BATES GUIDE TO PHYSICAL EXAMINATION
AND HISTORY TAKING COMPREHENSIVE
STUDY GUIDE 2026 CLINICAL ASSESSMENT
AND DIAGNOSTIC PRINCIPLES
◉ Sensitivity.
Answer: The probability that a person with disease has a POSITIVE
test.
Also known as the "true positive" rate.
Useful for screening tests because if sensitivity is > 90%, you can
rule OUT diseases (test is rarely negative when the disease is
present)
Ex) The probability that a patient with splenomegaly is associated
with percussion dullness below the left costal margin.
◉ Specificity.
Answer: The probability that a non-diseased person has a NEGATIVE
test.
,Also known as the "true negative" rate.
Useful as confirmatory tests because if specificity is >90%, it is safe
to confirm diseases (test is rarely positive when the disease is
absent)
Ex) The probability that a patient WITHOUT splenomegaly will have
percussion dullness is the false positive rate for this physical
maneuver.
◉ A negative result from a test with high sensitivity....
Answer: ...usually means you can exclude the disease.
(high sensitivity = very low false-negative rate)
◉ SnNOUT Acronym.
Answer: a Sensitive test with a Negative result rules OUT disease
◉ SpPIN Acronym.
Answer: a Specific test with a Positive result rules IN disease
◉ Positive Predictive Value (PPV).
, Answer: The probability that a person with a positive test has
disease [a / (a + b)]
Ex) Prostate Cancer screening, where a man with a PSA value
greater than 4.0 ng/mL has only a 30% probability of having
prostate cancer when tested via biopsy.
The predictive value will vary substantially according to the
prevalence of disease.
◉ Negative Predictive Value (NPV).
Answer: The probability that a person with a negative test does not
have disease [d / (c + b)]
Ex) Among men with a PSA level of 4.0 ng/mL or below, 85% are
found to be cancer-free via biopsy.
◉ Prevalence of a disease.
Answer: The proportion of subjects that have the disease
◉ Likelihood Ratios.
Answer: The probability of obtaining a given test result in a diseased
patient DIVIDED BY the probability of obtaining a given test result in
a non-diseased patient.
AND HISTORY TAKING COMPREHENSIVE
STUDY GUIDE 2026 CLINICAL ASSESSMENT
AND DIAGNOSTIC PRINCIPLES
◉ Sensitivity.
Answer: The probability that a person with disease has a POSITIVE
test.
Also known as the "true positive" rate.
Useful for screening tests because if sensitivity is > 90%, you can
rule OUT diseases (test is rarely negative when the disease is
present)
Ex) The probability that a patient with splenomegaly is associated
with percussion dullness below the left costal margin.
◉ Specificity.
Answer: The probability that a non-diseased person has a NEGATIVE
test.
,Also known as the "true negative" rate.
Useful as confirmatory tests because if specificity is >90%, it is safe
to confirm diseases (test is rarely positive when the disease is
absent)
Ex) The probability that a patient WITHOUT splenomegaly will have
percussion dullness is the false positive rate for this physical
maneuver.
◉ A negative result from a test with high sensitivity....
Answer: ...usually means you can exclude the disease.
(high sensitivity = very low false-negative rate)
◉ SnNOUT Acronym.
Answer: a Sensitive test with a Negative result rules OUT disease
◉ SpPIN Acronym.
Answer: a Specific test with a Positive result rules IN disease
◉ Positive Predictive Value (PPV).
, Answer: The probability that a person with a positive test has
disease [a / (a + b)]
Ex) Prostate Cancer screening, where a man with a PSA value
greater than 4.0 ng/mL has only a 30% probability of having
prostate cancer when tested via biopsy.
The predictive value will vary substantially according to the
prevalence of disease.
◉ Negative Predictive Value (NPV).
Answer: The probability that a person with a negative test does not
have disease [d / (c + b)]
Ex) Among men with a PSA level of 4.0 ng/mL or below, 85% are
found to be cancer-free via biopsy.
◉ Prevalence of a disease.
Answer: The proportion of subjects that have the disease
◉ Likelihood Ratios.
Answer: The probability of obtaining a given test result in a diseased
patient DIVIDED BY the probability of obtaining a given test result in
a non-diseased patient.
