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脑卒中患者医院感染危险因素分析及列线图预测模型构建

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目的:探讨脑卒中患者发生医院感染的危险因素,并构建医院感染风险预测模型.方法:选择 2020 年 1月至 2023 年 12 月在南通大学附属医院神经内科和神经外科住院期间发生医院感染的 300 例脑卒中患者(感染组),另选择同期未发生医院感染的脑卒中患者 300 例(对照组),分析医院感染及病原菌分布情况,比较两组临床特征,采用多因素Logistic回归分析脑卒中患者医院感染的危险因素,纳入R语言建立预测风险的列线图模型,并评估该模型的预测效果.结果:脑卒中患者医院感染部位以呼吸系统为主(62.67%,188/300),医院感染病原菌以革兰阴性菌为主(59.90%,121/202),其中多重耐药菌感染占 34.16%(69/202);与对照组相比,感染组脑出血、糖尿病、高血压、冠心病、意识障碍、呼吸机辅助呼吸、深静脉置管、导尿管留置、预防性使用抗菌药物、体质量指数(body mass index,BMI)≥24 kg/m2、住院时间≥14 d占比明显增高(P<0.05);多因素Logistic回归分析结果显示,卒中类型、高血压、糖尿病、BMI≥24 kg/m2、意识障碍、呼吸机辅助呼吸、导尿管留置、预防性使用抗菌药物、住院时间≥14 d是脑卒中患者发生医院感染的独立危险因素(P<0.05).基于回归结果构建列线图预测模型,ROC曲线下面积为 0.983(95%CI:0.975~0.991),灵敏度为 0.940,特异度为 0.937,Hosmer-Lemeshow检验(χ2=5.454,P=0.708)提示模型具有较好的拟合度和预测效能.结论:脑卒中患者发生医院感染的危险因素包括脑卒中类型、高血压和糖尿病等,基于此构建的列线图预测模型可较准确预测脑卒中患者发生医院感染的风险.
Risk factors analysis and nomogram prediction model construction of nosocomial infection in stroke patients
Objective:To investigate the risk factors of hospital infection in stroke patients and construct a risk prediction model of nosocomial infection.Methods:A total of 300 stroke patients with nosocomial infection during hospitalization in the Department of Neurology and Neurosurgery of Affiliated Hospital of Nantong University from January 2020 to December 2023 were also selected(infection group),and another 300 stroke patients without nosocomial infection during the same period were selected(control group).The distribution of nosocomial infection and pathogenic bacteria were analyzed,and clinical characteristics of the two groups were compared.Multivariate Logistic regression was used to analyze the risk factors of nosocomial infection in stroke patients,and a nomogram model for predicting risk was established by incorporating R language,and the predictive effect of the model was evaluated.Results:The predominant nosocomial infection site of stroke patients was the respiratory system(62.67%,188/300),the predominant pathogenic bacteria of nosocomial infection were Gram-negative bacteria(59.90%,121/202),and the multidrug-resistant bacteria infection accouned for 34.16%(69/202).Compared with the control group,the infection group had higher proportion of cerebral hemorrhage,diabetes,hypertension,coronary heart disease,disturbance of consciousness,central venous catheters,ventilators,urinary catheters,and preventive use of antibiotics,body mass index(BMI)≥24 kg/m2 and hospitalization time≥14 d(P<0.05).Multivariate Logistic regression analysis showed that stroke type,hypertension,diabetes,BMI≥24 kg/m2,disturbance of consciousness,use of ventilator,indwelling urinary catheter,preventive use of antibiotics,and hospitalization time≥14 d were independent risk factors for nosocomial infection in stroke patients(P<0.05).A nomogram prediction model was constructed based on the regression results,and the area under ROC curve was 0.983(95%CI:0.975-0.991).The sensitivity and specificity was 0.940 and 0.937,respetictively.The Hosmer-Lemeshow test(χ2=5.454,P=0.708)indicated that the model had a good fit and predictive performance.Conclusion:The risk factors of nosocomial infection in stroke patients include stroke type,hypertension and diabetes,etc.The prediction model based on the risk factors could accurately predict the risk of nosocomial infection in stroke patients.

strokenosocomial infectionpathogenic bacteriarisk factorsprediction modelnomogram

顾李琴、陈肖漪、章艳菊、陈晓君

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南通大学附属医院 感染管理办公室,江苏 南通 226001

南通大学附属医院 消化内科,江苏 南通 226001

脑卒中 医院感染 病原菌 危险因素 预测模型 列线图

2025

江苏大学学报(医学版)
江苏大学

江苏大学学报(医学版)

影响因子:0.535
ISSN:1671-7783
年,卷(期):2025.35(1)