ReviewJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2026
From classic to cutting-edge: technological approaches to respiratory physiological signals in assessing sleep-disordered breathing.
Review in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The diagnostic armamentarium for sleep-disordered breathing (SDB) has undergone substantial expansion in recent years, alongside the heightened awareness of SDB, its systemic impact on health, and the proliferation of home sleep apnea testing (HSAT). Many contemporary diagnostic modalities incorporate physiological measurement techniques that draw upon concepts primarily investigated in research paradigms, but may not align with existing HSAT classification frameworks, particularly regarding respiratory signal acquisition and analysis. This narrative review synthesizes current respiratory analysis techniques employed in SDB diagnosis, categorizing them broadly into three principal measurement domains: airflow dynamics, respiratory effort mechanics, and sympathetic activation patterns. Emphasis is placed on the historical background, underlying physiological mechanism, and clinical utility, while evaluating the methodological strengths and inherent limitations of each measurement approach. While prior literature reviews have extensively documented conventional respiratory analysis methodologies in sleep apnea diagnostics, the rapidly evolving landscape of cutting-edge diagnostic technologies and their physiological signals remain insufficiently addressed in the current literature. This respiratory technology-centered narrative review bridges this crucial knowledge gap through a rigorous and comprehensive examination of both established and emerging respiratory assessment modalities. Furthermore, we posit that the existing sleep testing classification frameworks no longer adequately reflect the breadth and sophistication of contemporary diagnostic technologies, and that their revision represents a pressing imperative for the sleep medicine community. We advocate a reconceptualization of sleep testing taxonomies to ensure clinical relevance and diagnostic utility amid accelerating technological evolution.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.