Influenza infection screening tools fail to accurately predict influenza status for patients during pandemic H1N1 influenza season.
Can Respir J. 2013 May-Jun;20(3):e55-9
Authors: Mulpuru S, Roth VR, Lawrence N, Forster AJ
BACKGROUND: Following the severe acute respiratory syndrome outbreak in 2003, hospitals have been mandated to use infection screening questionnaires to determine which patients have infectious respiratory illness and, therefore, require isolation precautions. Despite widespread use of symptom-based screening tools in Ontario, there are no data supporting the accuracy of these screening tools in hospitalized patients.
OBJECTIVE: To measure the performance characteristics of infection screening tools used during the H1N1 influenza season.
METHODS: The present retrospective cohort study was conducted at The Ottawa Hospital (Ottawa, Ontario) between October and December, 2009. Consecutive inpatients admitted from the emergency department were included if they were ≥18 years of age, underwent a screening tool assessment at presentation and had a most responsible diagnosis that was cardiac, respiratory or infectious. The gold-standard outcome was laboratory diagnosis of influenza.
RESULTS: The prevalence of laboratory-confirmed influenza was 23.5%. The sensitivity and specificity of the febrile respiratory illness screening tool were 74.5% (95% CI 60.5% to 84.8%) and 32.7% (95% CI 25.8% to 40.5%), respectively. The sensitivity and specificity of the influenza-like illness screening tool were 75.6% (95% CI 61.3% to 85.8%) and 46.3% (95% CI 38.2% to 54.7%), respectively.
CONCLUSIONS: The febrile respiratory illness screening tool missed 26% of active influenza cases, while 67% of noninfluenza patients were unnecessarily placed under respiratory isolation. Results of the present study suggest that infection-control practitioners should re-evaluate their strategy of screening patients at admission for contagious respiratory illness using symptom- and sign-based tests. Future efforts should focus on the derivation and validation of clinical decision rules that combine clinical features with laboratory tests.
PMID: 23762891 [PubMed - indexed for MEDLINE]