Self-diagnosis of seasonal influenza in a rural primary care setting in Japan: A cross sectional observational study.

OBJECTIVE

To elucidate the accuracy and optimal cut-off point of self-diagnosis and clinical symptoms of seasonal influenza compared with rapid influenza diagnostic tests as the reference standard, we conducted a cross sectional observational study at a rural clinic in Japan.

METHODS

Data during three influenza seasons (December 2013 to April 2016) were retrospectively collected from the medical records and pre-examination sheets of 111 patients aged >11 years (mean age 48.1 years, men 53.2%) who were suspected of influenza infection and underwent rapid influenza diagnostic testing. Patients' characteristics (age, sex, and past medical history of influenza infection), clinical signs (axillary temperature, pulse rate, cough, joint and muscle pain, and history of fever [acute or sudden, gradual, and absence of fever]), duration from the onset of symptoms, severity of feeling sick compared with a common cold (severe, similar, and mild), self-reported likelihood of influenza (%), and results of rapid influenza diagnostic tests.

RESULTS

At the optimal cut-off point (30%) for estimation of self-diagnosis of seasonal influenza, the positive likelihood ratio (LR+) was 1.46 (95% confidence interval 1.07 to 2.00) and negative likelihood ratio (LR-) was 0.57 (0.35 to 0.93). At a 10% cut-off point, LR-was 0.33 (0.12 to 0.96). At an 80% cut-off point, LR+ was 2.75 (0.75 to 10.07). As for clinical signs, the combination of acute or sudden onset fever and cough had LR+ of 3.27 (1.68 to 6.35). Absence of cough showed LR-of 0.15 (0.04 to 0.61).

CONCLUSIONS

Self-diagnosis of influenza using the optimal cut-off point (30%) was not found useful for ruling in or ruling out an influenza diagnosis. However, it could be useful when patients self-report extremely high (80%) or low (10%) probability of having influenza. Clinically useful signs were the combination of history of fever and cough, and absence of cough.