• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

韩国老年肺移植受者的候补名单表现和移植后结局分析:一项全国性队列研究。

Analysis of the waitlist performance and post-transplant outcomes of lung transplant in elderly recipients in Korea: A nationwide cohort study.

机构信息

Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Pusan National University School of Medicine, Transplantation Research Center, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea.

Department of Thoracic and Cardiovascular Surgery, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Republic of Korea.

出版信息

Clin Transplant. 2024 Sep;38(9):e15299. doi: 10.1111/ctr.15299.

DOI:10.1111/ctr.15299
PMID:39268639
Abstract

BACKGROUND

There is a lack of information on the waitlist performance and post-transplant outcomes of lung transplants in elderly recipients in Korea.

METHODS

We retrospectively reviewed and analyzed data from the Korean Network for Organ Sharing database between March 2010 and August 2023.

RESULTS

In total, 2574 patients were listed for lung transplantation during the study period, with 511 (19.9%) of them being over 65 years of age. Among these, 188 patients (36.8%) underwent transplantation, while 184 patients (36%) passed away without undergoing transplantation at the time of data extraction. The most prevalent underlying disease on the waitlist was idiopathic pulmonary fibrosis, accounting for 68.1%. The 1-year survival rate was significantly lower in the elderly compared to that in the nonelderly (65.4 vs. 75.4%; p = .004). In the multivariate Cox analysis, elderly (hazard ratio [HR], 1.49; 95% CI, 1.14-1.97; p = .004) and a high urgent status at registration (HR, 1.83; 95% CI, 1.40-2.40; p < .001) were significantly associated with post-transplant 1-year mortality. Kaplan-Meier curves demonstrated a significant difference in post-transplant mortality based on the urgency status at enrollment (χ = 8.302, p = .016). Even with the same highly urgent condition at the time of transplantation, different prognoses were observed depending on the condition at listing (χ = 9.056, p = .029).

CONCLUSION

The elderly exhibited worse transplant outcomes than nonelderly adults, with a highly urgent status at registration identified as a significant risk factor. Unprepared, highly urgent transplantation was associated with poor outcomes.

摘要

背景

韩国缺乏有关老年肺移植受者在等待名单上的表现和移植后结果的信息。

方法

我们回顾性分析了 2010 年 3 月至 2023 年 8 月期间韩国器官共享网络数据库中的数据。

结果

在研究期间,共有 2574 名患者被列入肺移植名单,其中 511 名(19.9%)年龄超过 65 岁。其中,188 名(36.8%)患者接受了移植,而 184 名(36%)患者在数据提取时未接受移植就已去世。等待名单上最常见的基础疾病是特发性肺纤维化,占 68.1%。与非老年患者相比,老年患者的 1 年生存率显著降低(65.4%对 75.4%;p=0.004)。在多变量 Cox 分析中,年龄较大(风险比[HR],1.49;95%置信区间[CI],1.14-1.97;p=0.004)和登记时的高紧急状态(HR,1.83;95%CI,1.40-2.40;p<0.001)与移植后 1 年死亡率显著相关。Kaplan-Meier 曲线显示,根据登记时的紧急状态,移植后死亡率存在显著差异(χ2=8.302,p=0.016)。即使在移植时具有相同的高度紧急情况,根据列表时的情况,也观察到不同的预后(χ2=9.056,p=0.029)。

结论

与非老年成年人相比,老年患者的移植结果更差,登记时的高度紧急状态被确定为显著的危险因素。准备不足的高度紧急移植与不良结局相关。

相似文献

1
Analysis of the waitlist performance and post-transplant outcomes of lung transplant in elderly recipients in Korea: A nationwide cohort study.韩国老年肺移植受者的候补名单表现和移植后结局分析:一项全国性队列研究。
Clin Transplant. 2024 Sep;38(9):e15299. doi: 10.1111/ctr.15299.
2
Gender differences in long-term survival post-transplant: A single-institution analysis in the lung allocation score era.移植后长期生存的性别差异:肺分配评分时代的单机构分析
Clin Transplant. 2017 Mar;31(3). doi: 10.1111/ctr.12889. Epub 2017 Feb 8.
3
Association of pretransplant and posttransplant program ratings with candidate mortality after listing.移植前和移植后项目评分与候选者列名后的死亡率的相关性。
Am J Transplant. 2019 Feb;19(2):399-406. doi: 10.1111/ajt.15032. Epub 2018 Aug 21.
4
Functional status at listing predicts waitlist and posttransplant mortality in pediatric liver transplant candidates.在列功能状态预测儿科肝移植候选者的等待名单和移植后死亡率。
Am J Transplant. 2019 May;19(5):1388-1396. doi: 10.1111/ajt.15203. Epub 2018 Dec 31.
5
Waiting list outcomes in pediatric lung transplantation: Poor results for children listed in adult transplant programs.儿科肺移植的候补者名单结果:在成人移植项目中列入名单的儿童结果较差。
J Heart Lung Transplant. 2017 Nov;36(11):1201-1208. doi: 10.1016/j.healun.2017.04.010. Epub 2017 Apr 24.
6
State-Level Variation in Waitlist Mortality and Transplant Outcomes Among Patients Listed for Heart Transplantation in the US From 2011 to 2016.2011 年至 2016 年美国心脏移植患者名单上的等待者死亡率和移植结果的州级差异。
JAMA Netw Open. 2020 Dec 1;3(12):e2028459. doi: 10.1001/jamanetworkopen.2020.28459.
7
Impact of delayed listing after initiating kidney transplant evaluation on transplant outcomes.启动肾移植评估后延迟登记对移植结果的影响。
Clin Transplant. 2024 May;38(5):e15319. doi: 10.1111/ctr.15319.
8
Inferior Outcomes on the Waiting List in Low-Volume Pediatric Heart Transplant Centers.低容量儿科心脏移植中心的候补名单上的不良结果。
Am J Transplant. 2017 Jun;17(6):1515-1524. doi: 10.1111/ajt.14252. Epub 2017 Mar 30.
9
Outcomes of Patients on the Lung Transplantation Waitlist in Korea: A Korean Network for Organ Sharing Data Analysis.韩国肺移植候补患者的结局:韩国器官共享网络数据分析。
J Korean Med Sci. 2022 Oct 24;37(41):e294. doi: 10.3346/jkms.2022.37.e294.
10
Performance Changes Following the Revision of Organ Allocation System of Lung Transplant: Analysis of Korean Network for Organ Sharing Data.肺移植器官分配系统修订后对供体肺功能的影响:韩国器官共享网络数据分析。
J Korean Med Sci. 2021 Mar 29;36(12):e79. doi: 10.3346/jkms.2021.36.e79.

引用本文的文献

1
Machine Learning for 1-Year Graft Failure Prediction in Lung Transplant Recipients: The Korean Organ Transplantation Registry.用于预测肺移植受者1年移植物失败的机器学习:韩国器官移植登记处
Clin Transplant. 2025 Aug;39(8):e70268. doi: 10.1111/ctr.70268.
2
Development of a Machine Learning-Powered Optimized Lung Allocation System for Maximum Benefits in Lung Transplantation: A Korean National Data.开发一种由机器学习驱动的优化肺分配系统以实现肺移植的最大效益:韩国国家数据。
J Korean Med Sci. 2025 Feb 24;40(7):e18. doi: 10.3346/jkms.2025.40.e18.