Development and validation of a clinical decision rule for the diagnosis of influenza.
BACKGROUND
A clinical decision rule to improve the accuracy of a diagnosis of influenza could help clinicians avoid unnecessary use of diagnostic tests and treatments. Our objective was to develop and validate a simple clinical decision rule for diagnosis of influenza.


METHODS
We combined data from 2 studies of influenza diagnosis in adult outpatients with suspected influenza: one set in California and one in Switzerland. Patients in both studies underwent a structured history and physical examination and had a reference standard test for influenza (polymerase chain reaction or culture). We randomly divided the dataset into derivation and validation groups and then evaluated simple heuristics and decision rules from previous studies and 3 rules based on our own multivariate analysis. Cutpoints for stratification of risk groups in each model were determined using the derivation group before evaluating them in the validation group. For each decision rule, the positive predictive value and likelihood ratio for influenza in low-, moderate-, and high-risk groups, and the percentage of patients allocated to each risk group, were reported.


RESULTS
The simple heuristics (fever and cough; fever, cough, and acute onset) were helpful when positive but not when negative. The most useful and accurate clinical rule assigned 2 points for fever plus cough, 2 points for myalgias, and 1 point each for duration <48 hours and chills or sweats. The risk of influenza was 8% for 0 to 2 points, 30% for 3 points, and 59% for 4 to 6 points; the rule performed similarly in derivation and validation groups. Approximately two-thirds of patients fell into the low- or high-risk group and would not require further diagnostic testing.


CONCLUSIONS
A simple, valid clinical rule can be used to guide point-of-care testing and empiric therapy for patients with suspected influenza.
Department of Epidemiology and Biostatistics and the Institute for Evidence-Based Health Professions Education, University of Georgia, Athens, GA 30602, USA. ebell@uga.edu
Mark H
MH
Ebell
Anna M
AM
Afonso
Ralph
R
Gonzales
John
J
Stein
Blaise
B
Genton
Nicolas
N
Senn
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D020000:Decision Support Systems, Clinical / Q000592:standards*; D019317:Evidence-Based Medicine; D005260:Female; D006801:Humans; D007251:Influenza, Human / Q000175:diagnosis* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D011320:Primary Health Care; D011446:Prospective Studies; D013557:Switzerland; D014481:United States; D055815:Young Adult