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Validation of Somno-Art Software, a novel approach of sleep staging, compared with polysomnography in disturbed sleep profiles

STUDY OBJECTIVES: Integrated analysis of heart rate (electrocardiogram [ECG]) and body movements (actimetry) during sleep in healthy subjects have previously been shown to generate similar evaluation of sleep architecture and continuity with Somno-Art Software compared to polysomnography (PSG), the...

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Detalles Bibliográficos
Autores principales: Thiesse, Laurie, Staner, Luc, Bourgin, Patrice, Roth, Thomas, Fuchs, Gil, Kirscher, Debora, Schaffhauser, Jean-Yves, Saoud, Jay B, Viola, Antoine U
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104381/
https://www.ncbi.nlm.nih.gov/pubmed/37193409
http://dx.doi.org/10.1093/sleepadvances/zpab019
Descripción
Sumario:STUDY OBJECTIVES: Integrated analysis of heart rate (electrocardiogram [ECG]) and body movements (actimetry) during sleep in healthy subjects have previously been shown to generate similar evaluation of sleep architecture and continuity with Somno-Art Software compared to polysomnography (PSG), the gold standard. However, the performance of this new approach of sleep staging has not yet been evaluated on patients with disturbed sleep. METHODS: Sleep staging from 458 sleep recordings from multiple studies comprising healthy and patient population (obstructive sleep apnea [OSA], insomnia, major depressive disorder [MDD]) was obtained from PSG visual scoring using the American Academy of Sleep Medicine rules and from Somno-Art Software analysis on synchronized ECG and actimetry. RESULTS: Inter-rater reliability (IRR), evaluated with 95% absolute agreement intra-class correlation coefficient, was rated as “excellent” (ICC(AAAvg95%) ≥ 0.75) or “good” (ICC(AAAvg95%) ≥ 0.60) for all sleep parameters assessed, except non-REM (NREM) and N3 sleep in healthy participants (ICC(AAAvg95%) = 0.43, ICC(AAAvg95%) = 0.56) and N3 sleep in OSA patients (ICC(AAAvg95%) = 0.59) rated as “fair” IRR. Overall sensitivity, specificity, accuracy, and Cohen’s kappa coefficient of agreement (κ) on the entire sample were respectively of 93.3%, 69.5%, 87.8%, and 0.65 for wake/sleep classification and accuracy and κ were of 68.5% and 0.55 for W/N1+N2/N3/rapid eye movement (REM) classification. These performances were similar in healthy and patient population. CONCLUSIONS: The present results suggest that Somno-Art can be a valid sleep-staging tool in both healthy subjects and patients with OSA, insomnia, or MDD. It could complement existing non-attended techniques measuring sleep-related breathing patterns or be a useful alternative to laboratory-based PSG when this latter is not available.