Venkat Bhat1, Mahmood Tazari2, Kymberly D Watt3, Mamatha Bhat4. 1. Department of Psychiatry, University Health Network, Toronto, Ontario, Canada. 2. Multi-Organ Transplant Program, University Health Network, Toronto, Ontario, Canada. 3. Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN. 4. Multi-Organ Transplant Program, University Health Network, Toronto, Ontario, Canada; Division of Gastroenterology and Hepatology, University Health Network, Toronto, Ontario, Canada. Electronic address: Mamatha.bhat@uhn.ca.
Abstract
OBJECTIVE: To identify key predictors and survival outcomes of new-onset diabetes after transplant (NODAT) in liver transplant (LT) recipients by using the Scientific Registry of Transplant Recipients. PATIENTS AND METHODS: Data of all adult LT recipients between October 1, 1987, and March 31, 2016, were analyzed using various machine learning methods. These data were divided into training (70%) and validation (30%) data sets to robustly determine predictors of NODAT. The long-term survival of patients with NODAT relative to transplant recipients with preexisting diabetes and those without diabetes was assessed. RESULTS: Increasing age (odds ratio [OR], 1.01; 95% CI, 1.00-1.02; P≤.001), male sex (OR, 1.09; 95% CI, 1.05-1.13; P=.03), and obesity (OR, 1.13; 95% CI, 1.08-1.18; P<.001) were significantly associated with NODAT. Sirolimus as a primary immunosuppressant carried a 33% higher risk of NODAT than did tacrolimus (OR, 1.33; 95% CI, 1.22-1.45; P<.001) at 1 year after LT. Patients with NODAT had significantly decreased 10-year survival than did those without diabetes (63.0% vs 74.9%; P<.001), similar to survival in patients with diabetes before LT (58.9%). CONCLUSION: Using a machine learning approach, we found that older, male, and obese recipients are at especially higher risk of NODAT. Donor features do not affect risk. In addition, sirolimus-based immunosuppression is associated with a significantly higher risk of NODAT than other immunosuppressants. Most importantly, NODAT adversely affects long-term survival after LT in a manner similar to preexisting diabetes, indicating the need for more aggressive care and closer follow-up.
OBJECTIVE: To identify key predictors and survival outcomes of new-onset diabetes after transplant (NODAT) in liver transplant (LT) recipients by using the Scientific Registry of Transplant Recipients. PATIENTS AND METHODS: Data of all adult LT recipients between October 1, 1987, and March 31, 2016, were analyzed using various machine learning methods. These data were divided into training (70%) and validation (30%) data sets to robustly determine predictors of NODAT. The long-term survival of patients with NODAT relative to transplant recipients with preexisting diabetes and those without diabetes was assessed. RESULTS: Increasing age (odds ratio [OR], 1.01; 95% CI, 1.00-1.02; P≤.001), male sex (OR, 1.09; 95% CI, 1.05-1.13; P=.03), and obesity (OR, 1.13; 95% CI, 1.08-1.18; P<.001) were significantly associated with NODAT. Sirolimus as a primary immunosuppressant carried a 33% higher risk of NODAT than did tacrolimus (OR, 1.33; 95% CI, 1.22-1.45; P<.001) at 1 year after LT. Patients with NODAT had significantly decreased 10-year survival than did those without diabetes (63.0% vs 74.9%; P<.001), similar to survival in patients with diabetes before LT (58.9%). CONCLUSION: Using a machine learning approach, we found that older, male, and obese recipients are at especially higher risk of NODAT. Donor features do not affect risk. In addition, sirolimus-based immunosuppression is associated with a significantly higher risk of NODAT than other immunosuppressants. Most importantly, NODAT adversely affects long-term survival after LT in a manner similar to preexisting diabetes, indicating the need for more aggressive care and closer follow-up.
Authors: Neta Gotlieb; Amirhossein Azhie; Divya Sharma; Ashley Spann; Nan-Ji Suo; Jason Tran; Ani Orchanian-Cheff; Bo Wang; Anna Goldenberg; Michael Chassé; Heloise Cardinal; Joseph Paul Cohen; Andrea Lodi; Melanie Dieude; Mamatha Bhat Journal: NPJ Digit Med Date: 2022-07-11
Authors: Giang Thu Vu; Bach Xuan Tran; Roger S McIntyre; Hai Quang Pham; Hai Thanh Phan; Giang Hai Ha; Kenneth K Gwee; Carl A Latkin; Roger C M Ho; Cyrus S H Ho Journal: Int J Environ Res Public Health Date: 2020-03-17 Impact factor: 3.390