Evolving trends in novel sleep tracking and sleep testing technology publications between 2020-2022.

IF 3.5 3区 医学 Q1 CLINICAL NEUROLOGY Journal of Clinical Sleep Medicine Pub Date : 2025-01-10 DOI:10.5664/jcsm.11562
Steven Holfinger, Sharon Schutte-Rodin, Dulip Ratnasoma, Ambrose A Chiang, Kelly Baron, Maryann Deak, Evin Jerkins, Julie Baughn, Kevin Gipson, Reut Gruber, Jennifer N Miller, Shalini Paruthi, Sachin Shaw, Fariha Abbasi-Feinberg, Eric Olsen, Anuja Bandyopadhyay
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Abstract

Study objectives: To update sleep medicine providers regarding (1) published research on the uses and performance of novel sleep tracking and testing technologies (2) the use of artificial intelligence to acquire and process sleep data and (3) research trends and gaps regarding the development and/or evaluation of these technologies.

Methods: Medline and Embase electronic databases were searched for studies utilizing screening and diagnostic sleep technologies, published between 2020 and 2022 in journals focusing on human sleep. Studies' quality was determined based on the Study Design criteria of The Oxford Centre for Evidence-Based Medicine Levels of Evidence.

Results: 96 of 3849 articles were included. Most studies were adult performance evaluation (validation) studies, often comparing a novel technology to polysomnography. Sleep tracker publications tended to be USA-based, non-industry funded, performance studies on healthy adults using non-FDA (Food and Drug Administration) cleared technologies. Sleep apnea testing technologies were more frequently industry-funded and FDA-cleared. All studied technologies utilized software with an algorithm and/or artificial intelligence. Few studies used randomized control designs, or accounted for recruitment/attrition biases associated with participants' age, race/ethnicity, or comorbid health conditions.

Conclusions: Evidence-based publications have not kept pace with the proliferation and landscape of' consumer and clinical sleep technologies. Due to the variance in technologies used within sleep research, careful review of the software used within studies is recommended. Future publications may fill identified gaps by including underrepresented populations, maintaining independence from industry, and through rigorous study design.

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2020-2022年新型睡眠跟踪和睡眠测试技术出版物的发展趋势。
研究目标:向睡眠医学提供者提供以下方面的最新信息:(1)关于新型睡眠跟踪和测试技术的使用和性能的已发表研究;(2)使用人工智能获取和处理睡眠数据;(3)关于这些技术开发和/或评估的研究趋势和差距。方法:检索Medline和Embase电子数据库,检索2020年至2022年间发表在人类睡眠期刊上的使用筛查和诊断睡眠技术的研究。研究质量是根据牛津循证医学证据水平中心的研究设计标准确定的。结果:3849篇纳入96篇。大多数研究是成人表现评估(验证)研究,通常将一种新技术与多导睡眠图进行比较。睡眠追踪器的出版物往往是基于美国的,非行业资助的,对健康成年人使用非fda(食品和药物管理局)批准的技术进行的性能研究。睡眠呼吸暂停测试技术更多的是由工业界资助和fda批准的。所有研究的技术都使用了带有算法和/或人工智能的软件。很少有研究采用随机对照设计,或考虑与参与者年龄、种族/民族或合并症健康状况相关的招募/消耗偏差。结论:基于证据的出版物没有跟上消费者和临床睡眠技术的增长和发展。由于睡眠研究中使用的技术存在差异,建议仔细审查研究中使用的软件。未来的出版物可能会通过纳入代表性不足的人群,保持独立于行业,并通过严格的研究设计来填补已确定的空白。
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来源期刊
CiteScore
6.20
自引率
7.00%
发文量
321
审稿时长
1 months
期刊介绍: Journal of Clinical Sleep Medicine focuses on clinical sleep medicine. Its emphasis is publication of papers with direct applicability and/or relevance to the clinical practice of sleep medicine. This includes clinical trials, clinical reviews, clinical commentary and debate, medical economic/practice perspectives, case series and novel/interesting case reports. In addition, the journal will publish proceedings from conferences, workshops and symposia sponsored by the American Academy of Sleep Medicine or other organizations related to improving the practice of sleep medicine.
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