For almost 50 years, sleep laboratories around the world have been collecting massive amounts of polysomnographic (PSG) physiological data to diagnose sleep disorders, the majority of which are not utilized in the clinical setting. Only a small fraction of the information available within these signals is utilized to generate indices. For example, the apnea–hypopnea index (AHI) remains the primary tool for diagnostic and therapeutic decision-making for obstructive sleep apnea (OSA) despite repeated studies showing it to be inadequate in predicting clinical consequences. Today, there are many novel approaches to PSG signals, making it possible to extract more complex metrics and analyses that are potentially more clinically relevant for individual patients. However, the pathway to implement novel PSG metrics/analyses into routine clinical practice is unclear. Our goal with this review is to highlight some of the novel PSG metrics/analyses that are becoming available. We suggest that stronger academic-industry relationships would facilitate the development of state-of-the-art clinical research to establish the value of novel PSG metrics/analyses in clinical sleep medicine. Collectively, as a sleep community, it is time to reinvent how we utilize the polysomnography to move us towards Precision Sleep Medicine.

近 50 年来，世界各地的睡眠实验室一直在收集大量多导睡眠图 (PSG) 生理数据来诊断睡眠障碍，其中大部分未在临床环境中使用。这些信号中只有一小部分可用信息用于生成索引。例如，呼吸暂停低通气指数 (AHI) 仍然是阻塞性睡眠呼吸暂停 (OSA) 诊断和治疗决策的主要工具，尽管反复研究表明它不足以预测临床后果。今天，有许多新的 PSG 信号方法，使得提取更复杂的指标和分析成为可能，这些指标和分析可能与个体患者的临床相关性更高。然而，在常规临床实践中实施新的 PSG 指标/分析的途径尚不清楚。我们这次审查的目标是强调一些可用的新 PSG 指标/分析。我们建议，更牢固的学术与行业关系将促进最先进的临床研究的发展，以建立新的 PSG 指标/分析在临床睡眠医学中的价值。总的来说，作为一个睡眠社区，是时候重塑我们如何利用多导睡眠图将我们推向精准睡眠医学了。我们建议，更牢固的学术与行业关系将促进最先进的临床研究的发展，以建立新的 PSG 指标/分析在临床睡眠医学中的价值。总的来说，作为一个睡眠社区，是时候重塑我们如何利用多导睡眠图将我们推向精准睡眠医学了。我们建议，更牢固的学术与行业关系将促进最先进的临床研究的发展，以建立新的 PSG 指标/分析在临床睡眠医学中的价值。总的来说，作为一个睡眠社区，是时候重塑我们如何利用多导睡眠图将我们推向精准睡眠医学了。