Clinical Reasoning & Differential Diagnosis Flashcards
DIsease
A disturbance of structure or function
Asymptomatic Disease
HTN, disease is present but not symptomatic
Subjective data
changes in the body perceived by the patient, Lab tests that were done at a previous visit
Classification of Disease:Metabolic
Disturbances of cellular energy processes
Classification of Disease: Neoplastic
Characterized by abnormal cell growth
Disease Risk Factor Categories:Disease-associated
Past illnesses that increase risk
Disease Risk Factor Categories: Treatment-associated
Surgical, transfusions, medications, allergies & adverse reactions, immunizations
Natural History of Disease (A-F)
A)Biologic onset of the condition B) Pathologic evidence of disease detectable by screening C)Signs and Symptoms of disease D)Health care sought E) Diagnosis of Disease F) Treatment of Disease
Preclinical- natural history of disease
A) Biologic onset of the condition
B) Pathologic evidence of disease detectable by screening
They don’t know they have it-Screenings
Clinical- natural history of disease
C)Signs and symptoms of disease
D) Health care sought
E) Diagnosis of Disease
Outcome-natural history of disease
F) Treatment of disease
Components of a patient problem
- Location
- Character or quality
- Severity
- Timing: onset, frequency, duration
- Sequence of symptoms
- Aggravating/ alleviating factors
- Associated factors and treatments
Deductive Reasoning with example
from general to specific
example: “Im tired–> hypothyroid”
Inductive Reasoning
from specific to general- uses probability theory
example: “Its probably this….lets order this test”
Critical Decision-making steps
Synthesis of relevant info Prediction of outcomes Examination of assumptions Generation of options Identification of patterns Choice of actions
Differential Diagnosis
Consideration of possible causes that account for clinical manifestations
What are differential diagnosis based on?
Clinical hx, social hx, family hx, physical exam
Constructing a differential diagnosis 1-5
- )Data acquisition
- )Accurate problem representation
- )Develop differential diagnosis
- ) Prioritize the differential diagnosis
- ) Test your hypotheses
Differential Diagnosis steps 1) Data acquisition 2) Accurate problem representation
1) Identify most important cues (cause, timeline, label for cluster of symptoms)
2) Understand & preform advanced examination techniques (Risks)
Differential Diagnosis step 3) Develop a complete framed differential diagnosis
Develop a list of possible causes (lists from textbooks, anatomic framework, organ/system framework)
Differential Diagnosis step 4) Prioritize the deferential diagnosis
Prioritize the list: possible probabilistic prognostic pragmatic
Possibilistic approach
all known causes treated as equally likely
Probabilistic approach
consider those that are more likely first
Prognostic approach
consider most serious first
Pragmatic approach
consider diagnoses most responsive to treatment first
example: “lets try steroid cream then if that doesnt work we will try this”
Steps in Diagnostic Reasoning
1) Identify the presenting problem
2) Assess patient
3) Formulate competing diagnoses
4) Order diagnostics
5) Select a diagnosis
6) Develop a treatment plan
7) Implement & evaluate the treatment plan:provide follow up care
Electromyogram (EMG)
- Measures electrical activity of skeletal muscle during contraction and at rest
- Can identify inflammatory and degenerative diseases of skeletal muscles and abnormal nerve conduction
CT scan
xray, visualizes soft tissue & organs with more detail
MRI
produces images similar to CT but with high energy magnetic fields, no radiation, not useful for bones
Positron Emisson Tomographic (PET) scan
looks at glucose uptake in body
Sensitivity definition and calculation
Ability of the test to detect patients WITH disease who test positive for the disease
true positives / total number of positive results
Specificity definition and calculation
Ability of the test to detect patients WITHOUT disease
true negatives/ total number of negative results
Positive predictive value and calculation
probability that the person has the disease if the test result is positive
True positive test result /total positive test results
Negative predictive value
Probability that the person does not have the disease if the test result is negative
Bayes Theorem
Predictive values relate to characteristics of a test & the frequency of the disease in a population
positive likelihood ratio definition and calculation
True positive% / False Positive %
=sensitivity /(1-specificity)
It tells you how likely it is that a result is a true positive rather than a false positive
negative likelihood ratio definition and calculation
False Negative%/ True negative %
=(1-sensitivity) / specificity
It tells you how likely it is that a result is a false negative rather than a true negative
LR >1
Test result is more likely to occur among patients with the disease than among those without the disease
LR <1
Test result is less likely to occur among patients with the disease than among those without the disease
LR >10
“rule in” disease
LR<0.1
“rule out” disease
Screening programs are most productive & efficient if directed at a low or high risk population?
high
Key steps in test selection and interpretation
1) Careful H&P
2) development of differential Dx’s
3) Consideration of estimated probability of disease
4) Selection od best test for situation
5) Interpretation of results
6) Continue cycle or “watchful waiting”
