J Y Park1, M H Kim2, E J Bae3, S Kim4, D K Kim5, K W Joo5, Y S Kim5, J P Lee6, Y H Kim7, C S Lim8. 1. Department of Internal Medicine, Dongguk University Ilsan Hospital, Gyeonggi-do, Korea. 2. Department of Dental Hygiene, College of Health Science, Eulji University, Gyeonggi-do, Korea. 3. Department of Internal Medicine, Gyeongsang National University College of Medicine, Changwon, Korea. 4. Department of Internal Medicine, Seoul National University Bundang Hospital, Gyeonggi-do, Korea. 5. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea. 6. Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea. 7. Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea. 8. Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea. Electronic address: cslimjy@snu.ac.kr.
Abstract
BACKGROUND: Comorbid conditions are important in the survival of kidney transplant recipients. The weights assigned to comorbidities to predict survival may vary based on the type of index disease and advances in the management of comorbidities. We aimed to develop a modified Charlson comorbidity index (CCI) in renal allograft recipients (mCCI-KT), thereby improving risk stratification for mortality. METHODS: A total of 3765 recipients in a multicenter cohort were included to develop a comorbidity score. The weights of the comorbidities, per the CCI, were recalibrated using a Cox proportional hazards model. RESULTS: Peripheral vascular disease, liver disease, myocardial infarction, and diabetes in the CCI were selected from the Cox proportional hazards model. Thus, the mCCI-KT included 4 comorbidities with recalibrated severity weights. Whereas the CCI did not discriminate for survival, the mCCI-KT provided significant discrimination for survival using the Kaplan-Meier method and Cox regression analysis. The mCCI-KT showed modest increases in c-statistics (0.54 vs 0.52, P = .001) and improved net mortality risk reclassification by 16.3% (95% confidence interval, 3.2-29.4; P = .015) relative to the CCI. CONCLUSION: The mCCI-KT stratifies the risk for mortality in renal allograft recipients better than the CCI, suggesting that it may be a preferred index for use in clinical practice.
BACKGROUND: Comorbid conditions are important in the survival of kidney transplant recipients. The weights assigned to comorbidities to predict survival may vary based on the type of index disease and advances in the management of comorbidities. We aimed to develop a modified Charlson comorbidity index (CCI) in renal allograft recipients (mCCI-KT), thereby improving risk stratification for mortality. METHODS: A total of 3765 recipients in a multicenter cohort were included to develop a comorbidity score. The weights of the comorbidities, per the CCI, were recalibrated using a Cox proportional hazards model. RESULTS: Peripheral vascular disease, liver disease, myocardial infarction, and diabetes in the CCI were selected from the Cox proportional hazards model. Thus, the mCCI-KT included 4 comorbidities with recalibrated severity weights. Whereas the CCI did not discriminate for survival, the mCCI-KT provided significant discrimination for survival using the Kaplan-Meier method and Cox regression analysis. The mCCI-KT showed modest increases in c-statistics (0.54 vs 0.52, P = .001) and improved net mortality risk reclassification by 16.3% (95% confidence interval, 3.2-29.4; P = .015) relative to the CCI. CONCLUSION: The mCCI-KT stratifies the risk for mortality in renal allograft recipients better than the CCI, suggesting that it may be a preferred index for use in clinical practice.
Authors: Martin Tepel; Subagini Nagarajah; Qais Saleh; Olivier Thaunat; Stephan J L Bakker; Jacob van den Born; Morten A Karsdal; Federica Genovese; Daniel G K Rasmussen Journal: Front Immunol Date: 2022-07-25 Impact factor: 8.786
Authors: Paul V Ritschl; Nora Nevermann; Leke Wiering; Helen H Wu; Philipp Moroder; Andreas Brandl; Karl Hillebrandt; Frank Tacke; Frank Friedersdorff; Thorsten Schlomm; Wenzel Schöning; Robert Öllinger; Moritz Schmelzle; Johann Pratschke Journal: Am J Transplant Date: 2020-05-10 Impact factor: 9.369