University of Oulu

Takada, T., Hoogland, J., Hansen, J. G., Lindbaek, M., Autio, T., Alho, O.-P., Ebell, M. H., Reitsma, J. B., & Venekamp, R. P. (2022). Diagnostic prediction models for CT-confirmed and bacterial rhinosinusitis in primary care: Individual participant data meta-analysis. British Journal of General Practice, 72(721), e601–e608.

Diagnostic prediction models for CT-confirmed and bacterial rhinosinusitis in primary care : individual participant data meta-analysis

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Author: Takada, Toshihiko1,2; Hoogland, Jeroen1; Hansen, Jens G.3;
Organizations: 1Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
2Department of General Medicine, Shirakawa Satellite for Teaching And Research (STAR), Fukushima Medical University, Fukushima, Japan
3Department of Clinical Epidemiology, Aarhus University Hospital, Clinical Institute, Aarhus University, Aarhus, Denmark
4Department of General Practice, Institute of Health and Society, University Hospital of Oslo, Oslo, Norway
5Head & Neck Surgery, Oulu University Hospital, Oulu, Finland
6PEDEGO Research Unit, University of Oulu, Finland
7Department of Otorhinolaryngology, Head & Neck Surgery, Oulu University Hospital, Oulu, Finland
8Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, US.
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.1 MB)
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Language: English
Published: Royal College of General Practitioners, 2022
Publish Date: 2023-01-26


Background: Antibiotics are overused in patients with acute rhinosinusitis (ARS) as it is difficult to identify those who benefit from antibiotic treatment.

Aim: To develop prediction models for computed tomography (CT)-confirmed ARS and culture-confirmed acute bacterial rhinosinusitis (ABRS) in adults presenting to primary care with symptoms suggestive of ARS.

Design and setting: This was a systematic review and individual participant data meta-analysis.

Method: CT-confirmed ARS was defined as the presence of fluid level or total opacification in any maxillary sinuses, whereas culture-confirmed ABRS was defined by culture of fluid from antral puncture. Prediction models were derived using logistic regression modelling.

Results: Among 426 patients from three studies, 140 patients (32.9%) had CT-confirmed ARS. A model consisting of seven variables: previous diagnosis of ARS, preceding upper respiratory tract infection, anosmia, double sickening, purulent nasal discharge on examination, need for antibiotics as judged by a physician, and C-reactive protein (CRP) showed an optimism-corrected c-statistic of 0.73 (95% confidence interval [CI] = 0.69 to 0.78) and a calibration slope of 0.99 (95% CI = 0.72 to 1.19). Among 225 patients from two studies, 68 patients (30.2%) had culture-confirmed ABRS. A model consisting of three variables: pain in teeth, purulent nasal discharge, and CRP showed an optimism-corrected c-statistic of 0.70 (95% CI = 0.63 to 0.77) and a calibration slope of 1.00 (95% CI = 0.66 to 1.52). Clinical utility analysis showed that both models could be useful to rule out the target condition.

Conclusion: Simple prediction models for CT-confirmed ARS and culture-confirmed ABRS can be useful to safely reduce antibiotic use in adults with ARS in high-prescribing countries.

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Series: British journal of general practice
ISSN: 0960-1643
ISSN-E: 1478-5242
ISSN-L: 0960-1643
Volume: 72
Issue: 721
Pages: e601 - e608
DOI: 10.3399/bjgp.2021.0585
Type of Publication: A1 Journal article – refereed
Field of Science: 3125 Otorhinolaryngology, ophthalmology
Funding: The Netherlands Organisation for Health Research and Development (grant reference: 91618026).
Copyright information: © The Authors. This article is Open Access: CC BY 4.0 licence (