ArticleMethodsX2025
Automated diagnostic method for sleep apnea and hypopnea using overnight airflow and oxygen saturation.
Article in MethodsX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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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
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Accuracy of Machine Learning Algorithms Based on Electroencephalogram in Sleep Apnea Detection: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Detection of apnea and hypopnea events using a wireless Abdomen-Worn sensor with SpO₂ integration.Sleep & breathing = Schlaf & Atmung · 2026Article
- Multicenter Validation of an AI-Based Snoring Model vs. Wearables for Diagnosing Sleep Apnea.Nature and science of sleep · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Polysomnography (PSG) is the gold standard for diagnosing obstructive sleep apnea-hypopnea syndrome (OSAHS), but it relies heavily on manual scoring by experienced clinicians, which is time-consuming and costly. This study presents an automated method for detecting sleep apnea and hypopnea events using overnight airflow and blood oxygen saturation signals. Apnea episodes are identified through local range (LR) analysis of airflow, while rapid oxygen desaturation supports hypopnea detection. LR thresholds were trained on data from 100 patients and validated on an independent cohort of 43 patients. The system's performance was compared to clinician annotations using the apnea-hypopnea index (AHI). The results demonstrated high consistency with manual scoring, highlighting the method's potential for home-based monitoring and large-scale screening. This approach offers a lightweight and scalable alternative to traditional diagnostic procedures, reducing dependence on complex equipment and human interpretation.
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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.