用于预测主动脉瘤手术后重症监护病房死亡率的SAB模型的开发。

Development of SAB model for predicting mortality in intensive care unit after aortic aneurysm surgery.

作者信息

Huang Kai, Shen Runnan, Peng Senyi, Li Ling, You Guochang, Kang Shimao, Zhan Xinyi, Zhu Dongxi, Zheng Junmeng

机构信息

Department of Cardiovascular Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China; Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.

Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.

出版信息

Ann Palliat Med. 2021 Oct;10(10):10147-10159. doi: 10.21037/apm-21-1660. Epub 2021 Sep 13.

DOI:10.21037/apm-21-1660

PMID:34551573

Abstract

BACKGROUND

Aortic aneurysm (AA) patients after vascular surgery are at high risk of death, some of them need intensive care. Our aim was to develop a simplified model with baseline data within 24 hours of intensive care unit (ICU) admission to early predict mortality.

METHODS

Univariate analysis and least absolute shrinkage and selection operator were used to select important variables, which were then taken into logistic regression to fit the model. Discrimination and validation were used to evaluate the performance of the model. Bootstrap method was conducted to perform internal validation. Finally, decision clinical analysis curve was used to test the clinical usefulness of the model.

RESULTS

We obtained baseline data of 482 AA patients from Medical Information Mart for Intensive Care III database, 33 (6.8%) of whom died in ICU. Our final model contained three variables and was called SAB model based on initials of three items [Sepsis, Anion gap, Bicarbonate (SAB)]. Area under the curve of SAB was 0.904 (95% CI: 0.841-0.967) while brier score was 0.043 (95% CI: 0.028-0.057). After internal validation, corrected area under the curve was 0.898 and brier score was 0.045, which showed good prediction ability of SAB model. The model can be assessed on https://vascularmodel.shinyapps.io/AorticAneurysm/.

CONCLUSIONS

SAB model derived in this study can be easily used to predict in-ICU mortality of AA patients after surgery precisely.

摘要

背景

血管手术后的主动脉瘤（AA）患者死亡风险很高，其中一些患者需要重症监护。我们的目的是开发一种简化模型，利用重症监护病房（ICU）入院24小时内的基线数据来早期预测死亡率。

方法

采用单因素分析和最小绝对收缩和选择算子来选择重要变量，然后将这些变量纳入逻辑回归以拟合模型。使用判别和验证来评估模型的性能。采用自助法进行内部验证。最后，使用决策临床分析曲线来检验模型的临床实用性。

结果

我们从重症监护医学信息集市III数据库中获取了482例AA患者的基线数据，其中33例（6.8%）在ICU死亡。我们的最终模型包含三个变量，根据三个项目[脓毒症、阴离子间隙、碳酸氢盐（SAB）]的首字母被称为SAB模型。SAB的曲线下面积为0.904（95%CI：0.841-0.967），而Brier评分是0.043（95%CI：0.028-0.057）。经过内部验证，校正后的曲线下面积为0.898，Brier评分为0.045，这表明SAB模型具有良好的预测能力。该模型可在https://vascularmodel.shinyapps.io/AorticAneurysm/上进行评估。