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血清阴离子间隙水平预测脓毒症患者的全因死亡率:基于 MIMIC III 数据库的回顾性研究。

Serum Anion Gap Level Predicts All-Cause Mortality in Septic Patients: A Retrospective Study Based on the MIMIC III Database.

机构信息

Department of Neonatology and Pediatrics, The First Affiliated Hospital of Jinan University, Guangzhou, China.

International School, 47885Jinan University, Guangzhou, China.

出版信息

J Intensive Care Med. 2023 Apr;38(4):349-357. doi: 10.1177/08850666221123483. Epub 2022 Sep 6.

Abstract

PURPOSE

Sepsis is a significant threat in the intensive care unit (ICU) worldwide because it has high morbidity and mortality rates. Early recognition and diagnosis of sepsis are essential for the prevention of adverse outcomes. The present study aimed to quantitatively assess the association between serum anion gap (AG) levels and 30- and 90-day all-cause mortality among sepsis patients.

METHODS

Clinical data of patients diagnosed with sepsis were extracted from the Medical Information Mart for Intensive Care III (MIMIC III) database. Kaplan-Meier curves and Cox proportional hazards models were used to evaluate the association between serum AG levels and all-cause mortality. A receiver operating characteristic (ROC) curve was drawn to quantify the efficacy of using the serum AG level to predict all-cause mortality.

RESULTS

A total of 3811 patients were included in the study. The Kaplan-Meier curves showed that patients with higher serum AG levels had a shorter survival time than those with lower levels. Serum AG levels were found to be highly effective in predicting all-cause mortality secondary to sepsis (30-day: AUROC = 0.703; 90-day: AUROC = 0.696). The Cox regression model further indicated that the serum AG level was an independent risk factor for 30- and 90-day mortality in sepsis (HR 3.44, 95% CI 2.97-3.99 for 30-day; HR 3.17, 95% CI 2.76-3.65 for 90-day, P < 0.001 for both).

CONCLUSIONS

High serum AG may be considered as an alternative parameter for predicting the death risk in sepsis when other variables are not immediately available. Prospective large-scale studies are needed to support its predictive value in the clinic.

摘要

目的

脓毒症是全球重症监护病房(ICU)的重大威胁,因为它具有高发病率和死亡率。早期识别和诊断脓毒症对于预防不良结局至关重要。本研究旨在定量评估血清阴离子间隙(AG)水平与脓毒症患者 30 天和 90 天全因死亡率之间的关系。

方法

从医疗信息集市重症监护 III (MIMIC III)数据库中提取诊断为脓毒症的患者的临床数据。使用 Kaplan-Meier 曲线和 Cox 比例风险模型评估血清 AG 水平与全因死亡率之间的关系。绘制受试者工作特征(ROC)曲线来量化使用血清 AG 水平预测全因死亡率的效果。

结果

共有 3811 名患者纳入研究。Kaplan-Meier 曲线显示,血清 AG 水平较高的患者生存时间短于血清 AG 水平较低的患者。血清 AG 水平在预测脓毒症继发全因死亡率方面非常有效(30 天:AUROC=0.703;90 天:AUROC=0.696)。Cox 回归模型进一步表明,血清 AG 水平是脓毒症 30 天和 90 天死亡率的独立危险因素(30 天:HR 3.44,95%CI 2.97-3.99;90 天:HR 3.17,95%CI 2.76-3.65,均 P<0.001)。

结论

在其他变量无法立即获得时,高血清 AG 可能被视为预测脓毒症死亡风险的替代参数。需要进行前瞻性大规模研究来支持其在临床上的预测价值。

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