Suppr超能文献

急性上消化道出血患者住院死亡率的预测:几种风险评分系统的验证。

Prediction of in-hospital mortality after acute upper gastrointestinal bleeding: cross-validation of several risk scoring systems.

机构信息

Clinic of Gastroenterology and Hepatology, Clinical Center Niš, 18000 Niš, Serbia.

Center of Radiology, Clinical Center Niš, 18000 Niš, Serbia.

出版信息

J Int Med Res. 2022 Mar;50(3):3000605221086442. doi: 10.1177/03000605221086442.

Abstract

OBJECTIVE

We aimed to identify the clinical, biochemical, and endoscopic features associated with in-hospital mortality after acute upper gastrointestinal bleeding (AUGIB), focusing on cross-validation of the Glasgow-Blatchford score (GBS), full Rockall score (RS), and Cedars-Sinai Medical Center Predictive Index (CSMCPI) scoring systems.

METHODS

Our prospective cross-sectional study included 156 patients with AUGIB. Several statistical approaches were used to assess the predictive accuracy of the scoring systems.

RESULTS

All three scoring systems were able to accurately predict in-hospital mortality (area under the receiver operating characteristic curve [AUC] > 0.9); however, the multiple logistic model separated the presence of hemodynamic instability (state of shock) and the CSMCPI as the only significant predictive risk factors. In compliance with the overall results, the CSMCPI was consistently found to be superior to the other two systems (highest AUC, highest sensitivity and specificity, highest positive and negative predictive values, highest positive likelihood ratio, lowest negative likelihood ratio, and 1-unit increase in CSMCPI associated with 6.3 times higher odds of mortality), outperforming the GBS and full RS.

CONCLUSIONS

We suggest consideration of the CSMCPI as a readily available and reliable tool for accurately predicting in-hospital mortality after AUGIB, thus providing an essential backbone in clinical decision-making.

摘要

目的

本研究旨在确定急性上消化道出血(AUGIB)患者住院期间死亡率相关的临床、生化和内镜特征,重点对格拉斯哥-布拉奇福德评分(GBS)、完整的罗克厄尔评分(RS)和雪松西奈医学中心预测指数(CSMCPI)评分系统进行交叉验证。

方法

本前瞻性横断面研究纳入了 156 例 AUGIB 患者。采用多种统计学方法评估评分系统的预测准确性。

结果

三种评分系统均能准确预测住院期间死亡率(接受者操作特征曲线下面积 [AUC]>0.9);然而,多因素逻辑回归模型表明,血流动力学不稳定(休克状态)和 CSMCPI 是唯一具有显著预测价值的风险因素。根据总体结果,CSMCPI 始终优于其他两种系统(最高 AUC、最高敏感性和特异性、最高阳性和阴性预测值、最高阳性似然比、最低阴性似然比,以及 CSMCPI 每增加 1 分,死亡风险增加 6.3 倍),优于 GBS 和完整 RS。

结论

我们建议将 CSMCPI 视为一种易于获得且可靠的工具,用于准确预测 AUGIB 患者住院期间的死亡率,从而为临床决策提供重要依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cad3/8943321/982cb5ec9c44/10.1177_03000605221086442-fig1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验