Mortality due to carbapenem-resistant Acinetobacter baumannii bacteraemia: a five-year cohort study in intensive care patients

2025-02-20

Our latest research was published in the top-tier journal Clinical Microbiology and Infection (European Society of Clinical Microbiology and Infectious Diseases), on February 17, 2025.

Mortality due to carbapenem-resistant Acinetobacter baumannii bacteraemia: a five-year cohort study in intensive care patients

Stamatis Karakonstantis, Evangelos I. Kritsotakis, Renatos-Nikolaos Tziolos, Loukia Vassilopoulou, Maria Loukaki, Despoina Kypraiou, Emmanouil C. Petrakis, Alberto Tovil, Sophia Kokkini, Kyriaki Tryfinopoulou, Petros Ioannou, Εumorfia Kondili, Diamantis P. Kofteridis

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https://doi.org/10.1016/j.cmi.2025.02.018

Abstract

Objectives:

Carbapenem-resistant Acinetobacter baumannii (CRAB) has emerged as a major and difficult-to-treat nosocomial pathogen. This study estimated the mortality associated with CRAB bacteraemia in patients receiving treatment in the intensive care unit. A susceptible-infection counterfactual framework was applied to reflect the potential benefit of improved antimicrobial therapy.

Methods:

A five-year (2019-2023) cohort study was conducted in a tertiary-care referral hospital in Greece. Competing risks survival analysis methods were applied to estimate excess in-hospital mortality due to CRAB bacteraemia by comparing patients infected by CRAB to those infected by other more susceptible Gram-negative bacteria (GNB).

Results:

The cohort comprised 400 intensive care patients with GNB bacteraemia (median age 70 years, 65% male). CRAB was the most common pathogen (43%), followed by K. pneumoniae (12%), E. coli (11%), and P. aeruginosa (10%). Patients with CRAB bacteraemia experienced significantly higher in-hospital mortality at 14 days (35% vs. 21%), 28 days (53% vs. 30%) and overall (74% vs. 52%) compared to patients with other GNB bacteraemia. Multivariable competing-risks regression confirmed that CRAB bacteraemia was independently associated with increased risk of 28-day inpatient death (cause-specific hazard ratio [csHR] 1.80, 95% CI 1.28–2.54; sub-distribution hazard ratio [sHR] 1.84, 95% CI 1.28–2.62), simultaneously lowering the probability of discharge alive (csHR 0.68, 95% CI 0.38–1.21; sHR 0.52, 95% CI 0.30–0.91). Estimation of the attributable fraction suggested that effective antimicrobial management may result in a relative decrease in the risk of in-hospital mortality by 44% (95% CI 22%–61%) in CRAB bacteraemia patients.

Conclusions:

CRAB's detrimental role as a leading cause of increased inpatient mortality and prolongation of hospitalisation in intensive-care patients was demonstrated. These outcomes could improve substantially if more effective antimicrobial treatment becomes available. Nevertheless, considering CRAB is predominantly a hospital-acquired pathogen, efforts should always be directed towards preventing nosocomial transmission.

Keywords: Carbapenem resistance; intensive care; bloodstream infection; Acinetobacter baumannii; survival analysis

Figure: Cumulative incidence plot of inpatient death and hospital discharge alive for N = 400 ICU patients with carbapenem-resistant A. baumannii (CRAB) bacteraemia versus other bacteraemia.

Figure: Cumulative incidence plot of inpatient death and hospital discharge alive for N = 400 ICU patients with bacteraemia caused by carbapenem-resistant A. baumannii (CRAB) versus bacteraemia by other pathogens.

Table: Sensitivity analyses of the effect of CRAB bacteraemia on the 28-day in-hospital outcome under various restrictive conditions

Figure: Sample sizes required for Cox proportional hazards regression to detect hazard ratios of inpatient death between 1.3 to 2.0 for the binary exposure of interest (CRAB bacteraemia), with power 1-β = 90%, significance level α = 0.05, assumed censoring rate of 30% , and assumed squared multiple-correlation coefficient R^2 =0.20 when adjusting for covariates (equivalent to a variance inflation factor of 1.25, i.e. sample size inflation by 25%). The method of Hsieh and Lavori (2000) was applied. The graph shows that with a sample size of about 400 patients, moderately sized hazard ratios >1.5 can be detected. [reference: Control Clin Trials 2000;21(6):552-60]