脓毒症合并急性静脉血栓预测模型的建立与验证

Construction and validation of a predictive model for acute venous thromboembolism in patients with sepsis

关键词:  脓毒症  危险因素  静脉血栓  预测模型  列线图

Key words:  sepsis  risk factors  venous thromboembolism  prediction model  nomogram

摘要:

目的 建立脓毒症患者合并急性静脉血栓的预测模型。 方法 回顾性纳入美国MIMIC Ⅲ重症数据库2010—2012年的脓毒症患者资料。根据住院期间是否合并急性静脉血栓，将患者分为两组。从人口学特征、合并症、实验室结果和干预措施等方面，初步筛选出26个变量。使用LASSO回归分析及Logistic回归分析选择预测因子并绘制预测模型,即“列线图”。通过Harrell一致性指数(C指数)和受试者工作特征(ROC)曲线对预测模型的性能进行评价。同时收集同济大学附属同济医院ICU 2020年1月—2022年12月297例脓毒症患者的数据对模型进行外部验证。 结果 多因素Logistic回归分析显示，D-二聚体(OR=9.183,95%CI: 8.124~10.251,P=0.005)、平均动脉压(OR=0.096,95%CI: 0.042~0.217,P<0.001)、血乳酸(OR=5.077,95%CI: 3.194~8.071,P<0.001)、充血性心力衰竭(OR=2.452,95%CI: 1.566~3.839,P<0.001)和机械通气(OR=2.061,95%CI: 1.319~3.221,P= 0.001)为脓毒症患者合并急性静脉血栓的独立预测因素。将D-二聚体、平均动脉压、充血性心力衰竭、血乳酸和机械通气5个变量进行整合，构建出预测模型。队列内部验证显示，C指数为 0.922(95%CI: 0.891~0.953,P<0001)，ROC曲线下面积(AUC)为0.92；外部验证显示，C指数为0.832(95%CI: 0.744~0.920,P<0.001)，AUC为0.76。 结论 D-二聚体、平均动脉压、充血性心力衰竭、血乳酸和机械通气构成的预测模型能早期识别脓毒症患者发生急性静脉血栓的风险，该模型具有良好的预测效能。

Abstract:

Objective To construct a predicting model for acute venous thromboembolism(VTE) in patients with sepsis. Methods Clinical data of patients with sepsis in the Medical Information Mart for Intensive Care Ⅲ(MIMIC Ⅲ) database from 2010 to 2012 were retrospectively analyzed. The patients were randomly divided into two groups based on whether they had VTE during hospitalization. A total of 26 variables were initially screened, including demographic characteristics, comorbidities, laboratory results, and interventions. LASSO regression and Logistic regression were utilized for selecting predictors and constructing prediction models(nomogram). Discrimination and calibration of nomogram was evaluated by Harrell’s concordance index(C-index) and receiver operating characteristic(ROC) curve. The data from 297 cases of sepsis patients treated in the intensive care unit(ICU) of Tongji Hospital Affiliated to Tongji University from January 2020 to December 2022 were collected for external validation of the model. Results Multivariate Logistic regression analysis showed that D-dimer(OR=9.183, 95%CI: 8.124-10.251, P=0.005), mean arterial pressure(MAP)(OR=0.096, 95%CI: 0.042-0.217, P<0.001), blood lactate(OR=5.077, 95%CI: 3194-8.071, P<0.001), congestive heart failure(OR=2.452,95%CI: 1.566-3.839, P<0.001) and mechanical ventilation(OR=2.061, 95%CI: 1.319-3.221, P=0.001) were independent predictors of VTE in sepsis patients. The variables D-dimer, MAP, congestive heart failure, blood lactate, and mechanical ventilation were integrated to construct a predictive model. Internal validation showed a C-index of 0.922(95%CI: 0.891-0.953, P<0.001), with an area under the ROC cure(AUC) of 0.92. External validation revealed a C-index of 0.832(95%CI: 0.744-0.920, P<0001), with an AUC of 0.76. Conclusion The model established in this study, which is composed of D-dimer, MAP, congestive heart failure, blood lactate and mechanical ventilation, can effectively predict the early risk of acute VTE in patients with sepsis.