构建与验证神经外科术后中枢神经系统感染的预后模型
Development and validation of prognostic nomogram for post-operative central nervous system infections after neurosurgery
程利 1王莉 2蔡强3
作者信息
- 1. 武汉大学人民医院东院重症医学科,武汉 430200
- 2. 江汉大学附属医院,武汉 432200
- 3. 武汉大学人民医院东院神经外科,武汉 430200
- 折叠
摘要
目的 构建与验证针对神经外科术后中枢神经系统感染(PCNSIs)患者影响预后的风险列线图模型.方法 收集2020年1月至2022年9月武汉大学人民医院和湘潭市中心医院收治的320例PCNSIs确诊患者的临床资料,其中男152例,女168例,年龄18～85岁(62.4±17.7)岁.Cox回归确定危险因素,内部验证采用自举法;外部验证经受试者工作特征(ROC)曲线、C指数及校准曲线评价模型的预测性能;决策曲线分析(DCA)评估模型的实用价值.计量资料的组间比较采用Mann-Whitney U检验,计数资料的组间比较采用x2检验.结果 共纳入PCNSIs确诊患者320例,43.4％(139/320)预后良好,56.6％(181/320)预后不良.Cox回归显示,≥3种基础疾病[风险比(HR)=1.507,95％置信区间(CI):1.018～2.232,P＜0.05]、检出多重耐药菌(HR=1.521,95％CI:1.029～2.248,P＜0.05)、合并脓毒症(HR=1.539,95％CI:1.046～2.263,P＜0.05)、急性生理与慢性健康状况评分(APACHE Ⅱ)(HR=1.096,95％CI:1.043～1.152,P＜0.05)及降钙素原(HR=1.010,95％CI:1.001～1.018,P＜0.05)是影响预后的独立危险因素;格拉斯哥昏迷评分(GCS)(HR=0.873,95％CI:0.834～0.915,P＜0.05)是唯一保护性因素.训练队列 30 d 和 60 d 模型的曲线下面积(AUC)分别为 0.786(95％CI:0.656～0.931)和 0.872(95％CI:0.723～0.968);验证队列 30 d 和 60 d 模型的 AUC 分别为 0.709(95％CI:0.612～0.847)和 0.776(95％CI:0.707～0.903).Hosmer-Lemeshow 检验结果显示,训练队列 30 d(x2=5.062,P＞0.05)低于 60d 模型(x2=4.749,P＞0.05);验证队列 30d(x2=8.117,P＞0.05)低于 60 d 模型(x2=7.658,P＞0.05).DCA分析显示,两队列60 d模型的净获益明显高于30 d模型(x2=2.132,P＜0.05).结论 本研究构建的针对PCNSIs患者的预后模型经内部及外部验证后,该模型的预测准确性较高.
Abstract
Objective To construct and validate a risk nomogram for predicting the prognosis of patients with post-operative central nervous system infections(PCNSIs).Methods The clinical data of 320 patients with PCNSIs in Renmin Hospital of Wuhan University and Xiangtan Central Hospital from Jan-uary 2020 to September 2022 were collected,including 152 males and 168 females aged 18 to 85 years(62.4±17.7)years.Cox regression to identify risk factors.Internal validation was conducted using the bootstrap method,while external validation evaluated the predictive performance of the model through re-ceiver operating characteristic(ROC)curve,C-index,and calibration curve.Decision curve analysis(DCA)was performed to assess the utility of the model.Mann Whitney U test was used for inter group comparison of quantitative data;the comparison of count data between groups was conducted using chi square test.Results A total of 320 patients with confirmed PCNSIs were included,among which 43.4％(139/320)had good prognosis and 56.6％(181/320)had poor prognosis.The results of Cox analysis showed that ≥3 basic disease histories[risk ratio(HR)=1.507,95％confidence interval(CI):1.018-2.232,P＜0.05],detection of multidrug-resistant bacteria(HR=1.521,95％CI:1.029-2.248,P＜0.05),sepsis(HR=1.539,95％CI:1.046-2.263,P＜0.05),acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(HR=1.096,95％CI:1.043-1.152,P＜0.05)and procalcitonin(HR=1.010,95％CI:1.00-1.018,P＜0.05)were independent risk factors affecting prognosis,while the glasgow coma score(GCS)(HR=0.873,95％CI:0.834-0.915,P＜0.05)was the only protective factor.The area under the curve(AUC)of the 30 d and 60 d models of the training cohort were 0.786(95％CI:0.656-0.931)and 0.872(95％CI:0.723-0.968),while the AUC of the 30 d and 60 d mod-els of the validation cohort were 0.709(95％CI:0.612-0.847)and 0.776(95％CI:0.707-0.903)re-spectively.The Hosmer-Lemeshow test results showed that the training cohort for 30 d model(x2=5.062,P＞0.05)was lower than the 60 d model(x2=4.749,P＞0.05),as well as for the 30 d model(x2=8.117,P＞0.05)was lower than the 60 d model(x2=7.658,P＞0.05)in the validation cohort.The DCA showed that the 60 d model exhibits significantly higher net benefit compared to the 30 d model in both cohorts(x2=2.132,P＜0.05).Conclusion After internal and external validation,the prognostic nomo-gram for patients with PCNSIs developed in this study had demonstrated high predictive accuracy.
关键词
神经外科术后中枢神经系统感染/列线图/预后/预测Key words
Post-operative central nervous system infections/Nomogram/Prognosis/Prediction引用本文复制引用
出版年
2024
NETL
NSTL
万方数据