Wearable Device-Measured Daily Step Count is an Independent Predictor of Postoperative Surgical Complications Among All of Us Research Participants

Author:

Gehl Carson J.ORCID,Verhagen Nathaniel B.ORCID,Shaik Tahseen J.,Nimmer Kaitlyn,Yang XinORCID,Taylor Bradley W.,Nataliansyah Mochamad M.,Kerns Sarah L.ORCID,Kothari Anai N.ORCID

Abstract

ABSTRACTBackgroundThe association between preoperative wearable device step counts and surgical outcomes has not been examined using commercial devices linked to electronic health records (EHR) at a population level. This study measured the association between daily preoperative step counts and postoperative complications.Study DesignData was obtained using the All of Us (AOU) Research program, a nationwide initiative to collect EHR and health-related data from the population. Included were patients who underwent a surgical procedure included in the National Surgical Quality Improvement Program (NSQIP) targeted procedures dataset. Excluded were patients without complete perioperative FitBit data. Primary outcome was the development of a postoperative complication. All analyses were performed in the AOU researcher workbench.ResultsOf 27,150 patients who underwent a surgical procedure, 475 participants with preoperative wearable data were included. 74.7% were female and 85.2% were White. The average age was 57.2 years. The overall rate of postoperative complications was 12.6%. Patients averaging fewer than 7,500 daily steps were at increased odds for developing a postoperative complication (OR 1.83, 95% CI [1.01, 3.31]). Following adjustment for age, sex, race, comorbid disease, body mass index (BMI), and relative procedure risk, patients with a baseline average steps/day < 7,500 were at increased odds for postoperative complication (aOR = 2.06, 95% CI [1.05, 4.06]).ConclusionsThis study found an increase in overall postoperative complication rate in patients recording lower average preoperative step counts. Patients with a baseline of less than 7,500 steps per day had increased odds of postoperative complications in this cohort. This population data supports the use of wearable devices for surgical risk stratification and suggests step count may help to measure preoperative fitness.

Publisher

Cold Spring Harbor Laboratory

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