Coexistence of Carbapenem Resistance Genes, Biofilm Formation, and Virulence Determinants in Clinical Klebsiella pneumoniae: A Systematic Review and Meta-Analysis

Vollständiger Abstract

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Carbapenem-resistant Klebsiella pneumoniae is a major clinical threat whose persistence may be reinforced by biofilm formation and virulence determinants. This systematic review and meta-analysis assessed population-level coexistence and isolate-level associations among carbapenem resistance, biofilm formation, and selected virulence markers in clinical K. pneumoniae. PubMed/MEDLINE, PubMed Central, publisher databases, and reference lists were searched from inception to 11 July 2026. Eligible studies examined human clinical K. pneumoniae isolates and reported carbapenem resistance or carbapenemase status together with biofilm phenotypes and/or virulence determinants. Random-effects meta-analysis was used for biofilm prevalence and comparable resistance-biofilm associations, with heterogeneity, 95% prediction intervals, and leave-one-out sensitivity analyses assessed. Twelve clinical cohorts comprising 1,504 isolate-associated cases were included. Eight cohorts (1,127 isolates) contributed to the prevalence analysis, with 930 biofilm producers. The pooled prevalence of any biofilm formation was 81.1% (95% CI 74.0-86.6%; I²=76.5%), and the 95% prediction interval was 61.3-92.1%. Three comparable studies yielded a pooled odds ratio of 4.09 (95% CI 1.29-12.97; I²=56.2%) for resistance-associated biofilm formation; however, the prediction interval (0.64-26.12) crossed 1. Carbapenem resistance, biofilm formation, and virulence determinants commonly coexist, but their isolate-level relationships are heterogeneous and context-dependent. This article advances the field by separating community-level associations of resistance, biofilm, and virulence from isolate-level effects. From a clinical point of view, the data add more fuel to decisions regarding vigilant source control and device management, and that biofilm state cannot be used to predict outcome.