Clinical Approach to Patients

Tanarat Choon-ngarm MD

Clinical decision makingClinical reasoningUse of cognitive short cuts1. Representativeness heuristics2. Availability heuristics3. Anchoring heuristics

Diagnostic hypothesis generation A diagnostic hyposthesis sets a context for

diagnostic test to follow and provides testable predictions

Expert clinicians do not follow a fixed pattern in patient examination

Negative findings are often as important as positive ones

Data collection History Physical examination Investigations which depend on the

hypothesis generated from clinical findings Interpretation of results of investigation in

context of the patient Final diagnosis or additional investigations

Fever Fever for one month Fever for one month with heart murmur Fever for one month with heart murmur

and roth spot Provisional diagnosis : infective

endocarditis Essential investigations : echocardiogram,

hemoculture

Dyspnea Cardiac disease Pulmonary disease Metabolic causes Psychiatric disease

Dyspnea Acute dyspnea for one day Acute dyspnea with bilateral wheezing Acute dyspnea with bilateral wheezing and

cardiomegaly and third heart sound Diagnosis : acute heart failure Investigations : ECG and chest X-ray and

echocardiogram

Edema Edema of both legs Edema of both legs and ascites Edema of both legs and ascites and

normal jugular venous pressure Edema of both legs and ascites and

normal jugular venous pressure with spider nevi and jaundice

Diagnosis: chronic liver disease ,probable liver cirrhosis

Approach to heart failure What is the etiology? eg. valvular disease Stage of heart failure? eg. stage A, B, C, or

D Functional class? eg. NYHA FC I-IV Any precipitating factors? Prognosis?

Alteration of consciousnessLocalizing signsNo localizing signs Diffuse brain damage from Encephalitis Metabolic disturbance: hyponatremia

hypernatremia, hypoglycemia, hyperglycemia, hypercalcemia, uremia, hepatic encephalopathy

Approach to neurologic patients Locate the anatomic location of the

disease Determine the etiology Example: acute onset of hemiparesis with

global aphasia indicates the location to be at the frontal and parietal lobe of the dominant hemisphere and the etiology is most likely from vascular disease such as infarction from thrombosis or embolism

Disease assessment Severity or staging Activity Complications or sequele Prognosis Example : CA colon, adenocarcinoma,

stage 4, complication- gut obstuction, 5 year survival 5%

Definite diagnosis Diagnostic criteria What investigation is the gold standard? Example: tissue pathology is the gold

standard for the diagnosis of malignancy A perfect diagnostic test should have a

sensitivity and specificity of 100%

Definition of sensitivity and specificity Sensitivity : The fraction of those with the

disease correctly identified as positive by the test.

Specificity: The fraction of those without the disease correctly identified as negative by the test.

Positive and negative predictive value Positive predictive value (+ PV) is the

fraction of people with positive tests who actually have the condition.

Negative predictive value (-PV) is The fraction of people with negative tests who actually don't have the condition.

The sensitivity and specificity are properties of the test. The positive and negative predictive values are properties of both the test and the

population you test. If you use a test in two populations with

different disease prevalence, the predictive values will be different. A screening test is most useful if directed to a high-risk population (high prevalence

and high predictive value).

Calculation of sensitivity and specificity

Patient with the disease

Patient without the

disease

Test is positive

ATrue Positive

BFalse Positive

Test is negative

CFalse

Negative

DTrue Negative

Using the 2X2 table you can calculate

Sensitivity = a / (a+c)Specificity = d / (b+d)

+ PV = a/(a+b)- PV = d/(c+d)

Knowing the prevalence of the disease in the population is necessary for

these calculations

Understanding Predictive Value Prevalence is defined as the number of patients

per 100,000 population who have the disease at a given time.

A high +PV indicates a strong chance that a person with a positive test has the disease whereas a low +PV is usually found in populations with low prevalence of the condition being examined. A high -PV means that a negative test in effect rules out the disease.

Effects of PrevalenceSensitivity=95% Specificity=95%

Population’sPrevalence

0.1%1.0%2.0%5.0%50%

Predictive Value of a Positive Test

1.9%16.1%27.9%50%95%

Effects of PrevalenceSensitivity=99% Specificity=99%

Population’sPrevalence

0.1%1.0%2.0%5.0%50%

Predictive Value of a Positive Test

9.0%50%

66.9%83.9%99%

Test interpretation When a sign, test or symptom has an

extremely high specificity (say, over 95%), a positive result tends to rule in the diagnosis.

When a sign, test or symptom has a high sensitivity, a negative result rules out the diagnosis.