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Updated: Jan 6, 2026

Drug-Induced Sleep Endoscopy DISE with Target Controlled Infusion TCI and Bispectral Analysis in Obstructive Sleep Apnea
Published on: December 6, 2016
REM-related obstructive sleep apnea: low AHI-high hypoxemia paradox
Elvan Burak Verdi1, Turan Acıcan2
1Department of Chest Diseases, Ankara University Faculty of Medicine, Ankara, Mamak, 06220, Turkey. burakverdi@gmail.com.
Purpose:
REM-related obstructive sleep apnea (OSA) presents a paradox where a low apnea-hypopnea index (AHI) may mask significant disease. We compared polysomnography, comorbidities, and oxygenation metrics across OSA phenotypes to determine if AHI-based severity classifications underestimate the nocturnal hypoxemia in REM-related OSA.
Methods:
Retrospectively, 378 OSA patients were classified as REM-related (AHIREM ≥2× AHINREM; AHINREM <5·h⁻¹, n = 30), REM-aggravated (AHIREM ≥2× AHINREM; AHINREM ≥5·h⁻¹, n = 63), or stage-independent (n = 285). We analyzed sleep architecture, AHI values, oxygen desaturation index (ODI; ≥3% dips·h⁻¹), and T90 (% sleep time with SpO₂<90%). Multivariable linear regression was used to assess the independent contribution of phenotype to cumulative nocturnal hypoxemia after adjusting for key confounders.
Results:
The REM-related group had the lowest AHITotal (6.3 ± 1.6) but a comorbidity profile indistinguishable from the stage-independent group (AHITotal=32.3 ± 25.4), where 43.5% had severe OSA. Mean nocturnal SpO₂ was comparable across phenotypes (p = 0.15). After adjustment, the phenotype independently predicted T90. Compared with the REM-related group, T90 was significantly lower in both the REM-aggravated (β=-15.6; p = 0.010) and stage-independent (β=-13.1; p = 0.016) groups. In contrast, phenotype was not associated with the ODI; this metric was influenced primarily by body weight (p = 0.004) and AHITotal (p < 0.001).
Conclusion:
REM-related OSA is a distinct phenotype where a low AHITotal underestimates risk, obscuring significant comorbidities and substantial cumulative hypoxemia. Time-based metrics such as T90, rather than event-based indices such as ODI, are essential for capturing physiological strain in this phenotype. These findings support moving beyond AHI-centric assessments toward a phenotype-specific diagnostic framework to improve risk stratification in OSA.
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