lecture 8 and 9 slides Diagnosis

8/3/2019 lecture 8 and 9 slides Diagnosis

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Diagnosis

Research Methods

Dent 313


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Diagnosis

This lecture deals with the basic principlesto follow when interpreting diagnostic tests

A diagnostic test is conventionally

performed in a lab It can be performed chairside (pulp vitality

testing) It can also be obtained from history taking,

physical examination and imaging procedures E.g: Severe spontaneous pain + provoked by cold +

badly decayed tooth: All serve as a diagnostic test to irreversible pulpitis


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Simplifying data

Clinicians generally reduce the data to a simplerform in order to make it useful in practice E.g., ordinal scales (tooth mobility)

E.g., dichotomous scale (tooth present/absent,normal/abnormal)

They often change interval scale to ordinal ornominal one E.g., blood pressurepresent/absent 90

Heart murmur to ordinal scale from I-IV


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Gold standard

Is the sound assessment of the truth It is the certainty that the disease is truly

present or absent

Establishing the diagnosis is imperfect


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Gold standard types of tests

Simple vs. elaborate

Simple tests are

Easier to perform

Inexpensive

But,,, less accurate

Elaborate tests are

More expensive More accurate

But,,, more risky


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Examples of simple and elaborate tests

Pulp vitality testing (simple)

Throat culture for strep throat (simple)

Histopathology for lesions (elaborate) Radiological contrast material

(elaborate)

Autopsies


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Gold standard

However, advanced tests are not the tests of options

most of the time

More costly, less feasible and more risky

Simpler tests can give adequate results without a risk (at least

initially) Compromising accuracy is justified by minimizing the risk

Examples

It is easier to diagnose pneumonia with chest x-ray and sputum

smear rather than lung biopsy

ECG and Serum Enzyme rather than heart biopsy,

catheterization or imaging as in case of MI


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Gold standard

It is easier to establish diagnosis withsimpler tests with understanding that thereis a risk of diagnosis

Therefore we are going to describe thevalue of diagnostic tests


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Accuracy of test results

Establishing a diagnosis is a probability

rather than a certainty

We commonly use possible: or rule out

Clinicians should be familiar with

mathematical relationships between the

properties of diagnostic tests and the

information they have about them


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Accuracy of test results

DISEASE

Present Absent

TEST Positive True positive False positive

Negative False negative True negative


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Sensitivity and specificity

Sensitivity

The proportion of people who tested positive

for the disease from those who have thedisease

High sensitive test will rarely miss people with

the disease


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Specificity:

The proportion of people who tested negative

for the disease from those without the disease

High specific test will rarely miss peoplewithout the disease


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Relationship between

sensitivity & specificity ofdiagnostic tests

Disease

Present Absent

Test Positive aTrue positive

bFalse positive

Negative c

False negative

d

True negative


Sensitivity (Se) = a/a+c Specificity (Sp)= d/b+d

Prevalence (P) = a+c/a+b+c+d


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Example: 37 of 149 patients with sore throats were

diagnosed as having pharyngitis and receiveAntibiotics

Only 27 of those had positive culture forstreptococcus

The remaining 112 with sore throats were notdiagnosed as having pharyngitis and were not

given Antibiotics Of the those 112, 77 had negative cultures for

streptococcus


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Streptococcus

Cultures (Disease)

Present Absent

Doctors clinicalexaminations

(Test)

Positive 27 35

Negative 10 77


37 112

62

87


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Streptococcus

Cultures (Disease)

Present Absent


(Test)

Positive 27 35

Negative 10 77


37 112

62

87

a True +ve = 27

b False +ve = 35

d True ve = 77c False ve = 10


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Streptococcus

Cultures (Disease)

Present Absent


(Test)

Positive 27 35

Negative 10 77


Sensitivity= a/a+c = 27/27+10 = 27/37 = 73%

Specificity= d/b+d = 77/35+77 = 77/112=69%Prevalence= a+c/a+b+c+d = 37/149 = 25%

37 112

62

87

A True +ve = 27B False +ve = 35

D True ve = 77

C False ve = 10


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Use of sensitive tests

In case of important penalty of missing a

condition (dangerous but treatable condition)

Tuberculosis, syphilis, Hodgkin's disease

During early stage of diagnostic workup with

many possibilities to be considered in order to

reduce the number of those possibilities

Fever, anemia, nausea


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Use of sensitive tests

To rule out diseases with a negative result of ahighly sensitive test Highly sensitive HIV ab test early in evaluation of lung

infiltrates & wt loss to rule out AIDS-related infection

When the probability of disease is very low andthe purpose of test is to discover the disease

*In summary: useful when test result is negative

and we dont want false negative results


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Use of specific test

Useful to confirm a diagnosis

In cases when false positive results willharm the patient emotionally, physically

and financially E.g., cancer

*In summary: useful when test result ispositive and we dont want false positiveresults


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Predictive value

Sensitivity and specificity are obtained in persons known tohave or not have the disease

Predictive value of the test Is the probability of disease, given the results of a test

Positive predictive value

Is the probability of disease in a patient with a

positive (abnormal) test result

Negative predictive value

Is the probability of not having the disease

when the test result is negative (normal).


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Predictive value

If my patients test is positive, what are thechances that my patient does have thedisease?

Answer: positive predictive value If my patients test is negative, what are

the chances that my patient does not havethe disease?Answer: negative predictive value


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Disease

Present Absent

Doctors ClinicalExaminations

(Test)

Positive aTrue positive bFalse positive

Negative cFalse negative

dTrue negative

+ Predictive Value = a / a + b

- Predictive Value = d / c + d

Accuracy = a+d / a+b+c+d


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Accuracy

Accuracy summarize the overall value of a

test

Accuracyis the proportion of all test

results, both positive and negative, that

are correct

Accuracy = a+d / a+b+c+d


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StreptococcusCultures (Disease)

Present Absent

Doctors clinical

examinations(Test)

Positive 27 35

Negative 10 77

37112

62

87

+ Predictive Value = a / a + b = 27/62 = 44%-Predictive Value = d / c + d = 77/87 = 88%

Accuracy = a+d/a+b+c+d = 27+77/149 =69.8%


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The more sensitive a test is, the better

will be its negative predictive value

The more specific the test is, the better

will be its positive predictive value

Sensitivity & Specificity & PV


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Streptococcus Cultures(Disease)

Present Absent


(Test)

Positive 37 35

Negative 0 77

37 112

72

77

149

Sensitivity = 37/37 = 100% Specificity =77/112 = 69%

+ P V = 37/72 = 51% - P V = 77/77 = 100%


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Present Absent

Doctors clinical

examinations(Test)

Positive 27 0

negative 10 112

37 112

27

122

149

Sensitivity = 27/37 = 73% Specificity =112/112 = 100%

+ P V = 27/27 = 100% - P V = 112/122 = 92%


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Prev = a+c/a+b+c+d

Because predictive value is also

influenced by prevalence, it is not

independent of the setting in which the

test is used

Prevalence


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Prevalence

As the prevalence of disease in a

population approaches zero, the positive

predictive value of a test also approaches

zero

As prevalence approaches 100%,

negative predictive value approaches zero


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Present Absent


(Test)

Positive 27 35

negative 10 77

37 112

62

77

149

Prevalence = 37/149 = 25%

+Predictive Value = A / A + B = 27/62 = 44%

- Predictive Value = D / C + D = 77/87 = 88%


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Present Absent


(Test)

Positive 3 45

negative 1 100

4 145

48

101

149

Prevalence = 4/149 = 3%




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Present Absent

Doctors clinical

examinations(Test)

Positive 106 1

negative 40 2

146 3

107

42

149

Prevalence = 146/149 = 98%




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Estimating Prevalence

Several sources of information to estimate theprevalence

Clinical observations Inaccurate mach wt for remarkable pts

Medical literature More accurate

Local databases

Clinical judgment

In general, prevalence is more important thansensitivity/specificity in determining predictivevalue


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Increasing the prevalence of disease

It is wise to apply diagnostic tests to those with increasedprobability of having the disease Applying tests when prevalence of disease is high

It is not appropriate to use vitality pulp testing in symptomatic

and asymptomatic teeth How to increase prevalence of disease

Referral process Referring patients to specialized clinics

Selected demographic groups With higher risk for disease

Specifics of the clinical situation When symptoms, signs, disease risk factors are present

Documents

lecture 8 and 9 slides Diagnosis