Physiological Age by Artificial Intelligence-Enhanced Electrocardiograms as a Novel Risk Factor of Mortality in Kidney Transplant Candidates.
Physiological Age by Artificial Intelligence-Enhanced Electrocardiograms as a Novel Risk Factor of Mortality in Kidney Transplant Candidates.
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人工智能增强心电图的生理年龄作为肾移植候选者死亡的新危险因素。
DOI：
10.1097/tp.0000000000004504
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发表时间：
2023
期刊：
影响因子：
6.2
通讯作者：
Attia,
中科院分区：
文献类型：
--
作者：
Lorenz,ElizabethC;Zaniletti,Isabella;Johnson,BradleyK;Petterson,TanyaM;Kremers,WalterK;Schinstock,CarrieA;Amer,Hatem;Cheville,AndreaL;LeBrasseur,NathanK;Winkelmayer,WolfgangC;Navaneethan,SankarD;Baez-Suarez,Abraham;Attia,
背景：肾移植（KT）前的死亡风险评估不完善。非移植人群死亡的一个新风险因素是通过人工智能在心电图 (ECG) 中的应用确定的生理年龄。本研究的目的是检查心电图年龄与 KT 候补死亡率之间的关系。方法。我们将先前开发的卷积神经网络应用于 2014 年至 2019 年评估的 KT 候选人的心电图，以确定心电图年龄。我们使用 Cox 比例风险模型来检查心电图年龄是否与候补死亡率相关。结果。在评估的 2183 名患者中，59.1% 是男性，81.4% 是白人，11.4% 在随访期间死亡。平均心电图年龄为 59.0±12.0 岁，心电图平均实际年龄为 53.3±13.6 岁。调整实际年龄、合并症和其他与死亡率相关的特征后，心电图年龄比类似实际年龄患者的平均心电图年龄每增加 > 10 岁，与死亡风险的增加相关（每增加 10 年风险比 3.59；95% 置信区间，2.06-5.72；P < 0.0001）。结论。心电图年龄是 KT 的危险因素候补名单死亡率。通过人工智能确定心电图年龄可能有助于在评估 KT 候选人时指导风险效益评估。
Background.Mortality risk assessment before kidney transplantation (KT) is imperfect. An emerging risk factor for death in nontransplant populations is physiological age as determined by the application of artificial intelligence to the electrocardiogram (ECG). The aim of this study was to examine the relationship between ECG age and KT waitlist mortality.Methods.We applied a previously developed convolutional neural network to the ECGs of KT candidates evaluated 2014 to 2019 to determine ECG age. We used a Cox proportional hazard model to examine whether ECG age was associated with waitlist mortality.Results.Of the 2183 patients evaluated, 59.1% were male, 81.4% were white, and 11.4% died during follow-up. Mean ECG age was 59.0±12.0 y and mean chronological age at ECG was 53.3±13.6 y. After adjusting for chronological age, comorbidities, and other characteristics associated with mortality, each increase in ECG age of> 10 y than the average ECG age for patients of a similar chronological age was associated with an increase in mortality risk (hazard ratio 3.59 per 10-y increase; 95% confidence interval, 2.06-5.72; P< 0.0001).Conclusions.ECG age is a risk factor for KT waitlist mortality. Determining ECG age through artificial intelligence may help guide risk-benefit assessment when evaluating candidates for KT.