ArticleJournal of thoracic disease2026
Association between albumin-corrected anion gap and in-hospital mortality in ICU patients with lung cancer: a retrospective cohort study based on the MIMIC database.
Article in Journal of thoracic disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.