怀疑中枢神经系统感染的儿童细菌脑膜炎的诊断预测模型:系统性审查和前性验证研究
Nina S Groeneveld1, Merijn W Bijlsma2, Ingeborg E van Zeggeren1
1Department of Neurology, Amsterdam UMC Location AMC, Amsterdam, The Netherlands.
BMJ open
|August 8, 2024
概括
诊断预测模型有效地帮助排除疑似中枢神经系统 (CNS) 感染的儿童的细菌性脑膜炎 (BM). 这些模型的准确性很好,但应该补充,而不是取代临床评估.
科学领域:
- 儿童传染病 儿童传染病
- 临床流行病学临床流行病学
- 诊断测试评价 诊断测试评价 诊断测试评价
背景情况:
- 细菌性脑膜炎 (BM) 在怀疑中枢神经系统 (CNS) 感染的儿童中具有重大风险.
- 现有的诊断预测模型旨在评估儿科患者的BM概率.
研究的目的:
- 在广泛的儿科人口中对细菌性脑膜炎 (BM) 的现有诊断预测模型进行外部验证.
- 评估这些模型在疑似中枢神经系统感染的儿童中的诊断准确性和校准.
主要方法:
- 在Medline的系统文献审查中,确定了BM的相关预测模型.
- 在450名疑似中枢神经系统感染的儿童 (0-18岁) 的前队伍中对已识别的模型进行外部验证 (2012-2015).
- 计算灵敏度,特异性,预测值,AUC和校准评估.
主要成果:
- 23个预测模型得到了验证. 17%的患者患有中枢神经系统感染,7%的患者被诊断为BM.
- 总体AUC在0.69到0.94之间 (中位数为0.83).
- 模型表现良好至优秀,特别是在28天以上的儿童中 (中位数AUC为0.89).
结论:
- 诊断预测模型表现出良好的到优秀的测试特征,用于排除儿科患者的BM.
- 这些模型可以帮助诊断疑似儿童中枢神经系统感染的诊断工作.
- 模型应与彻底的临床评估和辅助测试一起使用,而不是作为替代品.
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