SynthesisPloS one2024
Dynamics of serum anion gaps with in-hospital mortality: Analysis of the multi-open databases.
Synthesis in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Anion gap trajectory patterns and prognosis in sepsis patients: A multicenter retrospective study.Medicine · 2026Article
- Predicting ICU mortality in patients with abdominal aortic aneurysm: a nomogram based on MIMIC-IV and eICU-CRD.International journal of medical sciences · 2026Article
- Serum anion gap and its interaction with diabetes in predicting mortality among critically ill patients with non-traumatic intracerebral hemorrhage.European journal of medical research · 2025Article
- Thirty-day mortality risk prediction for geriatric patients undergoing non-cardiac surgery in the surgical intensive care unit.European journal of medical research · 2025Article
- Anion gap associated with 28-days all-cause mortality in Acute cholangitis patients admitted to the intensive care unit in MIMIC-IV database: a retrospective cohort study.Frontiers in medicine · 2025Article
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Authors and funding
6 authors.
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Abstract
backgroundFew studies have investigated the relationship between the anion gap, including the corrected anion gap, and patient mortality in intensive care units (ICUs) without restricting the analysis to specific diseases or medical specialties. Our primary objective was to investigate the association between the anion gap and ICU mortality using multiple open-access databases.
methodsWe identified 4229 subjects from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, whose entries were from between 2008 and 2019. For each patient, the anion gap and corrected anion gap were calculated, and the study sample was divided into tertile groups (T) according to these levels. The association between the anion gap and in-hospital mortality was assessed using hazard ratios (HRs) and 95% confidence intervals (CIs) derived from a multivariable-adjusted Cox proportional hazards model. Besides MIMIC-IV, we also incorporated study samples from two other databases (MIMIC-III and electronic ICU) to calculate summary HRs using a random-effects meta-analysis.
resultsWithin MIMIC-IV, 1015 patients (24%) died during an average follow-up period of 15.5 days. The fully adjusted HRs and 95% CIs for T2 and T3, relative to T1, were 1.31 (95% CI 1.08-1.58) and 1.54 (95% CI 1.24-1.90), respectively. When grouped by corrected anion gap, the results remained statistically significant. In the meta-analysis, the summary HRs and 95% CIs for T2 and T3 were 1.24 (95% CI 1.08-1.43) and 1.55 (95% CI 1.33-1.82), respectively.
conclusionsBoth the anion gap and corrected anion gap were associated with in-hospital mortality regardless of specific diseases or medical specialties.
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