European journal of medical research · 2025
Impact of 2018 allocation system change on heart transplantation outcomes in china: a retrospective analysis.
СтатьяНазвание и аннотация: Перевод в очереди
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Zhu Zhiyuan, Zheng Shanshan, Huang Jie, Liao Zhongkai, Wang Xianqiang, Feng Wei, Zheng Zhe, Liu Sheng
Аннотация
BACKGROUND: In 2018, China implemented a nationally standardized urgency-based heart allocation system, replacing the previous region-based prioritization approach. However, its impact on waitlist dynamics and post-transplant outcomes remains unclear.
METHODS: We retrospectively analyzed heart transplant recipients treated at Fuwai Hospital between 2015 and 2022. The data were obtained from the China Heart Transplant Registry (CHTR). A total of 731 consecutive recipients were stratified into prereform (Era 1) and post-reform (Era 2) cohorts. Era 2 recipients were further classified as urgent or nonurgent. Survival was analyzed using Kaplan-Meier curves and log-rank tests. Multivariable Cox proportional hazards regression identified risk factors for 1-year mortality.
RESULTS: After implementation, urgent status transplants increased from 25.7% (2019) to 36.5% (2022), while the waitlist-to-transplant ratio declined from 1.41 to 1.10. Despite COVID-19-related disruptions that peaked waitlist mortality at 15.2% in 2021, urgent recipients had significantly shorter waiting times than nonurgent patients (15 vs. 89 days, P < 0.001). Notably, 1-year survival was similar between eras (92.15% vs. 94.57%, P = 0.181) and urgency groups (93.1% vs. 95.2%, P = 0.324), despite urgent recipients presenting with greater preoperative acuity (71.6% vs. 11.1% IABP dependence), more postoperative complications (74.1% vs. 21.8% IABP support), and longer ICU stays (6 vs. 6 days, P = 0.040). Multivariate analysis identified preoperative dialysis (aHR = 5.67, P = 0.001), elevated bilirubin (aHR = 1.01, P = 0.007), and prolonged cardiopulmonary bypass time (aHR = 1.01/hour, P < 0.001) as predictors of mortality.
CONCLUSIONS: Our findings provide preliminary evidence that China's urgency-based allocation system prioritizes critically ill recipients while maintaining comparable 1-year survival. These findings provide initial validation of the policy's clinical effectiveness in balancing equity and survival benefits. However, larger and more comprehensive datasets are needed for further confirmation.
METHODS: We retrospectively analyzed heart transplant recipients treated at Fuwai Hospital between 2015 and 2022. The data were obtained from the China Heart Transplant Registry (CHTR). A total of 731 consecutive recipients were stratified into prereform (Era 1) and post-reform (Era 2) cohorts. Era 2 recipients were further classified as urgent or nonurgent. Survival was analyzed using Kaplan-Meier curves and log-rank tests. Multivariable Cox proportional hazards regression identified risk factors for 1-year mortality.
RESULTS: After implementation, urgent status transplants increased from 25.7% (2019) to 36.5% (2022), while the waitlist-to-transplant ratio declined from 1.41 to 1.10. Despite COVID-19-related disruptions that peaked waitlist mortality at 15.2% in 2021, urgent recipients had significantly shorter waiting times than nonurgent patients (15 vs. 89 days, P < 0.001). Notably, 1-year survival was similar between eras (92.15% vs. 94.57%, P = 0.181) and urgency groups (93.1% vs. 95.2%, P = 0.324), despite urgent recipients presenting with greater preoperative acuity (71.6% vs. 11.1% IABP dependence), more postoperative complications (74.1% vs. 21.8% IABP support), and longer ICU stays (6 vs. 6 days, P = 0.040). Multivariate analysis identified preoperative dialysis (aHR = 5.67, P = 0.001), elevated bilirubin (aHR = 1.01, P = 0.007), and prolonged cardiopulmonary bypass time (aHR = 1.01/hour, P < 0.001) as predictors of mortality.
CONCLUSIONS: Our findings provide preliminary evidence that China's urgency-based allocation system prioritizes critically ill recipients while maintaining comparable 1-year survival. These findings provide initial validation of the policy's clinical effectiveness in balancing equity and survival benefits. However, larger and more comprehensive datasets are needed for further confirmation.