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Plethysmography-derived Respiratory Rate Scott D. Kelley, M.D. Chief Medical Officer Respiratory and Monitoring Solutions Covidien

Workshop: Postoperative Monitoring

Conflict  of  Interest  Disclosure:  Covidien    Employee  (Salary,  Equity,  Op<ons)  

Manufacturer  Nellcor™  Respira<on  Rate  

Respiratory  Abnormali<es:  A  Warning  Sign  

1.  Hillman  KM,  et  al.  Dura<on  of  life-­‐threatening  antecedents  prior  to  intensive  care  admission.  Intensive  Care  Med.  2002;28:1629-­‐34.  2.  Schein  RM,  et  al.    Clinical  antecedent  to  in-­‐hospital  cardiopulmonary  arrest.  Chest.  1990;98:1388-­‐92.  

Reason  for  551  ICU  admissions  from  general  ward  1  

Abnormality   %  

Respiratory   33  

Cardiovascular   20  

Neurologic   14  

Sepsis   13  

Gastrointes<nal   9  

Others   6  

Trauma   1  

Pathophysiologic  altera=ons  prior    to  cardiopulmonary  arrest  2  

Altera<on   %  

Respiratory   38  

Mul<ple  abnormali<es  

27  

Metabolic   11  

Cardiac   9  

Neurologic   6  

Event   Odds  Ra=o  (95%  CI)  

Bradypnea  (RR  <  6)   14.4  (2.6  -­‐  80.0)  

Tachypnea  (RR  >  30)   7.2  (3.9  -­‐  13.2)  

Loss  of  consciousness   6.4  (2.9  -­‐  13.6)  

Decrease  of  consciousness   6.4  (2.6  -­‐  15.7)  

Hypotension   2.5  (1.6  -­‐  4.1)  

Hypoxemia  (SpO2  <  90%)   2.4  (1.6  -­‐  4.1)  

Extremes  in  Respiratory  Rate  Predict  Mortality  

Extremes  of  respira=on  rate  are  strong  predictors  of  in-­‐hospital  mortality  on  the  general  ward  

Buist  M,  et  al.  Associa<on  between  clinically  abnormal  observa<ons  and  subsequent  in-­‐hospital  mortality:  a  prospec<ve  study.  Resuscita2on.  2004;62(2):137-­‐141.  

Prospec<ve  study  of  6,303  pa<ents  on  the  general  hospital  ward.    

Independent  Predictors  of  Mortality  

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Gaps:  Respira<on  Rate  Monitoring  on  the  GCF  • “The  main  problem  iden<fied  when  ademp<ng  to  introduce  an  early  warning  system  to  the  acute  general  ward  areas  in  one  hospital  was  the  general  paucity  of  monitoring  of  pa<ent  observa<ons  by  the  nursing  team.  ”  1  Ø     Respira<on  Rate:  only  parameter  recorded  <50%  of  the  <me1  

• Clinically-­‐collected  values  miss  a  number  of  events2  

1. Hogan. British Journal of Nursing. 2006;15(9):489-91.

2. Curry et al. Anesthesiology 2002; 96:A1173.

Detection & Threshold # of Events Rate (per hour)

Charted spot-check SpO2 < 90% 9 0.0037

Continuous Oximetry SpO2< 90% 1213 0.497

Respira<on  Produces  Photoplethysmogram  Changes  

Spontaneous  respira=on  

produces  well-­‐characterized  PPG  modula=ons1  

1.  Meredith  DJ,  Clihon  D,  Charlton  P,  Brooks  J,  Pugh  CW,  Tarassenko  L.  Photoplethysmographic  deriva<on  of  respiratory  rate:  a  review  of  relevant  physiology.    J  Med  Eng  Technol  2012;36:1-­‐7    

     

Respira<on  Related  Changes  in  Photoplethysmogram  

Baseline Modulation

Ligh

t Tra

nsm

issi

on

Frequency ModulationExpireLi

ght T

rans

mis

sion

Amplitude Modulation

Ligh

t Tra

nsm

issi

on

Central Respiratory Drive

↑ Heart Rate ↓ Stroke Volume ↑ Venous Return

↓ Intrathoracic Pressure

Diaphragm

Meredith DJ, Clifton D, Charlton P, Brooks J, Pugh CW, Tarassenko L. Photoplethysmographic derivation of respiratory rate: a review of relevant physiology. J Med Eng Technol 2012;36:1-7

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Photo  Pleth  Signal  

Respiration Features

   Baseline  Modula<on  

 Amplitude  modula<on  

   Respiratory  sinus  arrhythmia  

   

Wavelet  Transform   Autocorrela<on  

Signal  Processing    

Pleth-­‐based  Respira<on  Rate  Fundamentals  

Respira<on  Components  

Pleth-­‐based  Respira<on  Rate  Technology  Algorithm-­‐based  Averaging  Approach  

= RRX+1

= RRX+2

= RRX+3

A respiration rate is calculated every 5 seconds = RRX

“Averaging window” = 45 seconds

Reported rate ( @ X+3) = Weighted average of RRX, RRX+1, RRX+2, RRX+3, with additional logic

1.  Addison et al. (2012) Developing an algorithm for pulse oximetry derived respiratory rate (RRoxi): a healthy volunteer study. J Clin Monit Comput; 26(1): 45-51.

Pleth-based Respiration Rate Accuracy (General Care Floor Patients)

Distribu=on  of  Differences  Between  RRPLETH  and  RRETCO2  

Bland-­‐Altman  Density  Plot    

Addison PS, Watson JN, Mestek ML, Ochs JP, Uribe AA, Bergese SD. Pulse oximetry-derived respiratory rate in general care floor patients. J Clin Monit Comput. May 6, 2014.

•  N=  63  pa<ents  •  Range  of  respira<on  rates:4.7  to  32.0  breaths  per  minute.   •  16,980  paired  observa<ons  between  pleth-­‐based  Respira<on  Rate  

and  capnography-­‐based  reference    

LOW  

POINT  DEN

SITY  

HIGH  

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Pleth-based Respiration Rate Accuracy

Study   N   Setting  Results (BrPM)  

Mean Diff   S.D.   RMSD  

FDA Submission Trial* 53   Hospital GCF Cohort   0.1   1.98   1.98  

26   Healthy Volunteer Cohort   0.37   0.78   0.96  

79   Combined GCF & Healthy   0.18   1.65   1.66  

J.Clin Mon & Comp. 2012   139   Adult Healthy Volunteers   -0.23   1.14   1.16  

J.Clin Mon & Comp. 2014   63   GCF Patients   -0.48   1.77   1.83  

CHEST 2012   22   COPD   0.7   1.6   1.74  

CHEST 2012   12   CHF   0.4   1.5   1.55  

ASA 2012   12   PACU   -0.5   0.7   0.86  

ASA 2012   17   Obese volunteers   0.07   1.8   1.8  

IAMPOV 2012   12   Cold Room Hypoxia Study   -0.18   0.72   0.74  

Pleth-­‐based  respira<on  rate  has  an  accuracy  (mean  diff)  of  ±  1  breaths  per  min    when  compared  to  respira<on  rate  derived  from  a  capnography-­‐based  reference  

*  Nellcor™  Respira<on  Rate  Product  labeling,  US  510(k)  cleared  (K111933).  Studies  yielded  23,243  paired  observa<ons.  Range  of  respira<on  rates  observed  was  4  to  34  breaths  per  minute.  RMSD  =  root  mean  square  devia<on.  ClinicalTrials.gov  NCT01804062  Addison  et  al.  (2012)  Developing  an  algorithm  for  pulse  oximetry  derived  respiratory  rate  (RRoxi):  a  healthy  volunteer  study.    J  Clin  Monit  Comput;  26(1):  45-­‐51Addison  PS  et  al,  Pulse  oximetry-­‐derived  respiratory  rate  in  general  care  floor  pa<ents.  J  Clin  Monit  Comput.  May  6,  2014.  Mestek  ML  et  al.  Accuracy  of  Con<nuous  Non-­‐invasive  Respiratory  Rate  Derived  from  Pulse  Oximetry  in  Obese  Subjects.  Abstract  A561,  AASA  2012  Annual  Mee<ng;      Mestek  ML  et  al.  Accuracy  of  Con<nuous  Noninvasive  Respiratory  Rate  Derived  From  Pulse  Oximetry  in  Conges<ve  Heart  Failure  Pa<ents.  Abstract  113A  Chest.  2012;142:113A.      Mestek  ML  et  al.    Accuracy  of  Con<nuous  Noninvasive  Respiratory  Rate  Derived  From  Pulse  Oximetry  in  Chronic  Obstruc<ve  Pulmonary  Disease  Pa<ents.  Abstract  142:671A.  Chest.  2012  

Commercially Available Pleth-based Respiration Rate Monitoring (Nellcor™ Respiration Rate Technology)

Commercially Available Pleth-based Respiration Rate Monitoring (Nellcor™ Respiration Rate Technology)

•  Con=nuous,  noninvasive  monitoring  of  respira=on  rate  on  adult  pa=ents  

•  Yields  SpO2,  Pulse  Rate,  Respira=on  Rate  from  a  single  pulse  ox  sensor    

•  Nellcor  Respira=on  Rate  Version  1  (FDA  cleared):  –     Respira<on  Rate  sohware  and  Adult  Respiratory  Sensor  –     Bedside  Respiratory  Pa<ent  Monitoring  System  with  Respira<on  Rate  –     SpO2  PCBA  with  Respira<on  Rate  for    OEM  Integra<on  

•  Respira=on  Rate  Version  2  (FDA  510(k)  Pending):  – Algorithm  changes  addressing:  •  Time  to  pos<ng  first  Respira<on  Rate  measurement  • Accuracy  at  low  and  high  RR  •  Response  <me  to  changes  in  RR  •  Reliability  during  disturbance  condi<ons  (e.g.,  mo<on,  talking)    

– User  interface:  Adjustable  RR  alarm  limits  (range  4-­‐40  breaths/minute)  – CE  Mark:  June  2014  

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700 720 740 760 780 800 820 8400

100

200

300

400

EtCO

2

700 720 740 760 780 800 820 8405

10

15

20

25

30

time (seconds)

RR

(/m

in)

TTI CO2 RR V1 V2

700 720 740 760 780 800 820 8400

100

200

300

400

EtCO

2

700 720 740 760 780 800 820 8405

10

15

20

25

30

time (seconds)

RR

(/m

in)

TTI CO2 RR V1 V2

25 breaths / min 11 breaths / min

Response Time to Changes in Respiration Rate •  Pleth-­‐based  RespRate  is  not  a  breath  by  breath  measure  

•  An  averaging  window  (≈  45  sec)  supports  overall  accuracy  •  Response  <me  to  step  change  is  similar  to  other  devices  (~1  minute)  

~ 1 min

*Covidien Internal Data

Variable   Baseline   Opioid    Infusion  

Detect  OIRD    (RR<8;  SpO2↓3%)  

Pleth-­‐RespRate  (BrPM)   13.1  ±  3.1   6.8  ±  0.8*   12/12  

SpO2  (%)   99.7  ±  0.7   98.9  ±  1.8   3/12  

Opioid-­‐Induced  Respiratory  Depression1  

 Kelley  SD,    Neitenbach  AM,    AR  Kinney  AR,    Mestek  ML.  Detec<on  of  Opioid-­‐Induced  Respiratory  Depression  with  Pulse  Oximetry-­‐Derived  Respiratory  Rate  Monitoring    Abstract  A095,  ASA  2012  Annual  Mee<ng    

Remifentanil Infusion Recovery

Opioid-­‐Induced  Respiratory  Depression    -­‐                  Central  Apnea  

1500 2000 2500 30000

20

40

60

EtCO2

1500 2000 2500 3000

5

10

15

20

25

time (sec)

RR

(B

rPM

)

reference V2

1500 2000 2500 30000

20

40

60

EtCO2

1500 2000 2500 3000

5

10

15

20

25

time (sec)

RR

(B

rPM

)

reference V2~60 second apnea

Audible RR Alarms

reference PlethRR EtCO2 RR

*Covidien Internal Data

Remifentanil Infusion

Audible RR Alarms

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Limita<ons  of  Pleth-­‐based  Respira<on  Rate  •  Respira=on  Rate  uses  the  same  pleth  signal  as  SpO2  and  relies  on  informa=on  derived  from  Pulse  Oximetry.    

•  A  Respira=on  Rate  value  will  only  be  calculated  if  the  pleth  signal  is  sufficient  for  pulse  oximetry.  

•  Challenges  to  SpO2  Performance  – Mo<on  – Low  Perfusion  – Electrosta<c  Interference  – Dyes  /  Nail  Polish  /  Pigmenta<on  – Strong  ambient  lights  

 

Pulse Oximetry

Respiration Rate

Pleth

•  Motion inherently more challenging for Respiration Rate than Pulse

Oximetry. – Pulse Oximetry can use short, intermittent periods of quiescence to attenuate

and read through neighboring interference (cardiac-gated averaging)

–  Longer time intervals associated with RR monitoring means fewer sections of unperturbed pleth signal for respiration rate analysis.

•  Talking (not shown here) is handled similarly to motion

Mo<on  (and  Talking)  

490 495 500 505 510 515 520 525 530

4

4.2

4.4

4.6

4.8

5

5.2

5.4

5.6x 105

Period of calm

Period of noise

45 second window

*Covidien Internal Data

IR P

PG

Am

plitu

de

145 150 155 160 165 1700

100

200

300

400

500

600

time (seconds)

CO2

145 150 155 160 165 170

4

4.05

4.1

4.15

4.2

4.25

4.3

4.35

4.4

4.45

x 105

time (seconds)

light

inte

nsity

Respiratory Sinus Arrhythmia One breath with very large pulse amplitude and pulse period modulations

•  Strong Sinus Arrhythmia provides a key respiratory-based modulation.

•  Strong and frequent pulse amplitude modulations during certain arrhythmias can overpower respiratory-based modulations and decrease pleth-based Respiration Rate accuracy. (e.g. > 6 PVCs in 60 sec)

Arrhythmia

240 245 250 255 260 265 270 275 280 285 2900

50

100

150

200

250

300

350

400

time (seconds)

CO2

240 245 250 255 260 265 270 275 280 285 290

4.8

5

5.2

5.4

5.6

5.8x 105

time (seconds)

light

inte

nsity

Premature Ventricular Contractions Large, fairly regular, pulse amplitude and frequency modulations that are NOT due to breathing

*Covidien Internal Data

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Obstructive Apnea

353 353.5 354 354.5 355

AB

Chest

Air FlowAir Flow

Pleth Frequency Modulations

Obstructive Apnea

Pleth Baseline modulations

Pleth Amplitude modulations

Chest Movement

Abdomen Movement

• Pleth-­‐based  Respira<on  Rate  tracks  indicators  of  central  respiratory  drive.        

•   During  an  obstruc<ve  apnea,  pleth-­‐based  respira<on  rate  will  likely  post  at  the  “central  respiratory  drive”  rate.  

Pleth

Central  drive  rate  remains  constant  through  obstruc<on  *Covidien Internal Data

Iden<fying  Repe<<ve  Reduc<ons  in  Airflow    Pa=erns  of  oxygen  desatura2on  correlate  with  intermident,  repe<<ve  reduc<ons  in  airflow  

*Covidien Internal Data

SPD:  Satura<on  Padern  Detec<on    

Pleth-­‐based  RR  Monitoring  Implementa<on  Integra<on  -­‐  The  Path  to  Clinical  Benefit?  

 

Bedside  Monitor  →  Distributed  Central  Monitoring  System    (Nursing  Sta<on;  Tele-­‐War  Room,  Respiratory  Therapy)  

57  yo  Male,  BMI  31    Post-­‐op  Abdominal  Surgery  

PCA  Pain  Rx  

*S Kelley – Personal Observation

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Assessing  Respira<on  Rate  /Ven<la<on  Monitors  

Pleth-­‐RR   ü ü ∅ ü ü Pending

Acous<c-­‐RR  

Exhaled  CO2  

Minute  Ven<la<on  

ECG-­‐TTI  

Manual  Observa<on  

Trends  Re

spira<on  

Single  Sensor  SpO 2  +  R

R  

Clinical  Benefit  Evide

nce  

Comfortable

 

Accurate  

Breath  by  breath  

Improving  Postopera<ve  Monitoring  

What  remains  to  be  established,  however,  is  the  level  of  performance  (accuracy,  response  <me,  persistence  of  discrepancy)  required  for  these  devices  to  have  clinical  benefits  in  different  areas  of  care.    However,  given  the  current  lack  of  respira<on  rate  monitoring  on  the  general  care  floor,  it  is  likely  that  the  available  devices  are  sufficiently  accurate  for  implementa<on  into  con<nuous  monitoring  care  strategies.  The  cri<cal  evidence  needed  is  to  assess  whether  the  addi<on  of  con<nuous  respira<on  rate  monitoring  can  further  enhance  pa<ent  safety  and  outcomes  when  u<lized.    

Anesthesia  &  Analgesia  2014  (in  press)  

Pleth-based Respiration Rate: Summary

Respiration Rate – Important and overlooked! ü Predictor: Patient deterioration & demise ü Respiratory rate – even intermittent – often not charted

A pleth-based solution measures Respiration Rate ü Commercially available ü Clinically acceptable accuracy: ± 1 BrPM ü Simple integration into pulse oximetry work-flow ü Combined with oximetry: enhanced patient information ü Recognized limitations: opportunities for improvement

Continuous Respiration Rate Monitoring ü Poised to mitigate complications and thereby improve both

clinical and financial outcomes. ü Needed: evidence generation of application & value