Night‐to‐night variability of obstructive sleep apnea

Stöberl, Anna S.; Schwarz, Esther I.; Haile, Sarah R.; Turnbull, Chris D.; Rossi, Valentina A.; Stradling, John; Kohler, Malcolm

doi:10.1111/jsr.12558

Cited by 88 publications

(64 citation statements)

References 32 publications

(49 reference statements)

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“…29 Another explanation for the aforementioned differences in baseline measurements could be night-to-night variability. 44 This phenomenon can be explained by both the so-called "firstnight effect" and intrinsic variability. 45,46 Intrinsic variability can be divided into variables such as behavioral factors, differences in body position, and sleep architecture between recordings.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of a Trial Period With a Sleep Position Trainer in Patients With Positional Sleep Apnea

Beyers

Dieltjens

Kastoer

et al. 2018

Journal of Clinical Sleep Medicine

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Section: Discussionmentioning

confidence: 99%

Evaluation of a Trial Period With a Sleep Position Trainer in Patients With Positional Sleep Apnea

Beyers

Dieltjens

Kastoer

et al. 2018

Journal of Clinical Sleep Medicine

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show abstract

“…The quest for a quantified index of respiratory events as a meas- Sixth, how many consecutive nights must be monitored to yield a reliable AHI (Crinion et al, 2020;Le Bon et al, 2000;Prasad et al, 2016;Stoberl et al, 2017)? And, finally, should the procedure be performed in the sleep laboratory or at home ( Apnea A cessation of airflow at the nose and mouth lasting at least 10 s.…”

Section: Methodological Issuesmentioning

confidence: 99%

On the rise and fall of the apnea−hypopnea index: A historical review and critical appraisal

Pevernagie

Gnidovec-Stražišar

Grote

et al. 2020

Journal of Sleep Research

195

134

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The publication of "The Sleep Apnea Syndromes" by Guilleminault et al. in the 1970s hallmarked the discovery of a new disease entity involving serious health consequences. Obstructive sleep apnea was shown to be the most important disorder among the sleep apnea syndromes (SAS). In the course of time, it was found that the prevalence of obstructive sleep apnea reached the proportions of a global epidemic, with a major impact on public health, safety and the economy. Early on, a metric was introduced to gauge the seriousness of obstructive sleep apnea, based on the objective measurement of respiratory events during nocturnal sleep. The apnea index and later on the apnea−hypopnea index, being the total count of overnight respiratory events divided by the total sleep time in hours, were embraced as principle measures to establish the diagnosis of obstructive sleep apnea and to rate its severity. The current review summarises the historical evolution of the apnea−hypopnea index, which has been subject to many changes, and has been criticised for not capturing relevant clinical features of obstructive sleep apnea. In fact, the application of

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“…4G-H) (32). Taken together, these data demonstrate that Bedscales can perform high fidelity monitoring of normal and pathologic respiratory dynamics and their hemodynamic consequences without the need for obtrusive adherence-dependent sensors and may allow longitudinal characterization of recently reported night-to-night variability (33,34).…”

Section: Sleep Study and Apnea Monitoringmentioning

confidence: 59%

Bedscales: A non-contact adherence-independent multi-person sensor for longitudinal physiologic monitoring in the home bed

Harrington

Wei

Hernandez-Pacheco

et al. 2020

Preprint

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Home health monitoring technologies promise to improve care and reduce costs, yet they are limited by the need for adherence to self-monitoring, usage of an app, or application of a wearable. While implantable sensors overcome the adherence barrier, they are expensive and require invasive procedures. Here, we describe a non-invasive, non-contact, adherence-independent sensor, that when placed beneath the legs of a patient's home bed, longitudinally monitors total body weight, detailed respiratory signals, and ballistocardiograms for months, without requiring any active patient participation.Accompanying algorithms demix weight and respiratory signals when the bed is shared by a partner or a pet. Validation studies during overnight clinical sleep studies exhibit quantitative equivalence to commercial sensors and allow discrimination of obstructive and central sleep apneas. In-home studies discriminate atrial fibrillation from normal sinus rhythm. To demonstrate real-world feasibility, we performed 3 months of continuous in-home monitoring in a patient with heart failure as he awaited and recovered from coronary artery bypass surgery. By overcoming the adherence barrier, Bedscales has the potential to create a multidimensional picture of chronic disease, learn signatures of impending hospitalization, and enable optimization of care in the home.

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Night‐to‐night variability of obstructive sleep apnea

Abstract: www.controlled-trials.com (ISRCTN 93153804, ISRCTN 73047833) and www.clinicaltrials.gov (NCT01332175 & NCT02050425).

Cited by 88 publications

References 32 publications

Evaluation of a Trial Period With a Sleep Position Trainer in Patients With Positional Sleep Apnea

Evaluation of a Trial Period With a Sleep Position Trainer in Patients With Positional Sleep Apnea

On the rise and fall of the apnea−hypopnea index: A historical review and critical appraisal

Bedscales: A non-contact adherence-independent multi-person sensor for longitudinal physiologic monitoring in the home bed

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