open access publication

Article, 2024

OP-4 DEVELOPMENT AND EXTERNAL VALIDATION OF A MODEL TO PREDICT MULTI-DRUG RESISTANT BACTERIAL INFECTIONS IN PATIENTS WITH CIRRHOSIS

Annals of Hepatology, ISSN 2659-5982, 1665-2681, Volume 29, Page 101277, 10.1016/j.aohep.2023.101277

Contributors

Marciano, Sebastián 0000-0002-7983-1450 [1] Piano, Salvatore [2] Singh, Virendra 0000-0002-9113-5167 [3] Caraceni, Paolo [4] Maiwall, Rakhi [5] Alessandria, Carlo [6] Fernandez, Javier [7] Kim, Dong Joon [8] Kim, Sung Eun [9] Soares, Elza Cotrim [10] Marino, Monica [11] Vorobioff, Julio Daniel [12] Merli, Manuela [13] Elkrief, Laure 0000-0003-2843-1710 [14] Vargas, Victor [15] Krag, Aleksander Ahm 0000-0002-9598-4932 [16] Singh, Shivaram Prasad 0000-0002-8197-2674 [17] Giunta, Diego Hernán 0000-0002-8427-6033 [1] Elizondo, Martin [18] Anders, Maria Margarita [19] Dirchwolf, Melisa [20] Mendizabal, Manuel 0000-0002-7026-9908 [21] Lesmana, Cosmas Rinaldi Adithya [22] Toledo, Claudio [23] Wong, Florence [24] Durand, Francois [25] Gadano, Adrian Carlos [1] Angeli, Paolo [2]

Affiliations

  1. [1] Hospital Italiano de Buenos Aires
    2. [NORA names: Argentina; America, South];
  2. [2] University of Padua
    3. [NORA names: Italy; Europe, EU; OECD];
  3. [3] Post Graduate Institute of Medical Education and Research
    4. [NORA names: India; Asia, South];
  4. [4] University of Bologna
    5. [NORA names: Italy; Europe, EU; OECD];
  5. [5] Institute of Liver and Biliary Sciences
    6. [NORA names: India; Asia, South];

Abstract

Introduction and Objectives Empirical antibiotic treatment for suspected infections in cirrhosis is crucial. This study aimed to develop and validate a model to predict the probability of infections by multi-drug resistant organisms (MDRO) in patients with cirrhosis. Materials and Methods Cross-sectional study (NCT05641025) of in-patients with bacterial infections from two prospective studies. A global transcontinental study was used for model development and internal validation (n = 1,302), and a study from Argentina and Uruguay (n=472) was used for external validation. Infection by MDROs was defined as an infection caused by at least one bacteria with acquired resistance to at least one antibiotic of three different families. A stepwise selection process was used for model development and bootstrapping for internal validation. Results The prevalence of infection by MDROs was 19% in the development and 22% in the external validation dataset. Most frequent infections were spontaneous bacterial peritonitis (SBP) and urinary tract infection (UTI). Half of the infections were community-acquired, and half were equally distributed among healthcare-associated and nosocomial origin. The model predictors are shown in the figure. Very good calibration was achieved in internal and external validation (Figure). Discrimination was adequate: area under the receiver operating characteristic curve (AUROC) of 0.73 (95% CI: 0.69 - 0.76) in internal validation and 0.67 (95% CI: 0.62 - 0.74) in external validation. When applying a probability cut-off point of 5% to the external dataset, a negative predictive value (NPV) of 93% (95% CI: 84% - 98%) was observed. Conclusions This easy-to-implement model achieved adequate performance for predicting infections by MDROs in patients with cirrhosis, offering costless bedside individualized risk estimates that might improve the selection of empiric antibiotics. Its high NPV suggests that it could be used as a rule-out tool, particularly in patients at higher risk of infection by MDROs, reducing the use of broad- spectrum antibiotics.

Keywords

Argentina, Method Cross-sectional study, Uruguay, adequate performance, antibiotic treatment, antibiotics, area, area under the receiver operating characteristic curve, bacteria, bacterial infections, bacterial peritonitis, bedside, broad-spectrum antibiotics, calibration, characteristic curve, cirrhosis, community-acquired, cross-sectional study, curves, cut-off point, dataset, development, discrimination, easy-to-implement model, empirical antibiotic treatment, empirical antibiotics, estimation, external datasets, external validation, external validation dataset, family, figures, frequent infections, half, healthcare-associated, high risk, high risk of infection, in-patients, individual risk estimates, infection, internal validity, materials, method, model, model development, model predictors, multi-drug resistant bacterial infections, multi-drug resistant organisms, negative predictive value, nosocomial origin, organization, origin, patients, performance, peritonitis, point, predicting infection, prediction, predictive value, predictors, prevalence, prevalence of infection, probability, probability cut-off points, probability of infection, process, prospective study, receiver operating characteristic curve, resistance, resistant organisms, risk estimates, risk of infection, rule-out tool, selection, selection of empirical antibiotics, selection process, spectrum antibiotics, spontaneous bacterial peritonitis, study, suspected infection, tools, tract infections, transcontinental study, treatment, urinary tract infection, validation dataset, validity, values

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