Pediatrics:新型算法可有效区分细菌性和无菌性脑膜炎

2020-12-11 MedSci原创 MedSci原创

新的生物标志物,如降钙素和C-反应蛋白,可能有助于识别细菌性脑膜炎低风险或高风险。近日,西班牙的一项研究旨在开发和验证一个评分(MSE),以区分在急诊科进行初步评估胸膜炎儿童时的细菌性脑膜

新的生物标志物,如降钙素和C-反应蛋白,可能有助于识别细菌性脑膜炎低风险或高风险患儿。近日,西班牙的一项研究旨在开发和验证一个评分(MSE),以区分在急诊科进行初步评估胸膜炎儿童时的细菌性脑膜炎和无菌性脑膜炎,研究结果已在线发表于Pediatrics。

研究纳入了25个西班牙急诊科收治的29天至14岁的脑膜炎患儿。使用2011年至2016年之间的回顾性队列作为推导集,使用2017年至2018年期间招募的前瞻性队列作为验证集。

 

结果,纳入的1009例患者中,无菌性脑膜炎917例,细菌性脑膜炎92例。利用多变量逻辑回归分析,研究人员从推导集中确定了以下细菌性脑膜炎的预测因素:降钙素原(PCT)>1.2 ng/mL,脑脊液(CSF)蛋白>80 mg/dL,CSF绝对中性粒细胞数>1000个/mm3,C反应蛋白>40 mg/L。利用推导集,研究人员制定了MSE,对降钙素原赋值3分,CSF蛋白赋值2分,其他变量各赋值1分。MSE≥1可预测细菌性脑膜炎,灵敏度为100%(95%置信区间[CI]:95.0%-100%),特异性为83.2(95%CI:80.6-85.5),阴性预测值为100%(95%CI 99.4-100)。

综上所述,该研究结果表明,MSE能准确区分CSF胸膜炎患儿的细菌性和无菌性脑膜炎。

在线使用:儿童细菌性和非细菌性脑膜炎鉴别模型(MSE得分)

原始出处:

Santiago MintegiSilvia García, et al., Clinical Prediction Rule for Distinguishing Bacterial From Aseptic Meningitis. Pediatrics. 2020 Sep;146(3):e20201126. doi: 10.1542/peds.2020-1126. 

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    2021-02-12 feather89
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    2021-05-14 hbwxf
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    2020-12-11 言西早

    新型算法可有效区分细菌性和无菌性脑膜炎。

    0

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