机器学习预测100岁后的百岁老人生存率:一个回顾性,基于人口的队列研究
Jonathan K L Mak1,2, Noel C Yue1, Gloria Hoi-Yee Li3
1Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
概括
使用电子健康记录的机器学习模型可以以中等准确度预测百岁老人的短期死亡率. 关键的生存因素包括白蛋白,住院和尿素水平.
科学领域:
- 老年学是指老年学的学科.
- 生物医学信息学 生物医学信息学
- 机器学习 机器学习
背景情况:
- 准确预测极端年龄组的生存率仍然是一个挑战.
- 电子健康记录 (EHR) 为健康预测提供了丰富的数据来源.
- 这项研究研究了使用机器学习 (ML) 和EHRs的百岁老人预测死亡率.
研究的目的:
- 评估使用ML和EHR来预测百岁老人的死亡率的可行性.
- 确定这一极端年龄组生存的关键决定因素.
- 将基于ML的预测模型与传统的并发症和脆弱性得分进行比较.
主要方法:
- 来自香港电子健康数据库 (2004-2018) 的9718名百岁老人的分析.
- 训练和测试后勤回归和四个ML算法使用82个预测器.
- 使用歧视 (AUROC) 和校准指标在百岁老人和最年长的队伍中的模型性能评估.
主要成果:
- 极端梯度增强ML模型实现了最高的性能,AUROC为0.707的1年死亡率和0.704的2年死亡率.
- 模型表明对5年死亡率预测的校准不佳.
- 较低的白蛋白,更频繁的住院治疗和更高的尿素水平是最重要的死亡率预测因素,优于并发症和脆弱性得分.
结论:
- ML模型和EHR数据可以以中等准确度预测百岁老人的短期生存率.
- 需要进一步的研究来探索最老的老年人群中特定年龄的死亡率预测因素.
相关概念视频
01:21Cancer Survival Analysis
645
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
645
01:20Actuarial Approach
286
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
286
01:24Kaplan-Meier Approach
574
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
574
01:15Assumptions of Survival Analysis
392
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
392
01:20Comparing the Survival Analysis of Two or More Groups
553
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
553
01:18Introduction To Survival Analysis
747
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
747