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胶质瘤切除术后中枢神经系统感染的风险预测与管理——来自三级医疗中心的8年经验

Risk Prediction and Management for Central Nervous System Infection After Resection for Gliomas-The 8-Year Experience from a Tertiary Medical Center.

作者信息

Zhang Xin, Zheng Zhiyao, Guo Xiaopeng, Wang Hai, Gong Le, Wang Yu, Guo Fuping, Ma Wenbin

机构信息

Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100006, China.

Department of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100006, China.

出版信息

J Clin Med. 2024 Dec 18;13(24):7733. doi: 10.3390/jcm13247733.

Abstract

: To identify risk factors for central nervous system infection (CNSI) following glioma resection and develop a predictive model. : Retrospective analysis of 435 glioma resection cases was conducted to assess CNSI risk factors. A nomogram predictive model was constructed and validated internally and externally. CSF characteristics and antibiotic use in CNSI patients were summarized and the impact of CNSI on long-term prognosis was evaluated. : CNSI incidence was 14.9%. Independent risk factors included ventricular opening, postoperative systemic infection, maximum diameter ≥ 5 cm, and preoperative peripheral blood monocyte percentage ≥ 10%. The predictive model showed good performance (C statistic = 0.797, AUC = 0.731). CNSI patients had elevated CSF protein and leukocytes, with meropenem and vancomycin as primary antibiotics. CNSI had no significant impact on long-term prognosis. : Key risk factors for CNSI were identified, and an effective predictive model was established, providing important references for clinical decision-making and CNSI management.

摘要

目的

确定胶质瘤切除术后中枢神经系统感染(CNSI)的危险因素并建立预测模型。方法:对435例胶质瘤切除病例进行回顾性分析以评估CNSI危险因素。构建列线图预测模型并进行内部和外部验证。总结CNSI患者的脑脊液特征和抗生素使用情况,并评估CNSI对长期预后的影响。结果:CNSI发生率为14.9%。独立危险因素包括脑室开放、术后全身感染、最大直径≥5 cm和术前外周血单核细胞百分比≥10%。预测模型表现良好(C统计量=0.797,AUC=0.731)。CNSI患者脑脊液蛋白和白细胞升高,主要抗生素为美罗培南和万古霉素。CNSI对长期预后无显著影响。结论:确定了CNSI的关键危险因素,并建立了有效的预测模型,为临床决策和CNSI管理提供了重要参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9737/11678521/0940b8eb029c/jcm-13-07733-g001.jpg

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