Abstract
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.
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.
Original language | English |
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Pages (from-to) | 265-269 |
Number of pages | 5 |
Journal | Journal of postgraduate medicine |
Volume | 58 |
Issue number | 4 |
DOIs | |
Publication status | Published - 4 Jan 2012 |
Keywords
- scoring system
- screening tool
- swine flu
- H1N1