With the increasing rate of infections caused by multidrug-resistant organisms (MDRO), selecting appropriate empiric antibiotics has become challenging. We aimed to develop and externally validate a model for predicting the risk of MDRO infections in patients with cirrhosis.MethodsWe included patients with cirrhosis and bacterial infections from two prospective studies: a transcontinental study was used for model development and internal validation (n = 1302), and a study from Argentina and Uruguay was used for external validation (n = 472). All predictors were measured at the time of infection. Both culture-positive and culture-negative infections were included. The model was developed using logistic regression with backward stepwise predictor selection. We externally validated the optimism-adjusted model using calibration and discrimination statistics and evaluated its clinical utility.ResultsThe prevalence of MDRO infections was 19% and 22% in the development and external validation datasets, respectively. The model's predictors were sex, prior antibiotic use, type and site of infection, MELD-Na, use of vasopressors, acute-on-chronic liver failure, and interaction terms. Upon external validation, the calibration slope was 77 (95% CI .48-1.05), and the area under the ROC curve was .68 (95% CI .61-.73). The application of the model significantly changed the post-test probability of having an MDRO infection, identifying patients with nosocomial infection at very low risk (8%) and patients with community-acquired infections at significant risk (36%).ConclusionThis model achieved adequate performance and could be used to improve the selection of empiric antibiotics, aligning with other antibiotic stewardship program strategies.
Development and external validation of a model to predict multidrug‐resistant bacterial infections in patients with cirrhosis / Marciano, Sebastián; Piano, Salvatore; Singh, Virendra; Caraceni, Paolo; Maiwall, Rakhi; Alessandria, Carlo; Fernandez, Javier; Kim, Dong Joon; Kim, Sung Eun; Soares, Elza; Marino, Mónica; Vorobioff, Julio; Merli, Manuela; Elkrief, Laure; Vargas, Victor; Krag, Aleksander; Singh, Shivaram; Elizondo, Martín; Anders, Maria M; Dirchwolf, Melisa; Mendizabal, Manuel; Lesmana, Cosmas R. A.; Toledo, Claudio; Wong, Florence; Durand, Francois; Gadano, Adrián; Giunta, Diego H; Angeli, Paolo; Null, Null. - In: LIVER INTERNATIONAL. - ISSN 1478-3223. - (2024). [10.1111/liv.16063]
Development and external validation of a model to predict multidrug‐resistant bacterial infections in patients with cirrhosis
Merli, Manuela;
2024
Abstract
With the increasing rate of infections caused by multidrug-resistant organisms (MDRO), selecting appropriate empiric antibiotics has become challenging. We aimed to develop and externally validate a model for predicting the risk of MDRO infections in patients with cirrhosis.MethodsWe included patients with cirrhosis and bacterial infections from two prospective studies: a transcontinental study was used for model development and internal validation (n = 1302), and a study from Argentina and Uruguay was used for external validation (n = 472). All predictors were measured at the time of infection. Both culture-positive and culture-negative infections were included. The model was developed using logistic regression with backward stepwise predictor selection. We externally validated the optimism-adjusted model using calibration and discrimination statistics and evaluated its clinical utility.ResultsThe prevalence of MDRO infections was 19% and 22% in the development and external validation datasets, respectively. The model's predictors were sex, prior antibiotic use, type and site of infection, MELD-Na, use of vasopressors, acute-on-chronic liver failure, and interaction terms. Upon external validation, the calibration slope was 77 (95% CI .48-1.05), and the area under the ROC curve was .68 (95% CI .61-.73). The application of the model significantly changed the post-test probability of having an MDRO infection, identifying patients with nosocomial infection at very low risk (8%) and patients with community-acquired infections at significant risk (36%).ConclusionThis model achieved adequate performance and could be used to improve the selection of empiric antibiotics, aligning with other antibiotic stewardship program strategies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.