Sleep apnoea svndrome (SAS) is a largely undiagnosed and prevalent disorder. It is associated with cardiovascular morbidity as well as excessive daytime sleepiness and poor quality of life. In the present study the SleepStrip, a novel screening device is introduced, which is low cost and easy to use and is aimed for widespread use. The results of three independent validation studies, which compared the SleepStrip score (Sscore) against "gold standard" polysomnographically-determined apnoea/ hypopnoea index (AHI), are reported both separately and combined. Four hundred and two patients suspected of SAS underwent full polysomnography recordings concomitantly with the use of the SleepStrip. For all samples combined, the correlation between AHI and Sscore was r=0.73, sensitivity and specificity values ranged from 80-86% and 57-86% respectively, and the area under the curve derived from receiver-operating characteristic curves ranged from 0.81-0.92 at varying AHI thresholds. Though not intended as a substitute for polysomnography, the SleepStrip may provide initial screening information, which may be useful in both clinical and experimental settings.
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http://dx.doi.org/10.1183/09031936.02.00227302 | DOI Listing |
Sleep Epidemiol
December 2024
Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA.
Objective: To examine longitudinal associations between self-reported sleep disturbances and mobility disability progression among women, including subgroups with multiple sclerosis (MS), diabetes, and osteoarthritis (OA).
Methods: Prospective cohort study using data from Nurses' Health Study long-form questionnaires (2008, 2012, 2014, 2016). Logistic regression was used to quantify associations between sleep-related variables at baseline and subsequent increase in mobility disability.
J Intensive Med
October 2024
Intensive Care Unit, Hospital Morales Meseguer, Murcia, Spain.
Recently, there has been growing interest in knowing the best hygrometry level during high-flow nasal oxygen and non-invasive ventilation (NIV) and its potential influence on the outcome. Various studies have shown that breathing cold and dry air results in excessive water loss by nasal mucosa, reduced mucociliary clearance, increased airway resistance, reduced epithelial cell function, increased inflammation, sloughing of tracheal epithelium, and submucosal inflammation. With the Coronavirus Disease 2019 pandemic, using high-flow nasal oxygen with a heated humidifier has become an emerging form of non-invasive support among clinicians.
View Article and Find Full Text PDFSleep Breath
January 2025
Akureyri Junior College, Akureyri, Iceland.
Objectives: Sleep is often compromised in adolescents, affecting their health and quality of life. This pilot-study was conducted to evaluate if implementing brief-behavioral and sleep-hygiene education with mindfulness intervention may positively affect sleep-health in adolescents.
Method: Participants in this community-based non-randomized cohort-study volunteered for intervention (IG)- or control-group (CG).
Sleep Breath
January 2025
Department of Health Research Methods, Evidence and Impact (HEI), McMaster University, Hamilton, ON, Canada.
Purpose: A high proportion of obstructive sleep apnea (OSA) remains undiagnosed. The main objectives of this study were to measure the prevalence of diagnosed OSA and determine OSA predictors in patients who underwent bariatric surgery, who are predominantly female and pre-menopausal and represent an understudied population in OSA literature.
Methods: This was a cross-sectional population-based study using the Ontario Bariatric Registry (OBR) from 2010 to 2016, linked to ICES databases which include health administrative data on all encounters within a single public-payer system.
Sleep
January 2025
Courant Institute of Mathematical Sciences, New York University, New York, 10012, USA.
Study Objectives: This paper validates TipTraQ, a compact home sleep apnea testing (HSAT) system. TipTraQ comprises a fingertip-worn device, a mobile application, and a cloud-based deep learning artificial intelligence (AI) system. The device utilizes PPG (red, infrared, and green channels) and accelerometer sensors to assess sleep apnea by the AI system.
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