{Reference Type}: Journal Article
{Title}: Development and external validation of a model to predict multidrug-resistant bacterial infections in patients with cirrhosis.
{Author}: Marciano S;Piano S;Singh V;Caraceni P;Maiwall R;Alessandria C;Fernandez J;Kim DJ;Kim SE;Soares E;Marino M;Vorobioff J;Merli M;Elkrief L;Vargas V;Krag A;Singh S;Elizondo M;Anders MM;Dirchwolf M;Mendizabal M;Lesmana CRA;Toledo C;Wong F;Durand F;Gadano A;Giunta DH;Angeli P; ;
{Journal}: Liver Int
{Volume}: 0
{Issue}: 0
{Year}: 2024 Aug 15
{Factor}: 8.754
{DOI}: 10.1111/liv.16063
{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.
METHODS: We included patients with cirrhosis and bacterial infections from two prospective studies: a transcontinental study was used for model development and internal validation (nā=ā1302), and a study from Argentina and Uruguay was used for external validation (nā=ā472). 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.
RESULTS: The 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%).
CONCLUSIONS: This model achieved adequate performance and could be used to improve the selection of empiric antibiotics, aligning with other antibiotic stewardship program strategies.