Clinical prediction models for ESBL-Enterobacteriaceae colonization or infection: a systematic review.

Background: β-Lactamase resistance among certain Gram-negative bacteria has been associated with increased mortality, length of hospitalization, and hospital costs.

Aim: To identify and critically appraise existing clinical prediction models of extended-spectrum β-lactamase-producing Enterobacteriaceae (ESBL-EKP) infection or colonization.

Methods: Electronic databases, reference lists, and citations were searched from inception to April 2018. Papers were included in any language describing the development or validation, or both, of models and scores to predict the risk of ESBL-EKP infection or colonization.

Findings: In all, 1795 references were screened, of which four articles were included in the review. The included studies were carried out in different geographical locations with differing study designs, and inclusion and exclusion criteria. Most if not all studies lacked external validation and blinding of reviewers during the evaluation of the predictor variables and outcome. All studies excluded missing data and most studies did not report the number of patients excluded due to missing data. Fifteen predictors of infection or colonization with ESBL-EKP were identified. Commonly included predictors were previous antibiotic use, previous hospitalization, transfer from another healthcare facility, and previous procedures (urinary catheterization and invasive procedures).

Conclusion: Due to limitations and variations in the study design, clinicians would have to take these differences into consideration when deciding on how to use these models in clinical practice. Due to lack of external validation, the generalizability of these models remains a question. Therefore, further external validation in local settings is needed to confirm the usefulness of these models in supporting decision-making.