Development and Validation of a New Score to Assess the Risk of Posttransplantation Diabetes Mellitus in Kidney Transplant Recipients

Author:

Serna-Higuita Lina Maria1,Isaza-López Maria Carolina2ORCID,Hernández-Herrera Gilma Norela2,Serna-Campuzano Angelica Maria3,Nieto-Rios John Fredy23,Heyne Nils456,Guthoff Martina456

Affiliation:

1. Department of Clinical Epidemiology and Applied Biostatistics, University Hospital Tübingen, Germany.

2. Faculty of Medicine, University of Antioquia, Medellín, Colombia.

3. Department of Nephrology, Hospital Pablo Tobón Uribe, Medellín, Colombia.

4. Department of Diabetology, Endocrinology, Nephrology, University of Tübingen, Tübingen, Germany.

5. Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany.

6. German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany.

Abstract

Background. Posttransplantation diabetes mellitus (PTDM) is a serious complication of solid organ transplantation. It is associated with major adverse cardiovascular events, which are a leading cause of morbidity and mortality in transplant patients. This study aimed to develop and validate a score to predict the risk of PTDM in kidney transplant recipients. Methods. A single-center retrospective cohort study was conducted in a tertiary care hospital in Medellín, Colombia, between 2005 and 2019. Data from 727 kidney transplant recipients were used to develop a risk prediction model. Significant predictors with competing risks were identified using time-dependent Cox proportional hazard regression models. To build the prediction model, the score for each variable was weighted using calculated regression coefficients. External validation was performed using independent data, including 198 kidney transplant recipients from Tübingen, Germany. Results. Among the 727 kidney transplant recipients, 122 developed PTDM. The predictive model was based on 5 predictors (age, gender, body mass index, tacrolimus therapy, and transient posttransplantation hyperglycemia) and exhibited good predictive performance (C-index: 0.7 [95% confidence interval, 0.65-0.76]). The risk score, which included 33 patients with PTDM, was used as a validation data set. The results showed good discrimination (C-index: 0.72 [95% confidence interval, 0.62-0.84]). The Brier score and calibration plot demonstrated an acceptable fit capability in external validation. Conclusions. We proposed and validated a prognostic model to predict the risk of PTDM, which performed well in discrimination and calibration, and is a simple score for use and implementation by means of a nomogram for routine clinical application.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Transplantation

Reference48 articles.

1. Analysis of risk factors and establishment of a risk prediction model for post-transplant diabetes mellitus after kidney transplantation.;Cheng;Saudi Pharm J,2022

2. Post-transplant diabetes mellitus and prediabetes in renal transplant recipients: an update.;Rodríguez-Rodríguez;Nephron,2021

3. Post-transplant diabetes mellitus in kidney transplant recipients: a multicenter study.;Malik;Kidney360,2021

4. Ten-year incidence of post-transplant diabetes mellitus in renal transplant patients.;Habibnia;Diab Vasc Dis Res,2022

5. Post-transplant diabetes mellitus in kidney transplant recipients in Sudan: a comparison between tacrolimus and cyclosporine-based immunosuppression.;Yousif;Cureus,2022

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