Background: Valid clinical predictors of influenza in patients presenting with lower respiratory tract infection (LRTI) symptoms would provide adequate patient information and reassurance.
Aim: Assessing the validity of an existing diagnostic model (Flu Score) to detect influenza in LRTI patients.
Design and setting: A European diagnostic study recruited 1801 adult primary care patients with LRTI-like symptoms existing ≤7 days between October and April 2007-2010.
Method: History and physical examination findings were recorded and nasopharyngeal swabs taken. Polymerase chain reaction (PCR) for influenza A/B was performed as reference test. Diagnostic accuracy of the Flu Score (1× onset <48 hours + 2× myalgia + 1× chills or sweats + 2× fever and cough) was expressed as area under the curve (AUC), calibration slopes and likelihood ratios (LRs).
Results: A total of 273 patients (15%) had influenza on PCR. The AUC of the Flu Score during winter months was 0.66 [95% CI (95% confidence internal) 0.63-0.70]. During peak influenza season, both influenza prevalence (24%) and AUC were higher [0.71 (95% CI 0.66-0.76], but calibration remained poor. The Flu Score assigned 64% of the patients as 'low-risk' (10% had influenza, LR - 0.6). About 12% were classified as 'high risk' of whom 32% had influenza (LR + 2.7). During peak influenza season, 60% and 14% of patients were classified as low and high risk, respectively, with influenza prevalences being 14% (LR - 0.5) and 50% (LR + 3.2).
Conclusion: The Flu-Score attributes a small subgroup of patients with a high influenza risk (prevalence 32%). However, clinical usefulness is limited because this group is small and the association between predicted and observed risks is poor. Considerable diagnostic imprecision remains when it comes to differentiating those with influenza on clinical grounds from the many other causes of LRTI in primary care. New point of care tests are required that accurately, rapidly and cost effectively detect influenza in patients with respiratory tract symptoms in primary care.
Keywords: Cough; Europe; diagnostic accuracy; influenza; lower respiratory tract infection; primary health care..
© The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: firstname.lastname@example.org.