Predictive score for patients with carbapenemase-producing enterobacterales colonization upon admission in a tertiary care hospital in an endemic area

• Published in: Journal of antimicrobial chemotherapy 2022-11, Vol.77 (12), p.3331-3339
• Main Authors: Papafotiou, Chrysanthe, Roussos, Sotirios, Sypsa, Vana, Bampali, Sofia, Spyridopoulou, Kalliopi, Karapanou, Amalia, Moussouli, Anastasia, Samarkos, Michael, Daikos, George L, Psichogiou, Mina
• Format: Article
• Language: English
• ISSN: 0305-7453; 1460-2091
• DOI: 10.1093/jac/dkac321

OBJECTIVESCarbapenemase-producing Enterobacterales (CPE) comprise important nosocomial pathogens worldwide. Colonized patients are the source of further dissemination in healthcare settings. Considering that timely detection of CPE carriers is pivotal but universal screening is unfeasible, we aimed to develop and validate a prediction score to detect patients harbouring CPE on hospital admission. METHODSThe study was conducted in a tertiary care hospital located in a CPE endemic area. Rectal swabs were obtained from 2303 patients, screened shortly after hospital admission. The Enterobacterales isolated in cultures were examined for the presence of blaVIM, KPC, NDM, OXA-48 by PCR. Demographic data and patient history of the previous 6 months were recorded. Risk factors for CPE carriage were identified using a multivariable logistic regression model and a points-system risk score was developed. The discriminative ability of the risk score was assessed using the AUC and its predictive performance was validated in a second dataset of 1391 patients in a different time period. RESULTSSeven predictors were identified: previous CPE colonization or infection, prior hospitalization, stay in a long-term health care facility, history of ≥2 interventions, renal replacement therapy, diabetes with end-organ damage and Karnofsky score. The developed risk score in the derivation dataset ranged between 0 and 79 points, with an AUC of 0.84 in the derivation and 0.85 in the validation dataset. CONCLUSIONSThis prediction tool may assist in identifying patients who are at risk of harbouring CPE on hospital admission in an endemic area and guide clinicians to implement prompt and appropriate infection control measures.