Comprehensive Evaluation of Night-to-Night Variability in Polysomnography Metrics and Apnea-Hypopnea Index-Based...

Night-to-night variability (NtNV) in polysomnography findings contributes to diagnostic uncertainty in OSA, yet multimetric evaluations using closely spaced polysomnography nights-particularly in moderate-to-severe disease-remain limited. The comparative stability of apnea-hypopnea index (AHI) definitions, hypoxic burden (HB), and threshold calibration remains unclear.

What is the NtNV across polysomnography-derived metrics, and how do AHI scoring definitions and threshold calibration influence diagnostic stability in OSA?

We performed a retrospective analysis of a prospective study including 147 participants with prior diagnosis or high pretest likelihood of moderate to severe OSA who underwent 2 polysomnography examinations within 10 days. NtNV was quantified across 20 polysomnography-derived metrics. A normalized NtNV matrix was analyzed using principal component analysis (PCA) followed by unsupervised k-means clustering to identify data-driven variability-pattern groups. Diagnostic stability was compared across AHI definitions (3%/arousal vs 4%/arousal) and HB risk categories. Statistical calibration models derived AHI 4% thresholds aligned with AHI 3%/arousal severity cutpoints.

NtNV demonstrated heterogeneity. Maximum heart rate (HR), positional fractions, and sleep latency were most variable, whereas average peripheral oxygen saturation (SpO₂), average HR, minimum SpO₂, and HB were most stable. In the PCA followed by k-means analysis, respiratory event frequency metrics contributed most strongly and separated participants into lower respiratory variability pattern and higher respiratory variability pattern groups. AHI of 4% showed higher classification disagreement than AHI of 3%/arousal in short-interval (29.9% vs 21.2% overall; 14.3% vs 5.4% at the moderate-to-severe threshold) and longitudinal (45.9% vs 31.1% and 20.9% vs 8.2%, respectively) comparisons. HB showed low internight disagreement (11.8%). Calibration models aligned AHI 4% thresholds of 6.1 to 6.9 events/h and of 18.4 to 22.3 events/h with AHI 3%/arousal cutpoints of 15 and 30 events/h.

Our results show that positional, autonomic, and sleep architecture metrics showed the highest NtNV, respiratory event frequency metrics showed intermediate NtNV, and oxygenation showed the most stable NtNV. Greater classification disagreement with AHI 4% was threshold driven, with implications for hypopnea scoring and payer policy in OSA diagnosis.

ClinicalTrials.gov; No.: NCT06603441; URL: www.

gov.