Development and Validation of Nosocomial Bacterial Infection Prediction Models for Patients With Systemic Lupus Erythematosus

Author:

Restrepo Escobar MauricioORCID,Jaimes Barragán Fabián1,Vásquez Duque Gloria María2,Aguirre Acevedo Daniel Camilo1,Peñaranda Parada Édgar Alfonso3,Prieto-Alvarado Johana4,Mesa-Navas Miguel Antonio5,Calle-Botero Estefanía6,Arbeláez-Cortés Álvaro7,Velásquez-Franco Carlos Jaime8,Vergara-Serpa Óscar8,Del-Castillo-Gil David Julián,Gordillo-González Camilo Andrés9,Guzmán-Naranjo Luis Carlos10,Granda-Carvajal Paula Andrea11,Jaramillo-Arroyave Daniel12,Muñoz-Vahos Carlos Horacio,Vélez-Marín Mariana13,Hernández-Zapata Johanna2,Eraso-Garnica Ruth,Vanegas-García Adriana Lucía,González-Naranjo Luis Alonso2

Affiliation:

1. Grupo Académico de Epidemiología Clínica (GRAEPIC), Universidad de Antioquia, Medellín, Colombia

2. Grupo de Reumatología de la Universidad de Antioquia (GRUA), Universidad de Antioquia, Medellín, Colombia

3. Universidad Nacional de Colombia, Reumatólogo Clínica Colsanitas, Santafé de Bogotá, Bogotá, Colombia

4. Clínica Colsubsidio Calle 100, Santafé de Bogotá, Bogotá, Colombia

5. Clínica el Rosario, Líder Área de Investigación En Reumatología SURA, Medellín, Colombia

6. Clínica SOMER, Rionegro, Antioquia, Colombia

7. Clínica IMBANACO, Cali, Colombia

8. Clínica Universitaria Bolivariana, Medellín, Colombia

9. Universidad del Valle, Cali, Colombia

10. Hospital Serena del Mar, Cartagena, Colombia

11. Servicios de Salud Suramericana, Medellín, Colombia

12. Universidad CES, Medellín, Colombia

13. EPS SURA, Medellín, Colombia

Abstract

Background Hospital-acquired bacterial infections are associated with high morbidity and mortality rates in patients with systemic lupus erythematosus (SLE). This study aimed to develop and validate predictive models for the risk of hospital-acquired bacterial infections in patients with SLE. Methods A historical cohort study was designed for development, and another bidirectional cohort study was used for external validation. The risk of bacterial infection was assessed upon admission and after 5 days of hospitalization. Predictor selection employed the least absolute shrinkage and selection operator (LASSO) techniques. Multiple imputations were used to handle missing data. Logistic regression models were applied, and the properties of discrimination, calibration, and decision curve analysis were evaluated. Results The development cohort comprised 1686 patients and 237 events (14.1%) from 3 tertiary hospitals. The external validation cohort included 531 patients and 84 infection outcomes (15.8%) from 10 hospital centers in Colombia (secondary and tertiary level). The models applied at admission and after 120 hours of stay exhibited good discrimination (AUC > 0.74). External validation demonstrated good performance among patients from the same tertiary institutions where the models were developed. However, geographic validation at other institutions has been suboptimal. Conclusions Two predictive models for nosocomial bacterial infections in patients with SLE are presented. All infection prevention recommendations should be maximized in patients at moderate/high risk. Further validation studies in diverse contexts, as well as clinical impact trials, are necessary before potential applications in research and clinical care.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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