Flashcards in ICR Week 3 Deck (13):

1

## List different strategies that physicians use to solve clinical problems

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•Hypothetico-deductive

•Algorithm or schema

•Concept Maps: Schema “plus”

• Key finding (key feature or key clue)

• Heuristics (cognitive shortcuts)

• Probabilistic (Bayesian)

• Pattern recognition

2

## Describe the key finding clinical strategy:

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• Key finding (key feature or key clue)

– Limited differential (splinter hemorrhage)

3

## Describe heuristics clinical strategy:

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• Heuristics (cognitive shortcuts)

– Consider CNS infection in all patients who present with fever and mental status changes

– Perform arthrocentesis in all patients presenting with acute monoarticular arthritis

4

## Describe probabilistic clinical strategy:

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• Probabilistic (Bayesian)

– Applying statistical principals to patient encounters

– Experts usually do this without “number crunching”

• Common vs. rare

5

## Describe pattern recognition clinical strategy:

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• Pattern recognition

– Diagnosis “at a glance”

6

## Describe how to construct a problem list:

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Problem lists can often be “split” or “lumped”

– “Splitters”--list each problem separately (not grouped)

• Generate unique differential for every problem on list

• Multisystem disease, several new diagnoses

– “Lumpers”--group problems into unifying diagnosis

• Common presentations of familiar diseases

7

## Define sensitivity

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Sensitivity: SnOUT if test is negative it can be ruled out if the test has a high sensitivity

(True postive rate) Proportion of all people with disease who test positive, or the probability that a test detects disease when disease is present.Value approaching 100% is desirable for ruling

out disease and indicates a low false-negative rate. High sensitivity test used for screening in diseases with low prevalence.

8

## Define specificity

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Specificity: Sp IN if the test is positive it can be ruled in if the test has a high specificity

(True negative rate) Proportion of all people without disease who test negative, or the probability that a test indicates non-disease when disease is absent. Value approaching 100% is desirable for ruling in disease and indicates a low falsepositive rate. High specificity test used for confirmation after a positive screening test.

9

## Calculate positive predictive values

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Positive predictive value (PPV)

Proportion of positive test results that are true positive. Probability that person actually has the disease given a positive test result.

= TP / (TP + FP)

PPV varies directly with prevalence or pretest probability: high pretest probability high PPV

10

## Calculate negative predictive values

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Negative predictive value (NPV):

Proportion of negative test results that are true negative.

Probability that person actually is disease free given a negative test result.

= TN / (FN + TN)

NPV varies inversely with prevalence or pretest probability: high pretest probability low NPV

11

## Describe the hypothetico-deductive clinical strategy:

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Hypothetico-deductive

– Arrive at the diagnosis by considering each potential Dx in

isolation without comparing/contrasting with other potential Dx

• Inefficient, redundant, but can be accurate

• Used by novice learners

12

## Describe the algorithm or schema clinical strategy:

###
Algorithm or schema

– Arrive at diagnosis through a series of prioritized decision points

or steps

– Work through a series of “yes”/“no” ?s with branch points

13