Metabolic acidosis is a frequent acid-base imbalance in critically ill patients and is often associated with poor prognosis. This study aimed to evaluate the prognostic value of the albumin-corrected anion gap (ACAG) in predicting poor prognosis among diabetic patients with severe acute myocardial infarction (AMI).

A retrospective analysis was conducted using clinical data from 1,181 patients with AMI and comorbid diabetes mellitus, sourced from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database in the United States. Patients were classified into survival and non-survival groups based on intensive care unit (ICU) outcomes and further stratified into quartiles according to ACAG levels. Kaplan–Meier survival analysis and log-rank tests were used to assess the association between ACAG and short-term (7-day) and long-term mortality. Cox proportional hazard models were applied to evaluate the independent prognostic value of ACAG. Restricted cubic spline (RCS) analysis was used to visualize the non-linear relationship between ACAG and all-cause mortality in ICU and in-hospital settings. A nomogram prediction model incorporating ACAG was also constructed and validated.

Among the 1,181 enrolled patients (61.05% male), the in-hospital and ICU mortality rates were 22.10% and 15.16%, respectively. Patients with ACAG values >18.75 had significantly higher mortality compared to those with values <15.75. After adjustment for potential confounders, elevated ACAG remained independently associated with an increased risk of death. RCS analysis revealed a positive linear association between ACAG levels and in-hospital and ICU mortality. Based on these findings, a nomogram prediction model incorporating ACAG was developed to estimate mortality risk in diabetic patients with acute AMI.

ACAG was significantly associated with both in-hospital and ICU all-cause mortality in diabetic patients with severe AMI. These findings suggest that ACAG may be a valuable prognostic biomarker for identifying high-risk individuals in this critically ill population.