Slideshow is from the University of Michigan Medical School's M1 Patients and Populations: Medical Decision-Making Sequence View additional course materials on Open.Michigan: openmi.ch/med-M1PatientsPopulations

1. Author(s): Rajesh Mangrulkar, MD, 2009
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3. Patients and Populations
Medical Decision-Making: Diagnostic
Reasoning I and II
Rajesh S. Mangrulkar, M.D.
Fall 2008

4. Ask
Acquire Apply
Thread 3: Diagnostic Reasoning
Appraise
R. Mangrulkar

5. Initial Diagnostic Reasoning
The Odyssey Reloaded
The Mechanic The Clinician
• Failure to entertain • Entertain all important
all possibilities possibilities
• Failure to pay • Elicit and pay attention
attention to all to description of all
symptoms symptoms
• Failure to inform • Inform and involve
customer patients
• Failure to perform • Perform effective
diagnostic tests diagnostic tests

6. The Odyssey: Conclusion
50 Prime, flickr
Initial Possibilities The Answer
#1: Trunk latch defect (recall
pending)
#2: Ajar sensing defect on #2: Ajar sensing defect on
side door side door
#3: Side door not closing
properly

7. Learning Objectives
• Acquire a basic understanding of diagnostic
question formulation
• Be able to define and calculate sensitivity,
specificity, and predictive values for
diagnostic tests
• Understand how risk factors drive prior
probabilities, and how this concept relates to
prevalence
• Be able to modify probabilities from test
results through 2x2 table calculations or
Bayesian reasoning

8. Recall case: Diagnostic Reasoning
• The case: A 56 year old man without heart
disease presents with sudden onset of
shortness of breath.
• Description of the problem: Yesterday, after
flying in from California the day before, the
patient awoke at 3AM with sudden
shortness of breath. His breathing is not
worsened while lying down.

9. Diagnostic Reasoning: Your Intake
• Q: What other symptoms were you
feeling at the time?
• A: He has had no chest pain, no leg
pain, no swelling. He just returned
yesterday from a long plane ride. He
has no history of this problem before.
He takes an aspirin every day. He
smokes a pack of cigarettes a day.

10. Diagnostic Reasoning: First Steps
The differential diagnosis
Your tasks:
• Assign likelihoods to each possibility
– E.g. P(X) = probability that X is the cause of the
patient s symptoms
• Place the possibilities in descending order of
likelihood

11. Your list

12. My list
My differential diagnosis
– Pulmonary embolism
– Congestive heart failure
– Emphysema exacerbation
– Asthma exacerbation

13. Probabilities
(1) PE P(PE) = 40%
(2) CHF P(CHF) = 30%
(3) Emphysema P(emphysema) = 20%
(4) Asthma P(asthma) = 10%
• What is the probability that the shortness of
breath is due to either PE or CHF? 70%*
*provided that both do not happen simultaneously.
If there is a 10% chance that both may happen, then this number is 60%

14. Prior Probabilities
• Based on many factors:
– Clinician experience
– Patient demographics
– Characteristics of the patient presentations (history and
physical exam)
– Previous testing
– Basic science knowledge
• Quite variable but can be standardized
– Clinical Prediction Rules
– http://www.mdcalc.com/wells-criteria-for-pulmonary-embolism-pe

15. More information
• Family history: father and brother have had DVTs in
the past
• Physical Exam:
– His blood oxygen saturation is 89% on room air (low)
– His respiratory rate is 16, but his pulse rate is 105
beats per minute
– Examination of his lungs reveals some crackles and
wheezes, but no pleural rub or evidence of
consolidation.
– Swollen right leg, with firm vein below the knee
• CXR: normal
• EKG: sinus tachycardia
http://www.mdcalc.com/wells-criteria-for-pulmonary-embolism-pe

16. Diagnostic Reasoning: Testing
• If a Test existed that could rule in PE
as the diagnosis with 100% certainty:
then P(PE | Test+) = 100%
• Two questions:
– What is this test called? Gold Standard
– Does P(CHF | Test+) = 0%? No

17. Diagnostic Testing
• Facilitates the modification of probabilities.
• Can include any/all of the following:
– Further history taking
– Physical Examination maneuver
– Simple testing (laboratory analysis,
radiographs)
– Complex technology (stress testing, $$$
angiography, CT/MRI, nuclear scans)

18. PICO: The Anatomy of a Diagnostic
Foreground Question
D
P • Patient: define the clinical condition or disease
clearly.
I
T • Intervention: define the diagnostic test clearly
• Comparison group: define the accepted gold
G
C standard diagnostic test to compare the results
against.
O • are the properties of the test itself (e.g.,interest
A Outcomes of interest: the outcomes of
accuracy and others we ll discuss).

19. Practice PICO
Case: A 56 year old man without heart disease
P presents with sudden onset of shortness of
breath. Considering PE.
Diagnostic Test to consider:
I Ventilation / Perfusion
Scanning
C Gold standard: Pulmonary Source Undetermined
angiography
O Need: Diagnostic accuracy
Source Undetermined

20. Studies of Diagnostic Tests
1. A well-defined group of people being
evaluated for a condition undergo:
- an experimental test, and
- the gold standard test.
2. Comparison is made between the
accuracy of the new test and that of the
gold standard.

21. Diagnostic Testing: Statistical
Significance
• Statistical significance: strength of the
association between…
– Diagnostic study results (for the diagnosis of a
particular disease)
– Gold standard results (for the diagnosis of the
same disease, in the same population)
• Strength = degree of accuracy

22. Diagnostic Testing: Clinical
Significance
• Clinical significance: how likely is the
diagnostic test going to affect patient care?
– Magnitude of the association between test
results and the accepted gold standard
– Other literature (including those of the gold
standard)
– Cost of the test, reproducibility of test
– Disease characteristics (will the test result
affect management of the disease?)

23. What are the results - Diagnosis
Diagnostic performance is an association
between test result and diagnosis of a
condition (as assessed by the gold
standard) Disease + Disease -
BONUS Test + A B
What type of
variable is TP FP
FN TN
disease
state? Test - C D

24. Which test characteristics?
• There are prevalence-dependent and
prevalence-independent measures in
diagnostic tests.
• Prevalence-independent: sensitivity and
specificity.
• Prevalence-dependent: positive and
negative predictive values.

25. Test Characteristics: SeNsitivity
Sensitivity:
• The probability that the test will be positive
when the disease is present.
• Of all the people WITH the disease, the
percentage that will test positive.
• A seNsitive test is one that will detect most
of the patients who have the disease (low
false-Negative rate).

26. Test Characteristics: SPecificity
Specificity:
• The probability that the test will be
negative when the disease is absent.
• Of all the people WITHOUT the disease,
the percentage that will test negative.
• A sPecific test is one that will rarely be
positive in patients who don t have the
disease (low false-Positive rate).

27. Test Characteristics: Predictive Values
• Positive predictive value: the probability
that a patient has a disease, given a
positive result on a test.
P (Disease + | Test +)
• Negative predictive value: the probability
that a patient does not have a disease,
given a negative result on a test.
P (Disease - | Test -)

28. Diagnostic Test Characteristics
• Sens = A/(A+C) Dx+ Dx-
• Spec = D/(B+D) T+ A B
• PPV = A/(A+B)
T- C D
• NPV = D/(C+D)
A+C B+D

29. To reflect upon...
Why are sensitivity and specificity
prevalence-INdependent
characteristics, while positive and
negative predictive values prevalence-
DEpendent?

30. Let s try it out
V/Q scan
Case: To determine the diagnostic
accuracy of V/Q scans for
detecting pulmonary embolism, a
study was conducted where 300
patients underwent both a V/Q
and pulmonary angiogram. 150 Source Undetermined
patients were found to have a PE Pulmonary Angiogram
by PA gram. Of those, 75
patients had a high probability
VQ scan. Of the 150 patients
without a PE, 125 had a non-high
probability VQ scan. Source Undetermined

31. Let s try it out
Case: To determine the
diagnostic accuracy of V/Q PE+ PE-
scans for detecting pulmonary
embolism, a study was
conducted where 300 patients VQ hi 75 25
underwent both a V/Q and
pulmonary angiogram. 150
patients were found to have a VQ
PE by PA gram. Of those, 75
patients had a high probability other 75 125
VQ scan. Of the 150 patients
without a PE, 125 did not
have a high probability VQ
scan (VQ other). 150 150

32. Let s try it out
PE+ PE- • Sens = 75/(75+75)
= 50%
VQ hi 75 25 • Spec = 125/(125+25)
= 83%
VQ • PPV = 75/(75+25)
75 125 = 75%
other
• NPV = 125/(125+75)
= 63%
150 150

33. Modification of Probability
Pretest Test result
Probability Test changes the
P (Disease) Result probability of
disease
P (Disease|Test Result)
R. Mangrulkar

34. Test Characteristics and Prevalence
• Sens = A/(A+C) Dx+ Dx-
• Spec = D/(B+D) T+ A B
• PPV = A/(A+B)
T- C D
• NPV = D/(C+D)
Disease
A+C B+D
Prevalence

35. Prevalence
PE+ PE-
• Sens = 50%
VQ hi 75 25 • Spec = 83%
• PPV = 75%
VQ • NPV = 63%
other 75 125
• Prevalence = 50%
???
150 150

36. Populations and Patients
Population view Patient view
• Prevalence reflects • Same concept
the number of implies how likely an
people with the individual patient
disease at a given has the disease
moment • P (Disease)

37. Modification of Probability
Pretest Test result
Probability Test changes the
P (Disease) Result probability of
disease
P (Disease|Test Result)
Disease
Prevalence
R. Mangrulkar

38. An Important Question and
Assumption
Question: Are certain test characteristics fixed?
Answer: Generally, yes.
Sensitivity and specificity are constants,
regardless of the prevalence of the
disease in the studied population
(prevalence-INdependent)*
*Exceptions and caveats to this assumption are real, but are beyond the
scope of this course

39. Modification of Probability
Pretest Test result
Probability Test changes the
P (Disease) Result probability of
disease
P (Disease|Test Result)
Disease sensitivity
Prevalence specificity
R. Mangrulkar

40. Importance of Pre-Test Probability
• Hi-prob V/Q: Sens = 50%, Spec = 83%
Post-TP
PV
D+ D-
Pre-TP/Prev PPV NPV T+ 75 25
50% 75% 63% T- 75 125
How do our predictive values relate to our
probability after the test result is obtained (our
post-test probabilities)?

41. Importance of Pre-Test Probability
• Hi-prob V/Q: Sens = 50%, Spec = 83%
Post-TP
PV
D+ D-
Pre-TP/Prev PPV NPV T+ 75 25
50% 75% 63% T- 75 125
• If our Pre-test Probability was 50%, and we
obtain a hi-prob V/Q scan on this patient,
what is our Post-test probability? 75%

42. Importance of Pre-Test Probability
• Hi-prob V/Q: Sens = 50%, Spec = 83%
Post-TP
PV
D+ D-
Pre-TP/Prev PPV NPV T+ 75 25
50% 75% 63% T- 75 125
• If our Pre-test Probability was 50%, and we
obtain a V/Q-other scan on this patient, what
is our Post-test probability? 37% (tricky: 1-63%)

43. What did we just do?
100
75% = P(PE|T+)
i
VQ h
50%
VQ oth
er
37% = P(PE|T-)
0
P (PE) P (PE | Test)
R. Mangrulkar

44. Modification of Probability
Pretest Test result
Probability Test changes the
P (Disease) Result probability of
disease
P (Disease|Test Result)
Disease sensitivity
Prevalence specificity Predictive Values
(Positive and Negative)
R. Mangrulkar

45. Fundamental Assumptions
Sensitivity and specificity are constants,
regardless of the prevalence of the
disease in the studied population
(prevalence-INdependent)*
Positive and Negative Predictive Values are
dependent on the prevalence of the
disease in the studied population
(prevalence-DEpendent)
*with exceptions

46. Now, what do we do?
Choices:
• Treat as if patient has PE
75% = P(PE|T+) • Decide to get another test
• Decide that patient does not have a PE
Choices:
37% = P(PE|T-) • Treat as if patient has PE
• Decide to get another test
• Decide that patient does not have a PE
What factors do you consider when making the next decision?

47. What if we change our pretest
probability?
• In essence, we are simultaneously
changing the prevalence:
– Original pre-TP = P(PE) = 50% HIGH RISK
– New pre-TP = P(PE) = 25% MED RISK
• Assuming that sensitivity and specificity
are fixed…then we must recalculate our
predictive values to determine our new
post-test probabilities.

48. Importance of Pre-Test Probability
• Hi-prob V/Q: Sens = 50%, Spec = 83%
D+ D-
Post-TP
T+ 75 25
Pre-TP/Prev PPV NPV
T- 75 125
hi risk 50% 75% 63%
D+ D-
med risk 25% 50% 83%
38/(38+38) 187/(187+37) T+ 38 38
Our Pre-test Probability was 25%, we obtain a V/Q-other scan
T- 37 187
on this patient, our Post-test probability is now…17%

49. Decision time
Choices:
• Treat as if patient has PE
• Decide to get another test
• Decide that patient does not have a PE
50% = P(PE|T+)
Choices:
• Treat as if patient has PE
• Decide to get another test
17% = P(PE|T-)
• Decide that patient does not have a PE

50. Let s change it again…
• Again, we are changing the prevalence:
– Young woman, no risk factors, some dyspnea,
no family history, normal exam (except hr of
105)
– Lets consult our clinical prediction rule:
– http://www.mdcalc.com/wells-criteria-for-pulmonary-embolism-pe
– New pre-TP = P(PE) = 5%: LOW RISK

51. Importance of Pre-Test Probability
• Hi-prob V/Q: Sens = 50%, Spec = 83%
D+ D-
Pred Val
T+ 75 25
Pre-TP/Prev PPV NPV
T- 75 125
hi risk 50% 75% 63%
D+ D-
lo risk 5% 15% 97%
8/(8+47) 238/(238+7) T+ 8 47
T- 7 238

52. What did we just do?
Observation
As prevalence (pre-test probability) decreases,
positive tests are more likely to be false-positives
75% = P(PE|T+)
i
VQ h
50%
VQ oth
er
37% = P(PE|T-)
VQ hi 15% = P(PE|T+)
5%
0 VQ other 3% = P(PE|T-)
P (PE) P (PE | Test)
R. Mangrulkar

53. Fundamentally...
Question: If you get a high probability V/Q scan
for the diagnosis of pulmonary embolism, is it
more likely to represent a false positive test if
the patient presented with…
(a) many clinical features of PE (shortness of
breath, chest pain, long plane ride), or
(b) no clinical features of PE (no shortness of
breath, no chest pain, no leg swelling, no long
plane ride)?

54. Another example
• Question: Why don t we screen the general
population for HIV with an ELISA in the USA?
• Sensitivity: 99%, Specificity: 95%
• A positive ELISA for HIV would most likely
represent true HIV infection in which of these
2 patients?
– 28 year old woman with history of iv drug abuse,
husband has HIV.
– 68 year old woman, monogamous her entire life,
no blood transfusions, no ivda.

55. Importance of Pre-Test Probability
• HIV ELISA: Sens = 99%, Spec = 95%
D+ D-
Post-TP
T+ 248 37
Pre-TP PPV
NPV T- 2 713
hi risk 25% 87% 99.7%
D+ D-
lo risk 1% 17% 99.9%
T+ 99 495
T- 1 9405

56. Pearls
• Studies of tests give you test characteristics,
not predictive values.
• The better the test, the greater the difference
between pre-test and post-test probability.
• If your pre-test probability is very low (<10%)
or very high (>90%), it is rare that a single
test can help you, unless it is a nearly perfect
test.

57. Diagnostic Reasoning
The Odyssey Returns
The Mechanic The Clinician
• Failure to entertain • Entertain all important
all possibilities possibilities
• Failure to pay • Elicit and pay attention
attention to all to description of all
symptoms symptoms
• Failure to inform • Inform and involve
customer patients
• Failure to perform • Perform effective
diagnostic tests diagnostic tests

58. Ask
Acquire Apply
Appraise
R. Mangrulkar

59. Additional Source Information
for more information see: http://open.umich.edu/wiki/CitationPolicy
Slide 4: Rajesh Mangrulkar
Slide 6: 50 Prime, flickr, http://www.flickr.com/photos/pernett/1544045987/, CC: BY http://creativecommons.org/licenses/by/2.0/deed.en
Slide 19: Sources Undetermined
Slide 30: Sources Undetermined
Slide 33: Rajesh Mangrulkar
Slide 38: Rajesh Mangrulkar
Slide 39: Rajesh Mangrulkar
Slide 43: Rajesh Mangrulkar
Slide 44: Rajesh Mangrulkar
Slide 52: Rajesh Mangrulkar
Slide 58: Rajesh Mangrulkar