Association between anion gap and the 30-day mortality of patients with ventilator-associated pneumonia: a study of the MIMIC-III database

Abstract

Background: Serum anion gap (AG) can potentially be applied to the diagnosis of various metabolic acidosis, and a recent study has reported the association of AG with the mortality of patients with coronavirus disease 2019 (COVID-19). However, the relationship of AG with the short-term mortality of patients with ventilator-associated pneumonia (VAP) is still unclear. Herein, we aimed to investigate the association between AG and the 30-day mortality of VAP patients, and construct and assess a multivariate predictive model for the 30-day mortality risk of VAP.

Methods: This retrospective cohort study extracted data of 477 patients with VAP from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Data of patients were divided into a training set and a testing set with a ratio of 7:3. In the training set, variables significantly associated with the 30-day mortality of VAP patients were included in the multivariate predictive model through univariate Cox regression and stepwise regression analyses. Then, the predictive performance of the multivariate predictive model was assessed in both training set and testing set, and compared with the single AG and other scoring systems including the Sequential Organ Failure Assessment (SOFA) score, the confusion, urea, respiratory rate (RR), blood pressure, and age (≥65 years old) (CURB-65) score, and the blood urea nitrogen (BUN), altered mental status, pulse, and age (>65 years old) (BAP-65) score. In addition, the association of AG with the 30-day mortality of VAP patients was explored in subgroups of gender, age, and infection status. The evaluation indexes were hazard ratios (HRs), C-index, and 95% confidence intervals (CIs).

Results: A total of 70 patients died within 30 days. The multivariate predictive model consisted of AG (HR =1.052, 95% CI: 1.008-1.098), age (HR =1.037, 95% CI: 1.019-1.055), duration of mechanical ventilation (HR =0.998, 95% CI: 0.996-0.999), and vasopressors use (HR =1.795, 95% CI: 1.066-3.023). In both training set (C-index =0.725, 95% CI: 0.670-0.780) and testing set (C-index =0.717, 95% CI: 0.637-0.797), the multivariate model had a relatively superior predictive performance to the single AG value. Moreover, the association of AG with the 30-day mortality was also found in patients who were male (HR =1.088, 95% CI: 1.029-1.150), and whatever the pathogens they infected (bacterial infection: HR =1.059, 95% CI: 1.011-1.109; fungal infection: HR =1.057, 95% CI: 1.002-1.115).

Conclusions: The AG-related multivariate model had a potential predictive value for the 30-day mortality of patients with VAP. These findings may provide some references for further exploration on simple and robust predictors of the short-term mortality risk of VAP, which may further help clinicians to identify patients with high risk of mortality in an early stage in the intensive care units (ICUs).

Keywords: 30-day mortality; Anion gap (AG); Medical Information Mart for Intensive Care III database (MIMIC-III database); ventilator-associated pneumonia (VAP).

Figure 1

Flowchart of data filtering in VAP patients form database. VAP, ventilator-associated pneumonia; MIMIC-III, Medical Information Mart for Intensive Care III; ICU, intensive care unit; AG, anion gap.

Figure 2

The decision curves of different scoring systems. BAP-65, blood urea nitrogen, altered mental status, pulse, and age (>65 years old); CURB-65, confusion, urea, respiratory rate, blood pressure, and age (≥65 years old); SOFA, Sequential Organ Failure Assessment; AG, anion gap.