Development and validation of early prediction models for new-onset functional impairment of patients with trauma at hospital discharge

Author:

Ohbe Hiroyuki,Yokokawa Yuta,Sato Tetsuya,Kudo Daisuke,Kushimoto Shigeki

Abstract

BACKGROUND Early identification of individuals at risk of functional impairment after trauma is crucial for the timely clinical decision-making and intervention to improve reintegration into the society. This study aimed to develop and validate models for predicting new-onset functional impairment after trauma using predictors that are routinely collected within 2 days of hospital admission. METHODS In this multicenter retrospective cohort study of acute care hospitals in Japan, we identified adult patients with trauma with independence in carrying out activities of daily living before hospitalization, treated in the intensive or high-dependency care unit, and survived for at least 2 days between April 2008 and September 2023. The primary outcome was functional impairment defined as Barthel Index ≤60 at hospital discharge. In the internal validation data set (between April 2008 and August 2022), using the routinely collected 129 candidate predictors within 2 days of admission, we trained and tuned the four conventional and machine learning models with repeated random subsampling cross-validation. We measured the performance of these models in the temporal validation data set (between September 2022 and September 2023). We also computed the importance of each predictor variable in our model. RESULTS We identified 8,529 eligible patients. Functional impairment at discharge was observed in 41% of the patients (n = 3,506/8,529). In the temporal validation data set, all four models showed moderate discrimination ability, with areas under the curve above 0.79, and extreme gradient boosting showing the best performance (0.83). In the variable importance analyses, age was the most important predictor, followed by consciousness, severity score, cervical spinal cord injury, mild dementia, and serum albumin level at admission. CONCLUSION We successfully developed early prediction models for patients with trauma with new-onset functional impairment at discharge that achieved high predictive performance using routinely collected data within 2 days of hospital admission. LEVEL OF EVIDENCE Prognostic/Epidemiological; Level II

Publisher

Ovid Technologies (Wolters Kluwer Health)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3