Original Research

Diagnosing Influenza: The Value of Clinical Clues and Laboratory Tests

Author and Disclosure Information

 

References

Data Analysis

Only patients who had an influenza culture could be included in the analysis. Three separate influenza epidemics occurred during the 2 years of data collection. These outbreaks were first analyzed separately to evaluate consistency of results across epidemics and then as a combined data set for determination of overall test characteristics.

The following variables were considered: clinician, patient age, sex, duration of symptoms, delay in presentation, vaccine, cough, fever, myalgias, sore throat, headache, WBC count, differential WBC count, ZstatFlu result, and culture result. An additional variable, “flu symptoms,” was defined as the combination of fever, cough, and myalgia. Delay in presentation was further categorized as 2 days or less or more than 2 days, since treatment is most effective when begun within 2 days of the onset of illness. A left-shifted WBC count was defined arbitrarily as a polymorphonuclear leukocyte proportion greater than 60%, and a right-shifted WBC count was defined arbitrarily as a lymphocyte proportion greater than 40%.

Within each epidemic group, patients with positive cultures were compared with those who had negative cultures. Since the 2 influenza epidemics (A and B) during the first year occurred simultaneously, patients with negative cultures during that time were used for comparisons in both groups for these initial analyses. Comparisons were made for age and duration of symptoms using the Student’s t test for independent samples. All other comparisons were made using the chi-square statistic.

We combined all data. For these combined analyses, the influenza-negative patients from year 1 were counted only once. Receiver operating characteristic (ROC) curves were constructed for the ZstatFlu test, WBC count, and WBC count combined with the ZstatFlu test. Rockit 0.9B software (University of Chicago; Chicago, Ill) was used to determine the area under the curve (AUC) and confidence intervals for the WBC count and the WBC count combined with the ZstatFlu test by maximum likelihood estimation of the ROC parameters.9 Individual cut-points for WBC counts were compared as binary tests by calculating the AUC for each.10 To determine the AUC for the ZstatFlu test we used the nonparametric Wilcoxin statistic.11 The logistic regression modeling function of Statistix7 software was used to analyze the individual and combined predictive properties of WBC count and ZstatFlu. Positive and negative likelihood ratios were calculated using standard formulas12; they correspond to the degree that a positive test result rules in disease and a negative test result rules out disease, respectively. These were used to estimate the rates of over- and undertreatment of influenza cases under 2 different baseline assumptions (pretest probabilities of influenza of 25% and 50%). Confidence intervals for sensitivity and specificity were calculated using the normal approximation to the binomial method.13

Results

We enrolled 382 patients during the first year (268 had influenza cultures performed) and 225 patients during the second year (90 were cultured). The total analyzable sample of cultured patients was 358 patients. In most cases, those who did not have cultures performed were seen on days when culture medium or laboratory pick-up were not available. Patients who had a culture performed were more likely to have a cough (P=.01) but otherwise did not differ from those who did not have a culture.In year 1, the influenza strains were A/Sydney (H3N2) and B/Bejing. In year 2, the strain was again A/Sydney (H3N2). The youngest patient with a positive flu culture was aged 10 months and the oldest was 73 years of age. The breakdown by age, sex, duration of symptoms, vaccine status, symptoms, WBC/differential, and ZstatFlu results by epidemic is shown in Table 1.

The presentation of influenza during the 3 epidemics differed. For example, the Beijing-like flu B in year 1 was more likely to infect younger people (mean age = 22.2 years) and was unlikely to cause a left WBC shift (25%), while the influenza A strain seen in the second year was more likely to infect older people (mean age = 28.3 years) and to be associated with a left WBC shift (72%). Culture-positive patients were somewhat more likely to report fever during 2 of the 3 outbreaks, but no single symptom or the symptom complex—fever, cough, and myalgias—reliably distinguished flu cases from nonflu cases across all epidemics.

Fifteen percent, 7%, and 17% of patients with positive influenza cultures in the 3 epidemics had received the vaccine. Both influenza strains were included in the vaccines given during those 2 years. However, immunization status was not consistently helpful for distinguishing influenza cases from those with other flu-like illnesses. Duration of symptoms was only associated with culture result in the year 2 flu A epidemic, in which influenza patients, on average, presented a half day earlier.

Pages

Next Article: