Albumin corrected anion gap for predicting in-hospital death among patients with acute myocardial infarction: A retrospective cohort study.

IF 2.4 4区 医学 Q2 MEDICINE, GENERAL & INTERNAL Clinics Pub Date : 2024-07-29 eCollection Date: 2024-01-01 DOI:10.1016/j.clinsp.2024.100455
Zhouzhou Lu, Yiren Yao, Yangyang Xu, Xin Zhang, Jing Wang
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Abstract

Objective: To explore the relationship between Anion Gap (AG), Albumin Corrected AG (ACAG), and in-hospital mortality of Acute Myocardial Infarction (AMI) patients and develop a prediction model for predicting the mortality in AMI patients.

Methods: This was a retrospective cohort study based on the Medical Information Mart for Intensive Care (MIMIC)-Ⅲ, MIMIC-IV, and eICU Collaborative Study Database (eICU). A total of 9767 AMI patients who were admitted to the intensive care unit were included. The authors employed univariate and multivariable cox proportional hazards analyses to investigate the association between AG, ACAG, and in-hospital mortality; p < 0.05 was considered statistically significant. A nomogram incorporating ACAG and clinical indicators was developed and validated for predicting mortality among AMI patients.

Results: Both ACAG and AG exhibited a significant association with an elevated risk of in-hospital mortality in AMI patients. The C-index of ACAG (C-index = 0.606) was significantly higher than AG (C-index = 0.589). A nomogram (ACAG combined model) was developed to predict the in-hospital mortality for AMI patients. The nomogram demonstrated a good predictive performance by Area Under the Curve (AUC) of 0.763 in the training set, 0.744 and 0.681 in the external validation cohort. The C-index of the nomogram was 0.759 in the training set, 0.756 and 0.762 in the validation cohorts. Additionally, the C-index of the nomogram was obviously higher than the ACAG and age shock index in three databases.

Conclusion: ACAG was related to in-hospital mortality among AMI patients. The authors developed a nomogram incorporating ACAG and clinical indicators, demonstrating good performance for predicting in-hospital mortality of AMI patients.

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预测急性心肌梗死患者院内死亡的白蛋白校正阴离子间隙:一项回顾性队列研究
目的探讨阴离子间隙(AG)、白蛋白校正AG(ACAG)与急性心肌梗死(AMI)患者院内死亡率之间的关系,并建立预测AMI患者死亡率的预测模型:这是一项基于重症监护医学信息市场(MIMIC)-Ⅲ、MIMIC-Ⅳ和eICU合作研究数据库(eICU)的回顾性队列研究。共纳入了9767名入住重症监护室的AMI患者。作者采用单变量和多变量cox比例危险度分析来研究AG、ACAG和院内死亡率之间的关系;P<0.05为有统计学意义。结果显示,ACAG和AG在预测AMI患者死亡率方面均表现出明显的相关性:结果:ACAG和AG均与AMI患者院内死亡风险升高有显著关联。ACAG 的 C 指数(C 指数 = 0.606)明显高于 AG(C 指数 = 0.589)。我们建立了一个提名图(ACAG 组合模型)来预测 AMI 患者的院内死亡率。训练集的曲线下面积(AUC)为 0.763,外部验证队列的曲线下面积(AUC)为 0.744,外部验证队列的曲线下面积(AUC)为 0.681,显示了该提名图具有良好的预测性能。提名图的 C 指数在训练集中为 0.759,在验证队列中为 0.756 和 0.762。此外,在三个数据库中,提名图的C指数明显高于ACAG和年龄休克指数:ACAG与AMI患者的院内死亡率有关。作者开发的提名图结合了 ACAG 和临床指标,在预测 AMI 患者院内死亡率方面表现良好。
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来源期刊
Clinics
Clinics 医学-医学:内科
CiteScore
4.10
自引率
3.70%
发文量
129
审稿时长
52 days
期刊介绍: CLINICS is an electronic journal that publishes peer-reviewed articles in continuous flow, of interest to clinicians and researchers in the medical sciences. CLINICS complies with the policies of funding agencies which request or require deposition of the published articles that they fund into publicly available databases. CLINICS supports the position of the International Committee of Medical Journal Editors (ICMJE) on trial registration.
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