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神经外科ICU患者医院感染的危险因素分析及预测模型构建

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目的 分析神经外科ICU患者发生医院感染的危险因素,构建风险预测模型,为神经外科ICU患者医院感染的预测提供参考。方法 回顾性分析2021年1月至2022年12月该院神经外科ICU收治的280例患者的临床资料,根据患者是否发生医院感染分为感染组和未感染组,每组140例;按照7︰3比例随机抽取196例患者作为训练集建立模型,剩余84例患者作为验证集进行内部验证。采用logistic回归分析神经外科ICU患者医院感染的危险因素,建立感染预测模型,并绘制受试者工作特征(ROC)曲线评估模型预测效果。结果 通过多因素logistic回归分析,得出年龄大、手术时间长、导尿管使用时间长和糖皮质激素的使用是神经外科ICU患者发生医院感染的主要危险因素。基于多因素分析结果构建列线图模型,训练集和验证集ROC曲线下面积分别为0。796和0。875。矫正模型体现出实际诊断和预测诊断之间有较好的一致性。结论 该研究构建的模型对神经外科ICU患者发生医院感染的风险有较高的预测价值。
Analysis of nosocomial infection risk factors in neurosurgical ICU patients and its prediction model construction
Objective To analyze the risk factors of nosocomial infection among the patients in neuro-surgical ICU,and to construct the risk prediction model to provide reference for the prediction of nosocomial infection in neurosurgical ICU patients.Methods The clinical data of 280 patients admitted and treated in the neurosurgery ICU of this hospital from January 2021 to December 2022 were retrospectively analyzed.The pa-tients were divided into the infection group and non-infection group based on whether or not nosocomial infec-tion occurring,140 cases in each group.A total of 196 patients were extracted as the training set by a ratio of 7︰3 for constructing the model,while the remaining 84 patients served as the validation set for conducting the internal verification.The logistic regression was used to analyze the risk factors of nosocomial infection in the neurosurgery ICU patients,and a predictive model was established.The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive effect of the model.Results The multivariate logistic re-gression analysis indicated that old age,long surgery time,catheter use and glucocorticoids use were screened as the main risk factors of nosocomial infection occurrence in neurosurgery ICU patients.The nomogram mod-el was constructed based on the results of multivariate analysis,the area under the curve of training set and validation set were 0.796 and 0.875,respectively.The correcting model reflected good consistency between actual diagnosis and predictive diagnosis.Conclusion The model constructed in this study has the high predic-tive value for the nosocomial infection occurrence risk in the patients of the neurosurgery ICU.

neurosurgeryICUnosocomial infectionrisk factorpredictive model

朱晓松、张玲、王丽萍、孙志清、左志文、卓凤娟、彭善鑫、宋庆鑫

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临沂市人民医院医院感染管理部 山东临沂 276003

临沂市人民医院神经外科,山东临沂 276003

神经外科 重症监护室 医院感染 危险因素 预测模型

2024

重庆医学
重庆市卫生信息中心,重庆市医学会

重庆医学

CSTPCD
影响因子:1.797
ISSN:1671-8348
年,卷(期):2024.53(14)