Diagnostic prediction models for bacterial meningitis in children with a suspected central nervous system infection: a systematic review and prospective validation study

Objectives Diagnostic prediction models exist to assess the probability of bacterial meningitis (BM) in paediatric patients with suspected meningitis. To evaluate the diagnostic accuracy of these models in a broad population of children suspected of a central nervous system (CNS) infection, we perfo...

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Main Authors: Michael W T Tanck, Matthijs C Brouwer, Diederik van de Beek, Merijn W Bijlsma, Nina S Groeneveld, Ingeborg E van Zeggeren, Steven L Staal
Format: Article
Language:English
Published: BMJ Publishing Group 2024-08-01
Series:BMJ Open
Online Access:https://bmjopen.bmj.com/content/14/8/e081172.full
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author Michael W T Tanck
Matthijs C Brouwer
Diederik van de Beek
Merijn W Bijlsma
Nina S Groeneveld
Ingeborg E van Zeggeren
Steven L Staal
author_facet Michael W T Tanck
Matthijs C Brouwer
Diederik van de Beek
Merijn W Bijlsma
Nina S Groeneveld
Ingeborg E van Zeggeren
Steven L Staal
author_sort Michael W T Tanck
collection DOAJ
description Objectives Diagnostic prediction models exist to assess the probability of bacterial meningitis (BM) in paediatric patients with suspected meningitis. To evaluate the diagnostic accuracy of these models in a broad population of children suspected of a central nervous system (CNS) infection, we performed external validation.Methods We performed a systematic literature review in Medline to identify articles on the development, refinement or validation of a prediction model for BM, and validated these models in a prospective cohort of children aged 0–18 years old suspected of a CNS infection.Primary and secondary outcome measures We calculated sensitivity, specificity, predictive values, the area under the receiver operating characteristic curve (AUC) and evaluated calibration of the models for diagnosis of BM.Results In total, 23 prediction models were validated in a cohort of 450 patients suspected of a CNS infection included between 2012 and 2015. In 75 patients (17%), the final diagnosis was a CNS infection including 30 with BM (7%). AUCs ranged from 0.69 to 0.94 (median 0.83, interquartile range [IQR] 0.79–0.87) overall, from 0.74 to 0.96 (median 0.89, IQR 0.82–0.92) in children aged ≥28 days and from 0.58 to 0.91 (median 0.79, IQR 0.75–0.82) in neonates.Conclusions Prediction models show good to excellent test characteristics for excluding BM in children and can be of help in the diagnostic workup of paediatric patients with a suspected CNS infection, but cannot replace a thorough history, physical examination and ancillary testing.
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spelling doaj-art-d29803df67484c7d9c1f693c02bc337d2025-08-20T02:17:33ZengBMJ Publishing GroupBMJ Open2044-60552024-08-0114810.1136/bmjopen-2023-081172Diagnostic prediction models for bacterial meningitis in children with a suspected central nervous system infection: a systematic review and prospective validation studyMichael W T Tanck0Matthijs C Brouwer1Diederik van de Beek2Merijn W Bijlsma3Nina S Groeneveld4Ingeborg E van Zeggeren5Steven L Staal6Department of Epidemiology and Data Science, Amsterdam UMC—Locatie AMC, Amsterdam, The NetherlandsDepartment of Neurology, Amsterdam UMC Location AMC, Amsterdam, The NetherlandsDepartment of Neurology, Amsterdam UMC Location AMC, Amsterdam, The NetherlandsDepartment of Pediatrics, Amsterdam UMC Location AMC, Amsterdam, The NetherlandsDepartment of Neurology, Amsterdam UMC Location AMC, Amsterdam, The NetherlandsDepartment of Neurology, Amsterdam UMC Location AMC, Amsterdam, The NetherlandsDepartment of Neurology, Amsterdam UMC Location AMC, Amsterdam, The NetherlandsObjectives Diagnostic prediction models exist to assess the probability of bacterial meningitis (BM) in paediatric patients with suspected meningitis. To evaluate the diagnostic accuracy of these models in a broad population of children suspected of a central nervous system (CNS) infection, we performed external validation.Methods We performed a systematic literature review in Medline to identify articles on the development, refinement or validation of a prediction model for BM, and validated these models in a prospective cohort of children aged 0–18 years old suspected of a CNS infection.Primary and secondary outcome measures We calculated sensitivity, specificity, predictive values, the area under the receiver operating characteristic curve (AUC) and evaluated calibration of the models for diagnosis of BM.Results In total, 23 prediction models were validated in a cohort of 450 patients suspected of a CNS infection included between 2012 and 2015. In 75 patients (17%), the final diagnosis was a CNS infection including 30 with BM (7%). AUCs ranged from 0.69 to 0.94 (median 0.83, interquartile range [IQR] 0.79–0.87) overall, from 0.74 to 0.96 (median 0.89, IQR 0.82–0.92) in children aged ≥28 days and from 0.58 to 0.91 (median 0.79, IQR 0.75–0.82) in neonates.Conclusions Prediction models show good to excellent test characteristics for excluding BM in children and can be of help in the diagnostic workup of paediatric patients with a suspected CNS infection, but cannot replace a thorough history, physical examination and ancillary testing.https://bmjopen.bmj.com/content/14/8/e081172.full
spellingShingle Michael W T Tanck
Matthijs C Brouwer
Diederik van de Beek
Merijn W Bijlsma
Nina S Groeneveld
Ingeborg E van Zeggeren
Steven L Staal
Diagnostic prediction models for bacterial meningitis in children with a suspected central nervous system infection: a systematic review and prospective validation study
BMJ Open
title Diagnostic prediction models for bacterial meningitis in children with a suspected central nervous system infection: a systematic review and prospective validation study
title_full Diagnostic prediction models for bacterial meningitis in children with a suspected central nervous system infection: a systematic review and prospective validation study
title_fullStr Diagnostic prediction models for bacterial meningitis in children with a suspected central nervous system infection: a systematic review and prospective validation study
title_full_unstemmed Diagnostic prediction models for bacterial meningitis in children with a suspected central nervous system infection: a systematic review and prospective validation study
title_short Diagnostic prediction models for bacterial meningitis in children with a suspected central nervous system infection: a systematic review and prospective validation study
title_sort diagnostic prediction models for bacterial meningitis in children with a suspected central nervous system infection a systematic review and prospective validation study
url https://bmjopen.bmj.com/content/14/8/e081172.full
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