The WBC count was strongly associated with culture result in all 3 epidemics. As the WBC count increased, the likelihood of a positive culture decreased. A right or left shift in the differential count was not consistently related to the probability of a positive culture. WBC count was positively correlated with duration of symptoms in children (Pearson correlation coefficient = 0.20; P=.04) and negatively associated with symptom duration in adults (Pearson correlation coefficient = -0.15; P=.66). There was also a negative association between left shift and duration of symptoms (P=.001) and a positive association between right shift and duration of symptoms (P=.01) for all patients, suggesting that influenza patients develop a left shift at onset of infection and later convert to a right shift.
ROC curves were constructed using various levels of WBC counts with and without the ZstatFlu test Figure 1. For WBC count alone, the AUC was 0.67 (95% confidence interval [CI], 0.61-0.74). By comparison, the AUC for the ZstatFlu test was 0.74 (95% CI, 0.68-0.80). The ROC curve describing the use of a combination of ZstatFlu test and the WBC count had an AUC of 0.82 (95% CI, 0.76-0.87); this was better than WBC alone but not significantly different from ZstatFlu alone.
WBC counts greater than 7000 (negative likelihood ratio = 0.41) were superior to a negative ZstatFlu test result at confirming the absence of the flu. WBC counts less than 3200 (positive likelihood ratio = 7.21) were superior to a positive ZstatFlu test result at confirming the presence of the flu. A WBC count greater than 6300 had greater sensitivity (67%) than the ZstatFlu test, however, for WBC counts between 6300 and 7000, the gain in sensitivity did not offset the loss in specificity. A WBC count less than 4600 had a greater specificity (84%) than the ZstatFlu test, but for WBC counts between 3200 and 4600 the gain in specificity did not offset the loss in sensitivity.
Table 2 shows the characteristics of WBC counts at several cut-points, of the ZstatFlu test, and of their combinations. Using the one test strategy of treating those with a WBC count of 8000 or less would ensure treatment of almost all influenza cases (92%). Using the ZstatFlu test as a one testing strategy would assure that most of the patients treated have the flu but would miss 44% patients with the flu. Adding a WBC count if the ZstatFlu test result is negative improves sensitivity but reduces specificity. The predictive values positive and negative in the Table 1 are based on a previous probability of 50% (peak of flu season). These values would obviously be lower at the beginning or ending of an epidemic.
Discussion
Unfortunately, signs, symptoms, and vaccine status may be of little consistent value in distinguishing patients with influenza from those with other respiratory illnesses during influenza season. During some epidemics, fever and cough may be of some help, but this will depend heavily on what other illnesses are prevalent at the same time. Others have observed that symptoms have low predictive value and that physicians have difficulty identifying flu cases during epidemics.5,6 Monto and colleagues7 reported that fever and cough occurred more frequently among influenza patients involved in clinical trials of an antiviral agent, but these results may not apply directly to primary care settings and represent pooled findings across several epidemics.
Vaccine status was also not helpful in this study for distinguishing influenza culture-positive patients. Influenza vaccination is effective in only 70% to 90% of patients. Therefore, there will always be vaccine-positive patients who develop the flu. Our data do not provide quantifiable information about overall vaccine efficacy, but the number of vaccine-positive patients was small, suggesting that the vaccine may have been effective in the community at large, though not in the culture-positive patients included in this study.
Both the WBC count and the ZstatFlu test can be helpful for identifying influenza cases. The testing strategy of choice depends to some degree on a number of factors including cost, duration and severity of symptoms, comorbidities, and potential adverse effects of treatment. The ZstatFlu test costs approximately $20. The cost of a WBC count is approximately $30, but it may have additional diagnostic value. Treating the patient with either zanamivir or oselfamivir costs $50 to $60, rimantidine $30, and amantadine $6.
The monetary value of an earlier return to work, reduced caregiver burden, or reduced transmission of infection will vary greatly. If the goal is to treat nearly every influenza case, a strategy of treating those with a WBC of 8000 or less appears to be the best strategy. If the goal is to be sure that only patients with the flu are treated, then treatment should be reserved for those who are ZstatFlu positive. Each patient and each physician would be expected to have different treatment thresholds that would affect the testing strategy. More than half the patients with positive influenza cultures were seen within 2 days of the onset of symptoms. These patients are the ones who would be most likely to benefit from the newer antiviral agents. For example, if the treatment threshold for a particular patient was 50%, no testing would have been necessary in any of the epidemics studied, since the pretest probabilities were all greater than 50%. An analysis that includes patient preferences would be helpful to determine the most cost-effective strategy.