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神经内镜联合显微镜血肿清除术后中枢神经系统感染的风险因素与列线图模型构建

Central Nervous System Infection After Neuroendoscopic and Microscopic Combined Hematoma Removal: Risk Factors and Construction of a Nomogram Prediction Model

  • 摘要:
    目的 分析神经内镜联合显微镜血肿清除术后患者中枢神经系统感染的危险因素,构建列线图模型并进行验证。
    方法 回顾性纳入2021年1月–2024年12月医院收治460例行神经内镜联合显微镜血肿清除术的患者,7∶3分配为建模集(n=322)和验证集(n=138),根据是否发生中枢神经系统感染将建模集分为感染组(n=68)和未感染组(n=254),通过logistic回归方程筛选中枢神经系统感染的独立预测因子,并据此建立列线图预测模型。
    结果 460例患者感染总发生率为20.65%(95/460),logistic回归分析结果显示,神经内镜联合显微镜血肿清除术后患者中枢神经系统感染的独立危险因素包括糖尿病史〔比值比(odds ratio, OR)=3.431,95%置信区间(confidence interval, CI):1.300~9.057〕、格拉斯哥昏迷量表(GCS)评分(OR=0.574,95%CI:0.462~0.711)、脑脊液渗漏(OR=4.492,95%CI:1.430~14.116),以及手术时间(OR=1.011,95%CI:1.004~1.019)、引流管留置时间(OR=5.452,95%CI:2.423~12.268)和白蛋白(ALB)(OR=0.778,95%CI:0.720~0.840)(P<0.05)。基于上述危险因素构建列线图预测模型,在建模集和验证集中预测事件发生的曲线下面积(area under the curve, AUC)为0.928(95%CI:0.895~0.960)、0.918(95%CI:0.885~0.951),校准曲线与理想曲线拟合度良好(Hosmer-Lemeshow检验P>0.05),决策曲线分析具有显著净收益优势。
    结论 基于糖尿病史、GCS评分、脑脊液渗漏、手术时长、引流管留置时间及ALB水平构建的列线图预测模型,对神经内镜辅助显微镜下血肿清除术后并发中枢神经系统感染具有较高预测效能。

     

    Abstract:
    Objective  To analyze the risk factors associated with central nervous system (CNS) infection in patients after neuroendoscopic hematoma removal combined with and microscopic hematoma removal, and to construct and validate a nomogram prediction model.
    Methods  A total of 460 patients who underwent neuroendoscopic hematoma removal combined with microscopic hematoma removal at our hospital between January 2021 and December 2024 were retrospectively enrolled. The patients were assigned to a modeling cohort (n = 322) and a validation cohort (n = 138) in a 7∶3 ratio. Furthermore, the modeling cohort was divided into an infection group (n = 68) and a non-infected group (n = 254) according to whether CNS infection occurred. The independent predictors of central nervous system infection were identified by logistic regression analysis, and a nomogram prediction model was constructed accordingly.
    Results  The overall incidence of CNS infection in the 460 patients was 20.65% (95/460). According to the logistic regression analysis, the independent risk factors for CNS infection in patients after neuroendoscopic and microscopic combined hematoma removal included a history of diabetes mellitus (odds ratio OR = 3.431, 95% CI: 1.300-9.057), the Glasgow Coma Scale (GCS) score (OR = 0.574, 95% CI: 0.462-0.711), cerebrospinal fluid leakage (OR = 4.492, 95% CI: 1.430-14.116), operation duration (OR = 1.011, 95% CI: 1.004-1.019), duration of drainage tube placement (OR = 5.452, 95% CI: 2.423-12.268) and albumin (ALB) level (OR = 0.778, 95% CI: 0.720-0.840) (P < 0.05). Based on these risk factors, a nomogram prediction model was constructed, and the area under the receiver operating characteristic curve (AUC) of the predicted events in the modeling cohort and the validation cohort was 0.928 (95% CI: 0.895-0.960) and 0.918 (95% CI: 0.885-0.951), respectively. The calibration curve fitted well with the ideal curve (Hosmer-Lemeshow test, P > 0.05), and the decision curve analysis demonstrated significant net benefit.
    Conclusion  The nomogram model based on history of diabetes mellitus, GCS score, cerebrospinal fluid leakage, operation duration, duration of drainage tube placement, and ALB level demonstrates high predictive performance for CNS infection after neuroendoscopy-assisted microscopic hematoma removal.

     

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