ArticleScientific reports2026
Sleep spindle density increases in patients with severe obstructive sleep apnea after 6 months of treatment: a longitudinal study.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Obstructive sleep apnea (OSA) disrupts sleep structure and alters NREM sleep microarchitecture, including reductions in sleep spindle activity. Given the central role of sleep spindles in sleep continuity and neurophysiological processing, their reduction in patients with OSA suggests a potentially reversible sleep microstructural disruption. We evaluated sleep spindles across four EEG derivations (F3, F4, C3, and C4) during NREM sleep in patients with suspected OSA, assessed before and after 6 months of routine clinical practice. The 6-month polysomnography was performed with participants using their prescribed treatment during the recording. A total of 216 patients (mean age 52.0 ± 11.5 years; 32.9% women) completed the study, including 66 with no or mild OSA (AHI < 15 events/hour), 50 with moderate OSA (AHI 15-<30), and 100 with severe OSA (AHI ≥ 30). Pre- and post-treatment sleep study data were available for analysis. At baseline, patients with severe OSA exhibited significantly lower sleep spindle density (SSD) compared with patients with moderate OSA and those with mild or no OSA. After six months of routine clinical management, there was a significant increase in SSD, but only in the severe OSA group (e.g., N2 C4-M1: +0.47 events/min, 95% CI 0.30 to 0.65), with similar patterns observed across central and selected frontal derivations. After correction for multiple comparisons, subtype analyses supported a significant increase only for fast spindles at a central derivation. These findings suggest that severe OSA is associated with spindle deficits and that routine clinical management ameliorates altered sleep microarchitecture. SSD may serve as a sensitive marker of severity-related changes in sleep microstructure and could complement conventional sleep staging in clinical cohorts.
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