Value of strong ion gap for predicting acute heart failure after acute myocardial infarction
10.3760/cma.j.issn.1671-0282.2019.01.015
- VernacularTitle:强离子隙对急性心肌梗死发生急性心力衰竭的预测价值
- Author:
Hongbing ZHANG
1
;
Chonghui JIANG
;
Peng YANG
;
Shiqi LU
;
Yi LI
Author Information
1. 广东中山火炬开发区医院急诊科
- Keywords:
Acute myocardial infarction;
Acute heart failure;
Strong ion gap;
Prediction
- From:
Chinese Journal of Emergency Medicine
2019;28(1):79-83
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the value of strong ion gap (SIG) for predicting acute heart failure (AHF) after acute myocardial infarction. Methods A total of 189 patients with acute myocardial infarction were enrolled from July 2015 to December 2016 in the First Affiliated Hospital of Soochow University. Based on AHF occurrence, the patients were divided into the AHF group (n=76) and the non-AHF group (n=113). General clinical data and laboratory tests were compared between the two groups. The univariate analysis and multivariate logistic regression analysis were performed to estimate the contribution of clinical risk factors to triggering AHF after acute myocardial infarction. Spearman correlation analysis was performed to estimate the correlation between SIG and Killip classification. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive value of ALB, anion gap (AG) and SIG in AHF after acute myocardial infarction. Results Age, proportion of history of diabetes, the serum level of C-reactive protein (CRP), AG and SIG of the AHF group were higher than those of the non-AHF group (P<0.05). Meanwhile, the serum level of albumin (ALB) of the AHF group were lower than those of the non-AHF group (P<0.05). Univariate analysis showed AHF after acute myocardial infarction was closely associated with age, history of diabetes, serum ALB, AG and SIG (P<0.05). Multivariate logistic regression analysis showed that history of diabetes (OR=2.034, 95％CI:1.075-4.113, P<0.05) and SIG (OR=2.445, 95％CI: 1.538-4.297, P<0.05) were significantly correlated with AHF after acute myocardial infarction. The ROC analysis revealed SIG (AUC=0.837,95％CI:0.781-0.893) had a large area under curve compared to ALB (AUC=0.671,95％CI: 0.593-0.750) and AG (AUC=0.728,95％CI: 0.654-0.802). The optimal diagnostic intercept value was 5.24 mmol/L, and the sensitivity and specificity were 76.32％ and 78.36％, respectively. Conclusions SIG could be used as an independent predictor for AHF secondary to acute myocardial infarction, and was significantly correlated with severity of AHF.
