Serum anion gap at admission predicts all-cause mortality in critically ill patients with cerebral infarction: evidence from the MIMIC-III database

Biomarkers. 2020 Dec;25(8):725-732. doi: 10.1080/1354750X.2020.1842497. Epub 2020 Nov 10.

Abstract

Background: Recent studies reported that serum anion gap could be regarded as a prognostic biomarker for patients admitted to intensive care units. However, the association between AG and mortality in cerebral infarction patients remained largely unknown.

Methods: Relevant clinical data were collected from Medical Information Mart for Intensive Care III. Patients were divided into three groups according to tertiles of AG. Kaplan-Meier curve and Cox proportional hazards models were used to evaluate the association between AG levels and all-cause mortality. Subgroup analyses were performed to verify the predictive role of AG on mortality.

Results: Kaplan-Meier analysis showed that patients with higher AG had shorter survival time. Cox regression model indicated high AG as an independent risk factor of 30-day, 60-day and 180-day all-cause mortality (30-day: HR = 2.45, 95% CI = 1.21-4.97, 60-day: HR = 2.04, 95% CI = 1.07-3.89, and 180-day: HR = 1.85, 95% CI = 1.02-3.36). However, no significance was observed between AG and 365-day all-cause mortality (HR = 1.56, 95% CI = 0.87-2.78).

Conclusions: High AG was associated with increased risk of all-cause mortality, and AG could be an independent short-term prognostic factor for cerebral infarction.

Keywords: Biomarker; MIMIC-III; anion gap; cerebral infarction; intensive care units; mortality.

MeSH terms

  • Acid-Base Equilibrium*
  • Aged
  • Aged, 80 and over
  • Biomarkers / blood
  • Cerebral Infarction / blood*
  • Cerebral Infarction / diagnosis
  • Cerebral Infarction / mortality
  • Cerebral Infarction / physiopathology
  • Critical Illness
  • Databases, Factual
  • Female
  • Humans
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Prognosis
  • Retrospective Studies
  • Risk Assessment
  • Risk Factors
  • Time Factors

Substances

  • Biomarkers