Abstract
BACKGROUND: This retrospective cohort study investigates the association between albumin-corrected anion gap (ACAG) and in-hospital mortality (IHM) among critically ill patients with lung cancer (LC). METHODS: ACAG was calculated using the formula: ACAG (mmol/L) = anion gap (mmol/L) + [4.4 - albumin (g/dL)] × 2.5, based on the first laboratory measurement within 72 hours of ICU admission. Data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, including 458 LC patients admitted to the intensive care unit (ICU). These patients were stratified by IHM status and ACAG levels into T1, T2, and T3 groups. Key variables were selected using cross-validated least absolute shrinkage and selection operator (LASSO) regression, and multivariable Cox proportional hazards models were employed to assess the relationship between ACAG and IHM. Restricted cubic spline (RCS) models were used to evaluate potential non-linear dose-response relationships. RESULTS: Results showed that higher ACAG levels were significantly associated with an increased risk of IHM when treated as a continuous variable [model 3: hazard ratio (HR) =1.077, 95% confidence interval (CI): 1.032-1.123, P<0.001]. RCS analysis revealed a linear association between rising ACAG levels and increased risk of all-cause IHM (model 3: P for non-linearity =0.506). Kaplan-Meier survival curves indicated better cumulative survival in the low-ACAG group compared to the high-ACAG group. Subgroup analyses demonstrated consistent effects across various subgroups, with no significant interactions between ACAG and other covariates. Sensitivity analyses confirmed the robustness of the findings. CONCLUSIONS: In conclusion, elevated ACAG is independently associated with a higher risk of IHM in LC patients admitted to the ICU, suggesting its potential utility as a prognostic biomarker in this population. Clinically, integrating ACAG into routine ICU assessments may facilitate the early identification of high-risk patients, enabling more personalized metabolic monitoring and timely therapeutic interventions. These findings highlight the importance of acid-base and metabolic parameters in risk stratification for LC patients admitted to the ICU.