Title
Validity of a clinical model to predict influenza in patients presenting with symptoms of lower respiratory tract infection in primary care
Author
Faculty/Department
Faculty of Medicine and Health Sciences
Publication type
article
Publication
Oxford ,
Subject
Human medicine
Source (journal)
Family practice. - Oxford
Volume/pages
32(2015) :4 , p. 408-414
ISSN
0263-2136
ISI
000359162100008
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
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 20072010. 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) 0.630.70]. During peak influenza season, both influenza prevalence (24%) and AUC were higher [0.71 (95% CI 0.660.76], 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.
Full text (open access)
https://repository.uantwerpen.be/docman/irua/982d01/fbc56395.pdf
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