of differences, and significance level for end-of-trial time, forcad vital capacity(FVC), and forced expiratow flow rate between 25 and 75 percent of the FVC (FEF2S.75%) between manual method by 2technicians and mathod 3 of end-of-trial criteria ........................................................................................................................ 41

13. Mean and standard deviation for end-of-trial time, forced vital capacity (FVC), and forced expiatory flow rate between 25and 75 percent of the FVC (FEF25.75%), by 5 mathods of datecting the end of trial ............................................................... 41

14. Percentage differences in end-of-trial time, forced vital capacity (FVC), and forced expiatory flow rate between 25 and 75percent of the FVC (FEF25.75%) between 4 methods of detecting the end of trial and the average manual reading................. 41

15. Mean paired difference and standard deviation of diffarances for end-of-trial time, forced vital capacity (FVC), and forcedexpiatory flow rate batwaen 25 and 75 percent of the FVC (F EF25.75’%) between manual methods by 2 technicians andmathods 3 and 4 ........................................................................................................................................................................ 42

16. Mean paired difference from index or nagative f low method without noise for end-of-trial time, forced vital capacity (FVC),and forced expiatory flow rate between 25 and 75 percent of the FVC (F EF25.75%), by 3 levels of noise on 18 normalspirograms and 4 end-of-trial methods ....................................................................................................................................... 42

17. Mean paired difference from index or negative flow method without noise for end-of-trial time, forced vital capacity (FVC),and forced expiatory flow rate between 25 and 75 percent of the FVC (F EF25.75%)c by 3 ievek of noise on 15 abnormalspirograms and 4 end-of-trial methods ....................................................................................................................................... 43

36

Table 1, Mean, standard deviation, and significance level for paired differences between zaro-time mathods on 19 trials for mathod 1and manual method, by 2 technicians

Paired

Pairsdifferences

P

~d sd

Seconds

Computer and technician #1 ............................................................................................................................. -0-007 0.037 NsComputw and technician #2 ,,, ,,,, ,., .......!.. ,,. .!.,.,.,.,....,.. ..................................!..... ................!.. .......................... -0.020 0.030 <0.05

Technician #1 and technician #2 ....................................................................................................................... -0.013 0.030 NS

NOTES: %d = mean paired difference; sd = standard deviation of difference; p= significance level; NS = not significant.

Tabla 2, Mean, mean paired difference, standerd deviation of differancas, and significance Iavel for zero-time measurements. by 4methods of computation on 19 trials

[Zero time in seconds]

I IZero.time

mathod ●ndmean

1 (0,926)1 (0.926)1 (0,926)

NOTES: ~

Alternative Pairad differenceszero-time method

and mean ~d sd P

2 (0,917) .............................9................................................................... .......................... -o.~ 0JJ51 NS3 (0.984) . ...................... .......... .................................... ...... .......................................... .. .... +0s358 yo: <0:4 (0.950) .................e. .. .. ............ .................. ............ .......... .......................... .... .............. .... +0.024 .

= mean paired difference; #d = standard deviation of difference; p = significant level; NS = not significant.

Table 3. Mean forced expiatory volume at 1 second (F EV1 .0) by 19 trials, by 4 zero-time mathods

IZero-time method I Mean FEV1.0

Liters

1........................,,! .,,,..,......,,. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..................... .............. 3.974

2 ... .... . ... .. ... . .... ... . ... ... ... .. .. ... .. .... .. ... .. .... .. . ... ... .. . .... ... .. .. ... .. ... .. .. ... .. ... .. ... .. .. ... ... .. .. ... ..... ................................ ..................... 3.966

....!.......,,.. .. .. ... ... .. ... ... .. .. . .... . ... .. ... .. ... ... .. .. ... .. ... .. .. ... .. .... .. .. . .. .. .. . .... .. ... .. ... . .... . ... ... .. ... .. .. ... ... ...... ................................ ..... 4.034

: .. . .. .. .. .... .. .... .. .. . ... .. .. ... .. .... ... . ... .. .. ... ... ... .. .. ... .. .. ... .. ... .. ... .. .. ... ... . .... .. ... .. .. .. .. ... ... .. .. ...... ................................ ..................... 4.002

37

Table 4. Mean paired difference, atanderd deviation of differences, and significance Iavel for forced expiatory volume ●t 1 second(FEVI .0), by zero-time method pairs

Paired diffarencasZero-time method pairs

~d sd P

1 and 2 ............................................................................................................................................................1 and 3 ............................................................................................................................................................1 and 4 ....... ................................................................... .................................................................................

-0.008+0.060+0.028

NOTES: ~d = mean paired difference; sd = standard deviation of difference; p = significance level; NS = not significant.

Table 5. Mean forced expiatory volume at 1 second (FEV1 .0), by 3 levels of noise and zero-time method

[1 trial]

Liters

_-L0.055 NS0.037 <0.050.014 <0.01

Zero-time method

1...................................................................................................................................................................

J-SlightNo .

‘oi= (HV)

Greaternoise(4 Cv)

Mean FEV1.0 (liters)

4.19 4.19 4.214.21 4.19 4.164.23 4.24 4.224.22 4.22 4.21

Table 6. Mean peired difference for forced expiatory volume at 1 second (FEV1 .0), by 3 levels of noise end zero-time method pairs

Zero-tire method pairs

1 and 2 .................................................................................................................................................1 and 3 .................................................................................................................................................1 and 4 .................................................................................................................................... .............

lp<o.os.

Mean paired diffaranca (liters)

-0.008QO.080

tO.028

+0.008%0.083

+0.027

-0,022”+0.027+omo8

38

Table 7. Meen paired difference, standard deviation of differences, and significance level for zero time and forced axpiretory volume at1 second (FEV.I .0), by zero-time method pairs on 18 abnormal spirograms *

Zero-time paired FEV1.0 paired

Zero-time method pairsdifferences differences

~d ‘d P ~, ‘d P

Seconds Liters

1 and 2 .........................................................................\...... ..................................1 and 3

0.028 0.094 NS 0.022 0.073 NS.................................................................................................................. 0.179 0.173 <0.05 0.177 0.114 <0.05

1 end 4 .................................................................................................................. 0.042 0-042 <0.05 0-033 0.037 q35

NOTES: %d = mean paired difference; sd = standard deviation of difference; p = significance level; NS = not significant.

Table 8. Mean paired difference between zero-time methods, by 3 levels of noise for 18 abn

Zero-time method pairs

1 and 2 ............. ..................................................................................................................... ............”..........1 and 3 ........................................................................................................................................................1 and 4 ........................................................................................................................................................

rmal spirograms

I I

No Slight Greater

noise noise noise(2 Cv) (4 Cv)

Mean paired difference(seconds)

0.028 0.037 0.1770.179 0.127 0.2650.042 0.001 0.099

Table 9. Maan paired difference and percent difference for forced expiatory volume at 1 second (FEV1 .0) between zero-time methods,by 3 levels of noise for 18 abnormal spirograms

No noiseSlight noise Greater noise

(2 Cv) (4 Cv)Zero-time method pairs

~dPercent ~d Percent ~d

Percentdifference difference difference

Liters Liters Liters

1 and 2 0,,,,,,,. ,!,, ,,,, ,, ,,, ,,, ,, .,,..,,,.,., .,,,0,.,,.,,...,.,., ... ,,. .,,, ,,,,.. ,,, ... . . .. .. . ... 0.022 1.76 0.049 3.92 0.056 4.48

1 and 3 ............................ ....... ..................... ...................................1 and 4

0.177 9.35 0.106 8.47 0.105 8.39................................................. ...... .................................... 0.033 2.64 0.029 2.32 0.021 1.68

A’ ................................................................................................... . . . -0.038 3.04 . . .A“ .............................................. .................................................... . . . . . . . . . . . . 0.046

. . . . . .3.68

NOTES: A’ = F1OWthreshold method with noise-free signal minus flow threshold method with 2 CVof noise; A“ = flow thresholdmethod with noise-free signal minus flow threshold method with 4 CV of noise.

39

Table 10. Mean and standard daviation for end-of-trial time, forcad vital capacity (FVC), and forced expiatory f low rate batwaen 25and 7!ipercent of the FVC (F EF25.75%) with mean paired difference, stendard deviation of differences, and significance level, by2 methods of detecting the end of trial

Parameter

End-of-trial time .................................................... ................................

FVC ................ .......................................................................................

I I.

Method 1 Method 3 Paired differenms

Seconds

4.164 I 0.606 i 6.024 { 1.688 \

Lkers

4,787 I 0.474 [ 4.939 [ 0.436 I

Liters par second

-1.860 ] 1.830

-0,152 I 0.124

4.287 0.719 3.977 0.905

P

<0.01

<0.01

<0.01

NOTES: ~= mean;s. = standard deviation; ~d = mean paired difference; sd = standard deviation of difference; p = significance level;NS = not significant. “-

Table 11. Mean and standard deviation for end-of-trial time, forced vital capacity- (FVC), and forced expiatory flow rate between 25and 75 parcent of the FVC (FEF25-75%) with mean paired difference, standard deviation of difference, and significance level, by 2technicians

Parameter

End-of-trial time .......................................................................................

FEF2&75% ..............................................................................................

I I

~

Seconds

6.258 I 1.627 I 6.244 I 1.693 I 0.014 [ 0.219

Liters

4,967 j 0.426 I 4,951 I 0,435 I 0.006 I 0.025

Liters per second

NOTES: X = mean; Sx = standard deviation; Xd = mean paired difference; Sd = standard deviation of difference; p = significance level;NS = not significant.

P

NS

NS

:0.01

40

Table 12. Mean pairad difference, standard daviation of differences, and significance Iavel for end-of-trial tima, forcad vital capacity(FVC), and forced expiatory flow rate between 25 and 75 Percent of the FVC (FEF2~75%) between manual method by 2technicians and mathod 3 of and-of-trial critaria

Paramater

End.of-trial time .........................................................................................................

FVC ............................................................................................................................

F~F2&7fj% .................................................................................................................

Paired differencesbetween technicianno. 1 and method 3

TSeconds

0.234 I 1.040

Liters

0.018 I 0.070

Litars parsecond

*

P

NS

NS

<0.01

Paired differencesbetween technicianno. 2 and method 3

Seconds

0.220 I 1.034

Liters

0.012 I 0.072

Liters persecond

H!W!!!NOTES: ~d = mean paired difference; sd = standard deviation of difference; p = significance level; NS = not significant.

Table 13.

P

NS

NS

NS

Maan and standard daviation for end-of-trial tima, forced vital capacity (FVC), and forcad aspiratory flow rata between 25and 75 percent of the FVC (F EF25.75%), by 5 methods of datecting the end of triel

Parameter

End-of.trial time.............................................

FEF26.75% ...................................................

Method 1Avarage

Mathod 2 Method 3 Method 4 of manualreadings

F .$x F s~ F s~ z s~

Seconds

4.164 I 0.606 I 5.036 I 1.077 [ 6.024 I 1.689 I 6.342 j 1.611 I 6.251 I 1.657

liters

4.787 I 0.474 I 4.878 I 0.482 [ 4.939 I 0.436 I 4.966 I 0.444 I 4.954 I 0.430

Liters par second

NOTES: ~= moan; Sx = standard deviation.

Table 14. Percentage diffat’encas in end.of-triel time, forced vital capacity (FVC), and forced expiatory flow rata bstween 25 and 75percant of the FVC (FEF2&75@ batwean 4 methods of datacting the end of trial and the average manual reading

Parameter Method 1 Method 2 Mathod 3 Method 4

Percent

End-of-trial time ....................................................................................................... -33.4 -19.4 -3.6 +1.5FVC .......................................................................................................................... -3.4 -1.5 –0.3 +0.2FEF25.75% .............................................................................................................. +8.3 +4.6 +1.4 -0.5

41

Table 15. Mean pairad difference and standard deviation of differences for end-of-trial time, forced vital capacity (FVC), and forcedexpiatory flow rate betwaen 25 and 75 percent of the FVC (F EF25.75%) between manual methods by 2 technicians and methods3 and 4

Paramater

End-of-trial time ................................................................

FVC ...................................................................................

Pairad differences betwean I Pairad differences betweentechnician no. 1 and: technician no. 2 and:

Method 3 Method 4 Method 3 Method 4

~d ‘d ~d ‘d ~d ‘d ~d Sd

0.234 I 1.040 I

0.018 I 0.070 I

Seconds

0.100 I 0.359 I 0.220 [ 1.034 I -0.086 I 0.325

Liters

0.009 I 0.021 [ 0.012 I 0.072 I -0,016 I 0.270

Liters par second

-0.189 0.321 -0.116 0.222 +0.080 0.324 +0.1 12 0.270FEF25.75% ........................................................................

NOTES: %d = mean paired difference; sd = standard deviation of difference.

Table 16. Meen paired difference from index or negative flow method without noise for end-of-trial time, forced vital capacity (FVC),and forced expiatory flow rate betwean 25 and 75 percent of the FVC (F EF2s75%), by 3 levels of noise on 18 normal spirogramsand 4 and-of-trial methods

Parameter and method

End-of-trial time

4 ................................................................................................................................ ............2 ............................................................................................................................................1 ................................................................................................................................ ............

FVC

4 ................................................................................................................................ ............2 ............................................................................................................................................1 ........................................................................................................................................... .

FEF25.75%

3 ................................................................................................................................ ............

4 ................................................................................................................................ ............2 ............................................................................................................................................1 ................................................................................................................................ ............

EEETE!EMean paired difference (seconds)

,..

+0.320-0.943-1.818

-1.740 I +0,476

-0.943 +0.473-0.943 -1.427-1.762 -1.532

Mean paired difference (liters)

. . .

+0.022-0.061-0.304

r.l.-

. . .

-0.073+0.T37-0.310

-0.142 -0.030

-0.057 +0.001–0.061 -0.115-0.150 -0.163

an paired difference(liters per second)

+().352 I -0.127

Table 17. Mean paired difference from indax or negetive flow method without noise for end-of-triel time, forced vitel capacity (FVC),and forced expiatory flow rate between 25 and 75 percent of the FVC (F EF25.75%), by 3 levels of noise on 15 abnormalspirograms and 4 end-of-trial methods

Parametar and method

End-of-trial time

4 .............................................................................................................................................2 ............................................................................................................................................

1 1 ................................................................................................................................ ............

FVC

4 .................................................,.. .,.....!..4.............................................................................2 ........................................................................................................................................... .1 ............................................................................................................................................

FE F2S.75%

4 ................................................................................................................................ ............2 ................................................................................................................................ ............1 .........................................................!...... ............................................................................

Greater noise(4 Cv)

Mean paired difference (seconds)

. . .

0.000-2.318-3.151

-3.050 I +0.1 55

-2.310-2.318-3.064

Mean paired difference (liters)

+0.1 55-2.446-3.120

. . . -0.144

0.000 -0.080+0.555 -0.083-0.370 -0.153

Meen paired difference(liters per second)

. . . +0.1 34

0.000 +0.089+().074 +0.083

0.000 +0.138

-0.050

-0.050-0.214-0.765

-0.033

-0.033+0.079+0.1 00

43

APPENDIXES

- CONTENTS

I. Glossary . . . . . . . . . . . . . ..o . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..o . . . . . . . . . . . . . ..o.......o.. 45

II. General Spirometric Test Procedure Used by NHANES ................................................................. 47Instructions for Older Chddmn and Adults ............................................................................... 47Instructions for Chddrcn 6-10 Years of Age .............................................................................. 47

APPENDIX FIGURE

I. l’hrcc phases in a forced expiatory spirogram ............................................................................... 45

44

IAPPENDIX I

GLOSSARY

Trial.–The term “trial” is used to specify asingle effort to perform the forced expiatoryspirogram (FES) m’imeuver. A test set comprisesfive trials; however, a spirometric examinationmay comprise one to three test sets. The FESalways has three parts as shown in figure I andthe accompanying explanation.

● phase I-effort-dependent flow,, entailingpeak flow for the breath.

● Phase II–constant deceleration of vol-ume exhaled (critical flow).

● Phase 111–terminal leakage flow.

10

5

0

PHASES

I II Ill

I I I I

I ICritical flow onzet

o 2 5

VOLUME IN LITERS

Figure i. Three phases in a forced expiatory spirogram

Procedural error. –A violation of the ex-pected shape (morphology) and completeness ofthe spirometric flow-volume signal is known asa “procedural error.” If artifacts are observed,the indication is that one or more of the follow-ing procedural errors has occurred during thetest: an inhalation or hesitation during the per-formance of the test, a less-than-expected initialrespiratory thrust, an absence of the character-istic decay portions of the flow and volume dueto a premature termination of the expiatoryeffort before reaching residual volume, or flowor volume values higher than clinically possible,perhaps due to a Venturi error.

Detection of these artifacts is cause to chal-lenge the validity of the test effort. For exam-ple, if an inhalation artifact is observed, the testhas no clinical value and should be discarded. Incontrast, if a Venturi phenomenon is observedbut the flow and volume history meet the re-producibility criteria on another trial, the cri-teria for reliable data have been fulfilled and thetest should be declared valid (in this example,the higher values observed may be because a per-son is exceptionally fit, e.g., an athlete).

Best h-al. –The best trial refers to a particu-lar trial, within a set of five, that clearly demon-strates the optimum presence of the two vari-ables that are of the most interest (i.e., thrustand sustained expiatory effort). Thrust, asmeasured by the flow rate, is judged throughthe visual observation of the flow-volume curvevelocities. Sustained expiatory thrust thereforeresults in the presence of higher flow ratesthroughout the spirogram, in contrast with othertrials in which less thrust was applied.

Variations in thrust can be reflected by over-all reductions in the peak flow rate (PFR), the

45

forced expiatory flows at 25 percent, 50 per-cent, and 75 percent of the vital capacity, theFEF25.75%, or in all of these. In contrast, sus-tained expiatory effort is judged by observationof the FVC signal on the volume (horizontal)axis of the oscilloscope display. Because all flowrates are volume dependent (except for thePFR), all flow rates must be judged in the con-text of the largest FVC. The best trial is the onethat exhibits the highest flow rates in the pres-ence of the largest FVC (and in the absence ofobvious procedural errors).

Biologic variation often causes some varia-tion of these values from trial to trial, such asthe presence of the highest observable flow rateson a trial in which the FVC is slightly lower thanin another trial, or conversely, a trial where alarger FVC contains slightly lower flow rates.During an examination, the technicians must usetheir best judgment to identify the best trial,taking into consideration the phenomenon ofbiologic variation; when the technician consci-

entiously applies reliability criteria (describedin the following section), this problem will re-solve itself.

This “eyeball” type of judgment is validatedand supplemented during data processing by adigital computer at a later time when each flowand volume parameter in the spirometnc curve isaccurately measured and compared with likemeasures in other curves in the triaI sequence. Inthis way, a consistent method of identifying thebest and most reliable data is used, whichreduces the probability of unacceptable dataquality.

Reliability. –Reproducible spirographic trac-ings are assumed to represent the very best ef-forts of the examinee. Reliability is determinedby comparing the flow and volume characteris-tics of the best and second-best spirograms in atest set of five trials by determining the repro-ducibility of the two trials. If limits of repro-ducibility are violated, the best trial is declarednot reliable, and the test sequence is repeated.

000

APPENDIX II

GENERAL SPIROMETRIC TEST PROCEDUREUSED BY NHANES

Instructions for Older Childrenand Adults’ 1

Examinees follow four simple steps duringthe test procedure:

. Inhaling as deeply as possible (examineemaximally inhales from room air).

. Holding in all the air while placing thelips tightly around the mouthpiece,being careful to keep the tongue underthe mouthpiece.

. Blasting out of all the air.

. Maintaining the expiatory effort until

all the air is out.

These directives, that is, a deep inspiration,proper placement of the mouthpiece, and theforceful exhalation of air into the tube, are dem-onstrated to the exarninee by the attending tech-nician. The technician overemphasizes the laststep by doubling up in an effort to squeeze outair by full exhalation.

Before commencing the first trial, the ex-aminee should have the mouthpiece firmlyseated in the hose with both hands around thehose an inch or so from the mouthpiece. Thestandard instructions for the test procedure areas follows:

● “Take in a deep breath of air, as far asyou Carlgo.”

● “Hold in the air and place your lipstightly around the mouthpiece .“ (Movethe hose toward the subject so he or shewill insert mouthpiece; when the mouth-piece is in place, press the recorderbutton.)

● “Keep blowing! ! ! Keep blowing!!! Get itall out! ! ! “Keep blowing!!!” By monitor-ing the oscilloscope, the technician candetect when the volume is not increasingand can judge when 1 or 2 seconds ofeffort at full expiration have transpired.

For subsequent trial instructions, the techni-cian must repeat the last four standard instruc-tions or use a special instruction for solving amisinterpretation based on the observations thathe or she has made. A complete test set requiresthe recording of five spirograms.

Instructions for Children 6-10 Yearsof Agel 1

In the current NHANES and in previous sur-ve ys, children 6-10 years of age were tested. Thefollowing spirometry instructions were appliedto the less behaviorally mature children; thisgroup included most of the children 6 and 7

years of age (except for a few poised childrenwith mature behavior), about half of the chil-dren 8 years of age, and the least mature of thechildren 9 and 10 years of age.

Technicians were instructed to proceedslowly, to be patient with the children, to usefew words, and to demonstrate mostly by vivid,clear example. A typical instruction situationwas

“We want to see how your lungs work. Wewill measure how much air you can take in(accompanied by a strenuous demonstra-tion) and how much you can blow out—ashard and as fast as you can.”

At this point, the technician asked the child ifhe or she could blow up a balloon quickly. The

47

response usually gave the technician an indica-tion of how ready the child was to perform asatisfactory spirogram. The instruction contin-ued with “Let me show you”:

“Take in as much air as you possibly can.Like this.“

“Hold it all in until I tell you to blow.”

“Lips closed around the tube like this.”

“When I say ‘blow,’ blow out all of your airas fast and hard as you can. Keep blowingout hard until I tell you to stop .“

The child was then given one or two practicetrials in a relaxed way. If still unsure of the

child’s understanding and ability to perform, thetechnician repeated the entire demonstration,stressing anything that the child did not do per-fectly (i.e., reemphasizing by use of exaggerateddemonstration rather than words how to per-form correctly).

A complete spirometry test set also com-prised five trials. If further instruction betweenttials was necessary, it was vivid, pertinent, andbrief. If no satisfactory data were obtained dur-ing the test, a decision was made either to havethe child come back later during the examina-tion session if the technician held hope forbetter trials, or mark the test as unsatisfactory ifthe technician believed that a satisfactory testcould not be obtained because the child wasfrightened, too confused, or did not understand.

000

48 W.S. GOVERNMENT PRINTING OFFICE 19S0 341-161/24 1-3

VITAL AND HEALTH STATISTICS Series

Series 1. Progrwrns and Collection Procedures. –Reports which describe the general programs of the NationalCenter for Heafth Statistics and its offices and divisions and data collection methods used and includedefinitions and other material necessary for understanding the data.

Series 2. Data Evaluation and Methods Research. –Studies of new statistical methodology including experi-mental tests of new survey methods, studies of vital statistics collection methods, new analyticaltechniques, objective evaluations of reliability of collected data, and contributions to statistical theory.

Series 3. Analytical Studies. –Reports presenting analytical or interpretive studies based on vital and healthstatistics, carrying the analysis further than the expository types of reports in the other series.

Series 4. Documents and Committee Reports. –Final reports of major committees concerned with vital andhealth statistics and documents such as recommended model vital registration laws and revised birthand death certificates.

Series 10. Data From the Health Interview Survey .–Statistics on illness, accidental injuries, disability, use ofhospital, medical, dental, and other services, and other health-related topics, all based on data collectedin a continuing national household interview survey.

Svric.s 11. Data h’rom the Health Examination Survey and the Health and Nutrition Examination Survey .–Datafrom direct examination, testing, and measurement of national samples of the civilian noninstitu-tionalized population provide the basis for two types of reports: (1) estimates of the medically definedprevalence of specific diseases in the United States and the distributions of the population with respectto physical, physiological, and psychological characteristics and (2) analysis of relationships among thevarious measurements without reference to an explicit finite universe of persons.

Series 12, Data From the Institutionalized Population Surueys. –Discontinued effective 1975. Future reports fromthese surveys will be in Series 13.

Series 13. Data on Health Resources Utilization. –Statistics on the utilization of health manpower and facilitiesproviding long-term care, ambulatory care, hospital care, and family planning services.

Series 14. Data on Health Resources: Manpower and Facilities. –Statistics on the numbers, geographic distri-bution, and characteristics of health resources including physicians, dentists, nurses, other healthoccupations, hospitals, nursing homes, and outpatient facilities.

Series 20. Data on Morta[ity. –Various statistics on mortality other than as included in regular annual or monthlyreports. Special analyses by cause of death, age, and other demographic variables; geographic and timeseries analyses; and statistics on characteristics of deaths not available from the vital records based onsample surveys of those records.

Series 21. Data on Natality, Marriage, and Divorce. –Various statistics on natality, marriage, and divorce otherthan as included in regular annual or monthly reports. Special analyses by demographic variables;geographic and time series analyses; studies of fertility; and statistics on characteristics of births notavailable from tbe vital records based on sample surveys of those records.

Series 22. Data From the National Mortality and Natality Surueys. –Discontinued effective 1975. Future reportsfrom these sample surveys based on vital records will be included in Series 20 and 21, respectively.

Series 23. Data From the National Survey of Family Growth. –Statistics on fertility, family formation and dis-solution, family planning, and related maternal and infant health topics derived from a bienniaf surveyof a nationwide probability sample of ever-married women 15-44 years of age.

For a list of tides of reports published in these series, write to: Scientific and Technical Information BranchNational Center for Health StatisticsPublic Health ServiceHyattsville, hid. 20782

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