Live-Donor Kidney Transplant Outcome Prediction (L-TOP) using artificial intelligence

结果(博弈论) 医学 肾移植 肾移植 内科学 数理经济学 数学
作者
Hatem Ali,Mahmoud Mohammed,Miklos Z. Molnar,Tibor Fülöp,B. F. Burke,Sunil Shroff,Arun Shroff,David Briggs,Nithya Krishnan
出处
期刊:Nephrology Dialysis Transplantation [Oxford University Press]
卷期号:39 (12): 2088-2099 被引量:1
标识
DOI:10.1093/ndt/gfae088
摘要

ABSTRACT Background Outcome prediction for live-donor kidney transplantation improves clinical and patient decisions and donor selection. However, the currently used models are of limited discriminative or calibration power and there is a critical need to improve the selection process. We aimed to assess the value of various artificial intelligence (AI) algorithms to improve the risk stratification index. Methods We evaluated pre-transplant variables among 66 914 live-donor kidney transplants (performed between 1 December 2007 and 1 June 2021) from the United Network of Organ Sharing database, randomized into training (80%) and test (20%) sets. The primary outcome measure was death-censored graft survival. We tested four machine learning models for discrimination [time-dependent concordance index (CTD) and area under the receiver operating characteristic curve (AUC)] and calibration [integrated Brier score (IBS)]. We used decision-curve analysis to assess the potential clinical utility. Results Among the models, the deep Cox mixture model showed the best discriminative performance (AUC = 0.70, 0.68 and 0.68 at 5, 10 and 13 years post-transplant, respectively). CTD reached 0.70, 0.67 and 0.66 at 5, 10 and 13 years post-transplant. The IBS score was 0.09, indicating good calibration. In comparison, applying the Living Kidney Donor Profile Index (LKDPI) on the same cohort produced a CTD of 0.56 and an AUC of 0.55–0.58 only. Decision-curve analysis showed an additional net benefit compared with the LKDPI ‘treat all’ and ‘treat none’ approaches. Conclusion Our AI-based deep Cox mixture model, termed Live-Donor Kidney Transplant Outcome Prediction, outperforms existing prediction models, including the LKDPI, with the potential to improve decisions for optimum live-donor selection by ranking potential transplant pairs based on graft survival. This model could be adopted to improve the outcomes of paired exchange programs.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
星辰发布了新的文献求助10
刚刚
坦率的匪应助科研通管家采纳,获得10
刚刚
刚刚
NexusExplorer应助科研通管家采纳,获得10
刚刚
黑猫发布了新的文献求助10
1秒前
坚强幼晴发布了新的文献求助10
1秒前
哈哈完成签到,获得积分20
2秒前
吉吉发布了新的文献求助10
3秒前
lize5493完成签到,获得积分10
3秒前
Melodie完成签到,获得积分10
3秒前
热心市民小红花应助123采纳,获得10
4秒前
油饼完成签到,获得积分10
5秒前
量子星尘发布了新的文献求助10
6秒前
徐璇完成签到,获得积分10
6秒前
星辰完成签到,获得积分10
8秒前
9秒前
9秒前
9秒前
10秒前
12秒前
6666发布了新的文献求助10
14秒前
无限雨南发布了新的文献求助10
14秒前
EgoElysia完成签到,获得积分10
14秒前
敏感雅香发布了新的文献求助10
15秒前
归尘发布了新的文献求助150
16秒前
zumri发布了新的文献求助10
16秒前
jia完成签到,获得积分10
18秒前
19秒前
19秒前
hino发布了新的文献求助10
19秒前
共享精神应助6666采纳,获得10
21秒前
shower_009完成签到,获得积分10
22秒前
24秒前
在水一方应助哈哈采纳,获得10
25秒前
25秒前
纯真追命完成签到 ,获得积分10
25秒前
25秒前
26秒前
咚咚锵完成签到,获得积分10
26秒前
26秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3988868
求助须知:如何正确求助?哪些是违规求助? 3531255
关于积分的说明 11253071
捐赠科研通 3269858
什么是DOI,文献DOI怎么找? 1804822
邀请新用户注册赠送积分活动 881994
科研通“疑难数据库(出版商)”最低求助积分说明 809035