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Flashcards in Medical Decision Making Deck (17):
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Diagnosis

A process and its conclusions

Physicians think about diagnosis in complex ways

Aspect of medicine least well understood by the general public
–“You told me I had exercise-induced asthma and treated me for it. Now you’re saying it’s something different. How can that be?”

1

Deductive Reasoning

–Hypothesis testing
–Comparing current case against a pattern
–Does the patient have pulmonary embolus?

2

Inductive Reasoning

–Differential diagnosis
–Find a pattern
–What does the patient have?

3

Diagnostic Process

•Deduction

•Induction

•Pattern Recognition
–Instance based
–Prototype

•Combination

Circular process
•History and physical
•Differential diagnosis
•Diagnostic testing

4

Evaluation of a New Diagnostic Test

•In what kind of patients?
–Among the type of patients who would actually receive the test in clinical practice

•Compared to what?
–An appropriate, reproducible gold standard

•Who should have the gold standard test?
–All the patients being studied regardless of the result of the test being evaluated

5

2x2 Contingency Table

.

6

Prevalence = 10%
Sensitivity = 90%
Specificity = 95%
Total # people = 500

PPV = ?
NPV = ?


45 23 68
5 427 432
50 450 500

7

Prevalence = 20%
Sens = 90%
Spec = 95%
Total people = 500

D+. D-
T+. 90. 20. 110
T- 10. 380. 390
100. 400 500

PPV = 90/110 = 82%
NPV = 380/390 = 97%

8

Influence of Prevalence on Diagnostic Tests

No effect on sensitivity or specificity

Affects predictive values
- Higher prevalence: ^ PPV, v NPV
- Lower prevalence: v PPV, ^ NPV

9

Likelihood Ratios

Ratio of 2 ratios:
Ppl with a given result among ppl with disease / Ppl with the same result among ppl without disease

LR:
(test result / disease positive) / (test result / disease negative)

10


D+ D-
High. 40. 10
Low. 100. 150
Indeterminate. 70. 630
210. 790

LR high
LR low
LR intermediate

•LRHigh =
(40/210) / (10/790) = 15 x more likely to have disease that ppl with low or indeterminate

•LRLow =
(100/210) / (150/790) = 2.5

•LRInd =
(70/210) / (630/790) = 0.42

11

Prevalence=10%
Sens = 90%
Spec = 95%
PPV = 67%
NPV = 99%



D+ D-
T+ 45. 22. 67
T- 5. 428. 433
50. 450. 500

LRpos
LRneg

LRpos = (45/50)/(22/450)
= 18.4

LRneg = (5/50)/(428/450)
= 0.11

12

Comparison of Predictive Values and Likelihood Ratios

•Both pertain to what does it mean if my patient has a given test result

•Predictive values depend on prevalence of disease

•Likelihood ratios do not
–Derived from sensitivity and specificity which are prevalence invariant

13

Likelihood Ratios and Sensitivity/Specificity

D+ D-
T+ a. b. a+b
T- c. d. c+d
a+c. b+d

•LR(+) =
(a/(a+c))/(b/(b+d))
or
sensitivity/(1-specificity)

•LR(-) =
(c/(a+c))/(d/(b+d))
or
(1-sensitivity)/specificity

14

Bayes Theorem

•General form:
Prior odds hypothesis x Bayes Factor = Final (Posterior) odds of hypothesis

•Form for diagnostic tests:
Pre-test odds of disease x likelihood ratio = Post-test odds of disease

15

Odds and Probabilities

•Odds = probability/(1 – probability)
–p=0.5 odds = 0.5/(1-0.5) = 1:1
–p=0.33 odds = 0.33/(1-0.33) = 1:2 (or 0.5:1)

•Probability = odds in favor/total odds
= odds in favor/(odds in favor + odds against)
–Odds=3:1 p = 3/(3+1) = 0.75
–Odds=1:4 p = 1/(1+4) = 0.2

16

Application of Bayes Theorem
•58 year old man with long smoking history, blood-streaked sputum, lung nodule on CXR
–Pre lung biopsy probability of lung cancer = 33%
•Possible biopsy results: “high”, “low”, “indeterminate”
–LR (high) = 10
–LR (low) = 0.2
–LR (ind) = 1.0
•What’s the post-test probability for a given result?

•Convert pre-test probability to pre-test odds
–p=0.33 odds = 0.33/(1-0.33) = 0.5:1 (or 1:2)
•Multiply pre-test odds with likelihood ratio of result obtained to obtain post-test odds
–High: 0.5x10= 5
–Low: 0.5x0.2 = 0.1
–Indeterminate: 0.5x1=0.5
•Convert post-test odd to probability
–High: 5/(5+1)=0.83
–Low: 0.1/(0.1+1)=0.09
–Indeterminate: 0.5/(0.5+1)=0.33

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