首页|脓毒症患者28d死亡危险因素分析及预测模型的构建与验证

脓毒症患者28d死亡危险因素分析及预测模型的构建与验证

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目的 构建用于预测脓毒症患者 28d死亡风险的列线图模型并验证其有效性。方法 回顾性分析 2017 年 1 月至 2022 年 12 月解放军联勤保障部队第九四〇医院重症医学科收治的 281 例脓毒症患者作为研究对象,按照 7∶3 的比例分为训练集(197 例)和验证集(84 例)。收集患者一般情况、入住重症监护病房(ICU)24 h内的诊疗情况、实验室检查指标等。依据 28d临床结局将患者分为存活组和死亡组。比较两组患者间各资料的差异,用Lasso回归筛选最优预测变量,用单因素和多因素Logistic回归分析脓毒症患者死亡的影响因素并建立列线图模型,通过受试者工作特征曲线(ROC曲线)、校准曲线、决策曲线分析(DCA)和临床影响曲线(CIC)对模型进行评价。结果 281 例脓毒症患者 28d死亡 82 例(29。18%),其中训练集和验证集死亡患者分别为 54 例(27。41%)和 28 例(33。33%)。Lasso回归分析、单因素和多因素Logistic回归分析后筛选出5 个与脓毒症患者死亡相关的独立预测因子,分别为血管活性药物使用[优势比(OR)=5。924,95%可信区间(95%CI)为 1。244~44。571,P=0。043]、急性生理学与慢性健康状况评分Ⅱ(APACHEⅡ:OR=1。051,95%CI为1。000~1。107,P=0。050)、合并多器官功能障碍综合征(MODS:OR=17。298,95%CI为5。517~76。985,P<0。001)、中性粒细胞计数(NEU:OR=0。934,95%CI为 0。879~0。988,P=0。022)和氧合指数(PaO2/FiO2:OR=0。994,95%CI为 0。988~0。998,P=0。017)。以上述独立预测因子构建列线图模型,ROC曲线分析显示,该列线图模型在训练集和验证集的曲线下面积(AUC)分别为0。899(95%CI为0。856~0。943)和0。909(95%CI为0。845~0。972);训练集和验证集的一致性指数(C-index)分别为 0。900 和 0。920,提示区分度较好;Hosmer-Lemeshoe检验均显示P>0。05,说明校准度较好,DCA和CIC证明该模型具有良好的临床效用。结论 血管活性药物使用、APACHEⅡ评分、合并MODS、NEU和PaO2/FiO2 是脓毒症患者 28d死亡的独立危险因素,基于上述因素构建的列线图模型对脓毒症患者 28d死亡风险预测具有一定的临床价值。
Analysis of 28 day-mortality risk factors in sepsis patients and construction and validation of predictive model
Objective To construct and validate a nomogram model for predicting the risk of 28-day mortality in sepsis patients.Methods A retrospective cohort study was conducted.281 sepsis patients admitted to the department of intensive care unit(ICU)of the 940th Hospital of the Joint Logistics Support Force of PLA from January 2017 to December 2022 were selected as the research subjects.The patients were divided into a training set(197 cases)and a validation set(84 cases)according to a 7∶3 ratio.The general information,clinical treatment measures and laboratory examination results within 24 hours after admission to ICU were collected.Patients were divided into survival group and death group based on 28-day outcomes.The differences in various data were compared between the two groups.The optimal predictive variables were selected using Lasso regression,and univariate and multivariate Logistic regression analyses were performed to identify factors influencing the mortality of sepsis patients and to establish a nomogram model.Receiver operator characteristic curve(ROC curve),calibration curve,decision curve analysis(DCA),and clinical impact curve(CIC)were used to evaluate the nomogram model.Results Out of 281 cases of sepsis,82 cases died with a mortality of 29.18%.The number of patients who died in the training and validation sets was 54 and 28,with a mortality of 27.41%and 33.33%respectively.Lasso regression,univariate and multivariate Logistic regression analysis screened for 5 independent predictors associated with 28-day mortality.There were use of vasoactive drugs[odds ratio(OR)=5.924,95%confidence interval(95%CI)was 1.244-44.571,P=0.043],acute physiology and chronic health evaluationⅡ(APACHEⅡ:OR=1.051,95%CIwas 1.000-1.107,P=0.050),combined with multiple organ dysfunction syndrome(MODS:OR=17.298,95%CI was 5.517-76.985,P<0.001),neutrophil count(NEU:OR=0.934,95%CI was 0.879-0.988,P=0.022)and oxygenation index(PaO2/FiO2:OR=0.994,95%CI was 0.988-0.998,P=0.017).A nomogram model was constructed using the independent predictive factors mentioned above,ROC curve analysis showed that the AUC of the nomogram model was 0.899(95%CI was 0.856-0.943)and 0.909(95%CI was 0.845-0.972)for the training and validation sets respectively.The C-index was 0.900 and 0.920 for the training and validation sets respectively,with good discrimination.The Hosmer-Lemeshoe tests both showed P>0.05,indicating good calibration.Both DCA and CIC plots demonstrate the model's good clinical utility.Conclusions The use of vasoactive,APACHEⅡscore,comorbid MODS,NEU and PaO2/FiO2 are independent risk factors for 28-day mortality in patients with sepsis.The nomogram model based on these 5 indicators has a good predictive ability for the occurrence of mortality in sepsis patients.

SepsisMultiple organ dysfunction syndromeNeutrophil countOxygenation indexRisk factorNomogram modelPrognosis

邵慧娟、王炎、张宏伟、周亚鹏、张江明、姚浩旗、刘东、刘冬梅

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解放军联勤保障部队第九四〇医院重症医学科,甘肃兰州 730050

甘肃中医药大学第一临床医学院,甘肃兰州 730000

解放军联勤保障部队第九四〇医院麻醉科,甘肃兰州 730050

脓毒症 多器官功能障碍综合征 中性粒细胞计数 氧合指数 危险因素 列线图模型 预后

甘肃省自然科学基金甘肃省自然科学基金甘肃省兰州市科技计划

21JR11RA00521JR7RA0022023-ZD-180

2024

中华危重病急救医学
中华医学会

中华危重病急救医学

CSTPCD北大核心
影响因子:3.049
ISSN:2095-4352
年,卷(期):2024.36(5)
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