Examining Sleep‐Disordered Breathing Events Using Latent Profile Analysis

The clinical utility of the ratio of the apnea-hypopnea index (AHI) occurring during rapid eye movement (REM) and non-REM (NREM) sleep (AHI<sub>REM</sub>/AHI<sub>NREM</sub> ratio) has been debated. We investigated the heterogeneity of REM and NREM sleep behaviors to identify unobserved distinct subtypes of sleep-disordered breathing (SDB) and examine their demographic and clinical features. The present study used a sample of 3626 adult patients who underwent diagnostic polysomnography evaluations at the Sleep Disorders Center of King Abdulaziz Medical City in Riyadh, Saudi Arabia. Latent profile analysis was performed to categorize subjects into distinct profiles of SDB based on AHI<sub>REM</sub>, AHI<sub>NREM</sub>, and AHI<sub>REM</sub>/AHI<sub>NREM</sub> ratio. A multinomial logistic model estimated the odds ratio of SDB profiles. Four distinct subtypes of SDB were identified: Class I (low AHI<sub>REM</sub>; 75.9%) included patients with normal SDB events during REM sleep, serving as the reference group; Class II (REM-OSA, 1.2%) included patients with high AHI during REM sleep but lowest AHI during NREM sleep, resulting in the largest AHI<sub>REM</sub>/AHI<sub>NREM</sub> ratio; Class III (AHI<sub>NREM</sub> < 30 events per hour, 17.4%); and Class IV (AHI<sub>NREM</sub> ≥ 30 events per hour, 5.5%). Compared to Class I, factors related to Class IV included older age, high BMI, large neck circumference, hypertension, reduced total sleep time, reduced REM sleep, poor sleep efficiency, high desaturation index, low SpO2, high arousal index, and high Epworth Sleepiness Scale. As hypothesized, the study characterized several subtypes of SDB based on the AHI<sub>REM</sub>, AHI<sub>NREM</sub>, and their ratio (AHI<sub>REM</sub>/AHI<sub>NREM</sub>) in a large cohort and identified their demographic and clinical features. These subtypes might be clinically useful for defining SDB among adult patients referred to sleep clinics who may have varying responses to treatment depending on their subtype of the disease.

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Publication Details

Journal
Behavioural Neurology
Published
2025-01-01
DOI
https://doi.org/10.1155/bn/8848485
Primary Topic
Obstructive Sleep Apnea Research
Type
article
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article

Examining Sleep‐Disordered Breathing Events Using Latent Profile Analysis

Anwar Ahmed, A. Almuttari, Marina Weinberger, Hamdan Al‐Jahdali et al.
Behavioural Neurology
Obstructive Sleep Apnea Research
article

Examining Sleep‐Disordered Breathing Events Using Latent Profile Analysis

Anwar Ahmed, A. Almuttari, Marina Weinberger, Hamdan Al‐Jahdali, Abdullah Al-Harbi, J. Kent Werner, Hani A Alsaigh
article en

Abstract

The clinical utility of the ratio of the apnea-hypopnea index (AHI) occurring during rapid eye movement (REM) and non-REM (NREM) sleep (AHI<sub>REM</sub>/AHI<sub>NREM</sub> ratio) has been debated. We investigated the heterogeneity of REM and NREM sleep behaviors to identify unobserved distinct subtypes of sleep-disordered breathing (SDB) and examine their demographic and clinical features. The present study used a sample of 3626 adult patients who underwent diagnostic polysomnography evaluations at the Sleep Disorders Center of King Abdulaziz Medical City in Riyadh, Saudi Arabia. Latent profile analysis was performed to categorize subjects into distinct profiles of SDB based on AHI<sub>REM</sub>, AHI<sub>NREM</sub>, and AHI<sub>REM</sub>/AHI<sub>NREM</sub> ratio. A multinomial logistic model estimated the odds ratio of SDB profiles. Four distinct subtypes of SDB were identified: Class I (low AHI<sub>REM</sub>; 75.9%) included patients with normal SDB events during REM sleep, serving as the reference group; Class II (REM-OSA, 1.2%) included patients with high AHI during REM sleep but lowest AHI during NREM sleep, resulting in the largest AHI<sub>REM</sub>/AHI<sub>NREM</sub> ratio; Class III (AHI<sub>NREM</sub> < 30 events per hour, 17.4%); and Class IV (AHI<sub>NREM</sub> ≥ 30 events per hour, 5.5%). Compared to Class I, factors related to Class IV included older age, high BMI, large neck circumference, hypertension, reduced total sleep time, reduced REM sleep, poor sleep efficiency, high desaturation index, low SpO2, high arousal index, and high Epworth Sleepiness Scale. As hypothesized, the study characterized several subtypes of SDB based on the AHI<sub>REM</sub>, AHI<sub>NREM</sub>, and their ratio (AHI<sub>REM</sub>/AHI<sub>NREM</sub>) in a large cohort and identified their demographic and clinical features. These subtypes might be clinically useful for defining SDB among adult patients referred to sleep clinics who may have varying responses to treatment depending on their subtype of the disease.

Behavioural NeurologyVol. 2025(1)
Uniformed Services University of the Health Sciences (US), King Saud bin Abdulaziz University for Health Sciences (SA), King Abdullah International Medical Research Center (SA)
Openalex Percentile: Top 91%
Obstructive Sleep Apnea Research
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