| Title: |
Open Renal Transplantation in Obese Patients: A Correlation Study between BMI and Early and Late Complications with Implementation of a Prognostic Risk Score |
| Authors: |
Marzorati, Sara; Iovino, Domenico; Inversini, Davide; Iori, Valentina; Parise, Cristiano; Masci, Federica; Liepa, Linda; Oltolina, Mauro; Zani, Elia; Franchi, Caterina; Morabito, Marika; Gritti, Mattia; Di Bella, Caterina; Bisogno, Silvia; Mangano, Alberto; Tozzi, Matteo; Carcano, Giulio; Ietto, Giuseppe |
| Contributors: |
Marzorati, Sara; Iovino, Domenico; Inversini, Davide; Iori, Valentina; Parise, Cristiano; Masci, Federica; Liepa, Linda; Oltolina, Mauro; Zani, Elia; Franchi, Caterina; Morabito, Marika; Gritti, Mattia; Di Bella, Caterina; Bisogno, Silvia; Mangano, Alberto; Tozzi, Matteo; Carcano, Giulio; Ietto, Giuseppe |
| Publisher Information: |
MDPI |
| Publication Year: |
2024 |
| Collection: |
Padua Research Archive (IRIS - Università degli Studi di Padova) |
| Subject Terms: |
kidney transplant; obesity; prognostic risk score |
| Description: |
Background: Obesity is a global epidemic that affects millions worldwide and can be a deterrent to surgical procedures in the population waiting for kidney transplantation. However, the literature on the topic is controversial. This study evaluates the impact of body mass index (BMI) on complications after renal transplantation, and identifies factors associated with major complications to develop a prognostic risk score. Methods: A correlation analysis between BMI and early and late complications was first performed, followed by a univariate and multivariate logistic regression analysis. The 302 included patients were divided into obese (BMI >= 30 kg/m2) and non-obese (BMI = 57 years, BMI >= 25 and >= 30 kg/m2, previous abdominal and/or urinary system surgery, and Charlson morbidity Score >= 3 as risk factors for significant complications. Based on the analyzed data, we developed a nomogram and a prognostic risk score. Results: The model's area (AUC) was 0.6457 (95% IC: 0.57; 0.72). The percentage of cases correctly identified by this model retrospectively applied to the entire cohort was 73.61%. Conclusions: A high BMI seems to be associated with an increased risk of DGF, but it does not appear to be a risk factor for other complications. Using an easy-to-use model, identification, and stratification of individualized risk factors could help to identify the need for interventions and, thus, improve patient eligibility and transplant outcomes. This could also contribute to maintaining an approach with high ethical standards. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/pmid/39063668; info:eu-repo/semantics/altIdentifier/wos/WOS:001277070800001; volume:14; issue:7; journal:LIFE; https://hdl.handle.net/11577/3539843 |
| DOI: |
10.3390/life14070915 |
| Availability: |
https://hdl.handle.net/11577/3539843; https://doi.org/10.3390/life14070915 |
| Rights: |
info:eu-repo/semantics/openAccess ; license:Creative commons ; license uri:http://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.9A00D850 |
| Database: |
BASE |