Association between triglyceride glucose index and all-cause mortality in patients with critical atrial fibrillation in the MIMIC-IV database.

Although several studies have demonstrated the relationship between the triglyceride glucose (TyG) index and the prevalence of atrial fibrillation (AF), more attention needs to be paid to patients with AF in intensive care units because the prevalence of AF is as high as one-third of the population. This study investigated the relationship between the TyG index and short-term prognosis in patients with critical care AF. We selected critically ill patients with AF from the MIMIC-IV database and categorized them into quartiles based on their TyG index levels. The primary outcome assessed was 30-day all-cause mortality, with secondary outcomes of 7-day and 15-day all-cause mortality. We utilized Kaplan-Meier survival curves, restricted cubic spline, and Cox proportional hazards regression models to illustrate the relationship between the TyG index and clinical outcomes in critically ill patients with AF. 1,146 critically ill patients with AF were included in this study, with a mean age of 75.90. The female population accounted for 48.43% of the total. Kaplan-Meier survival curves demonstrated a significant association between the TyG index and all-cause mortality at 7, 15, and 30 days. Cox proportional hazards analysis, after adjusting for multiple confounders, revealed a substantial increase in all-cause mortality in the fourth quartile of the TyG index compared to the first quartile (HR = 1.71, 95% CI: 1.17-2.49). Restricted cubic spline further illustrated that higher TyG index were associated with an elevated risk of all-cause mortality in critically ill patients with AF. The stratified analysis provided additional support for the robustness of this association. The TyG index demonstrated a significant association with 7-day, 15-day, and 30-day all-cause mortality in critically ill patients with AF. These findings suggest that the TyG index may serve as a useful tool in identifying AF patients at a higher risk of all-cause mortality, enabling early and effective intervention strategies.