Background: Influenza A (H1N1) hit the headlines in recent times and created mass hysteria and general panic. The high cost and non-availability of diagnostic laboratory tests for swine flu, especially in the developing countries underlines the need of having a cheaper, easily available, yet reasonably accurate screening test.
Aims: This study was carried out to develop a clinical feature-based scoring system (CFSS) for influenza A (H1N1) and to evaluate its suitability as a screening tool when large numbers of influenza-like illness cases are suspect.
Settings and design: Clinical-record based study, carried out retrospectively in post-pandemic period on subject's case-sheets who had been quarantined at IG International Airport's quarantine center at Delhi.
Materials and methods: Clinical scoring of each suspected case was done by studying their case record sheet and compared with the results of RT-PCR. RT-PCR was used to confirm the diagnosis (Gold Standard).
Statistical analysis: We calculated sensitivity, specificity, positive and negative predictive values of the clinical feature-based scoring system (the proposed new screening tool) at different cut-off values. The most discriminant cut-off value was determined by plotting the ROC curve.
Results: Of the 638 suspected cases, 127 (20%) were confirmed to have H1N1 by RT-PCR examination. On the basis of ROC, the most discriminant clinical feature score for diagnosing Influenza A was found to be 7, which yielded sensitivity, specificity, positive, and negative predictive values of 86%, 88%, 64%, and 96%, respectively.
Conclusion: The clinical features scoring system (CFSS) can be used as a valid and cost-effective tool for screening swine flu (influenza A (H1N1)) cases from large number of influenza-like illness suspects.