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

Autor:	Takada T; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; associate professor, Department of General Medicine, Shirakawa Satellite for Teaching And Research (STAR), Fukushima Medical University, Fukushima, Japan., Hoogland J; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands., Hansen JG; Department of Clinical Epidemiology, Aarhus University Hospital, Clinical Institute, Aarhus University, Aarhus, Denmark., Lindbaek M; Department of General Practice, Institute of Health and Society, University Hospital of Oslo, Oslo, Norway., Autio T; Head & Neck Surgery, Oulu University Hospital, Oulu, Finland., Alho OP; PEDEGO Research Unit, University of Oulu, Finland; professor of otorhinolaryngology, Department of Otorhinolaryngology, Head & Neck Surgery, Oulu University Hospital, Oulu, Finland., Ebell MH; Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, US., Reitsma JB; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands., Venekamp RP; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Jazyk:	angličtina
Zdroj:	The British journal of general practice : the journal of the Royal College of General Practitioners [Br J Gen Pract] 2022 Jul 28; Vol. 72 (721), pp. e601-e608. Date of Electronic Publication: 2022 Jul 28 (Print Publication: 2022).
DOI:	10.3399/BJGP.2021.0585
Abstrakt:	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. (© The Authors.)
Databáze:	MEDLINE
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