移动数字传感器监测与围手术期预后的关系:系统综述。

Ali Memon, Patrick Lec, Andrew Lenis, Vidit Sharma, Erika Wood, George Schade, Wayne Brisbane
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引用次数: 1

摘要

背景:传统上,监测手术恢复仅限于医院和诊所内可测量的指标。然而,商业上可用的移动传感器现在能够将测量扩展到患者家中。由于这些传感器是为非医疗应用而开发的,它们的临床作用尚未确定。本系统综述的目的是评估移动传感器产生的数据与术后结果之间的关系。目的:本研究的目的是描述当前在围手术期使用的移动传感器及其数据与临床结果之间的相关性。方法:系统检索EMBASE、MEDLINE和Cochrane图书馆,从创建到2019年4月,以确定使用移动传感器监测的手术患者的研究。如果传感器收集患者的指标,如步数、温度或心率,则考虑传感器。如果患者接受了大手术(术后住院天数≥1天),患者在围手术期使用移动传感器进行监测,并且研究报告了术后结果(即并发症和再入院),则纳入研究。对于包括步数在内的研究,使用平均值和随机效应线性模型计算并发症和非并发症队列术后每天步数的汇总分析。采用推荐、评估、发展和评价分级工具评估研究质量。结果:从2209篇摘要中,我们确定了11项研究进行综述。回顾的研究包括前瞻性观察队列(n=10)或随机对照试验(n=1)。活动监测器是最广泛使用的传感器(n=10),另外还有一项研究测量温度、呼吸频率和心率(n=1)。低步数与较差的术后结果相关。术后每天约1000步的中位步数与不良手术结果相关。在这些研究中,手术类型和报告的术后结果类型之间存在异质性。结论:尽管手术类型和传感器存在显著的异质性,但在外科专业中,低步数与较差的术后结果相关。需要进一步的研究和标准化来评估移动传感器在术后护理中的作用,但术后每天约1000步的阈值值得进一步研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Relationship Between Mobile Digital Sensor Monitoring and Perioperative Outcomes: Systematic Review.

Background: Monitoring surgical recovery has traditionally been confined to metrics measurable within the hospital and clinic setting. However, commercially available mobile sensors are now capable of extending measurements into a patient's home. As these sensors were developed for nonmedical applications, their clinical role has yet to be established. The aim of this systematic review is to evaluate the relationship between data generated by mobile sensors and postoperative outcomes.

Objective: The objective of this study is to describe the current use of mobile sensors in the perioperative setting and the correlation between their data and clinical outcomes.

Methods: A systematic search of EMBASE, MEDLINE, and Cochrane Library from inception until April 2019 was performed to identify studies of surgical patients monitored with mobile sensors. Sensors were considered if they collected patient metrics such as step count, temperature, or heart rate. Studies were included if patients underwent major surgery (≥1 inpatient postoperative day), patients were monitored using mobile sensors in the perioperative period, and the study reported postoperative outcomes (ie, complications and hospital readmission). For studies including step count, a pooled analysis of the step count per postoperative day was calculated for the complication and noncomplication cohorts using mean and a random-effects linear model. The Grading of Recommendations, Assessment, Development, and Evaluation tool was used to assess study quality.

Results: From 2209 abstracts, we identified 11 studies for review. Reviewed studies consisted of either prospective observational cohorts (n=10) or randomized controlled trials (n=1). Activity monitors were the most widely used sensors (n=10), with an additional study measuring temperature, respiratory rate, and heart rate (n=1). Low step count was associated with worse postoperative outcomes. A median step count of around 1000 steps per postoperative day was associated with adverse surgical outcomes. Within the studies, there was heterogeneity between the type of surgery and type of reported postoperative outcome.

Conclusions: Despite significant heterogeneity in the type of surgery and sensors, low step count was associated with worse postoperative outcomes across surgical specialties. Further studies and standardization are needed to assess the role of mobile sensors in postoperative care, but a threshold of approximately 1000 steps per postoperative day warrants further investigation.

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