AUTHOR=Qian Shirui , Cao Bingxin , Li Ping , Dong Nianguo 

TITLE=Development and validation of mortality prediction models for heart transplantation using nutrition-related indicators: a single-center study from China

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=Volume 11 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2024.1346202

DOI=10.3389/fcvm.2024.1346202

ISSN=2297-055X

ABSTRACT=Objective We sought to develop and validate a mortality prediction model for heart transplantation (HT) using nutrition related indicators, which clinicians could use to identify patients at high risk of death after HT.The model was developed and validated in adult participants in China who received HT between 1 January 2015 and 31 December 2020. The mean (SD) age was 48.67 (12.33) years and mean (SD) nutritional risk index (NRI) was 100.47 (11.89) in derivation cohort. Mortality after HT developed in 66 of 299 patients in the derivation cohort and 28 of 129 in the validation cohort. Age, nutritional risk index, serum creatine and triglyceride were included in the full model. The AUC of this model was 0.76. And the C statistics was 0.72 (95% CI, 0.67 -0.78) in derivation cohort and 0.71 (95% CI, 0.62 -0.81) in validation cohort. The multivariable model improved integrated discrimination improvement compared with the reduced model that included age and NRI (6.9%; 95% CI, 1.8% -15.1%) and the model which only included variable NRI (14.7%; 95% CI, 7.4% -26.2%) in the derivation cohort. Compared with the model which only included variable NRI, the full model improved categorical net reclassification index both in derivation cohort (41.8%; 95% CI, 9.9% -58.8%) and validation cohort (60.7%; 95% CI, 9.0% -100.5%).The proposed model was able to predict mortality after HT and estimate individualized risk of postoperative death. Clinicians could use this model to identify patients at high risk of postoperative death before HT surgery, which would help with targeted preventative therapy to reduce the mortality risk.