Publications by authors named "J Pepin"

Cardiac implantable electronic devices and their integrated thoracic impedance sensors have been used to detect sleep apnea for over a decade now. Despite their usage in daily clinical practice, there are only limited data on their diagnostic accuracy. AIRLESS and UPGRADE were prospective investigator-driven trials meant to validate the AP scan (Boston Scientific, Marlborough, MA, USA) in heart failure cohorts.

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: This study determined real-life care trajectories before and after initiation of noninvasive ventilation (NIV) in patients with amyotrophic lateral sclerosis (ALS). Caregiver adherence to respiratory management recommendations and the associated survival rate of people with ALS were also assessed. : Data were obtained from a tertiary center prospective ALS database that included 10 years of follow-up data for people with ALS.

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Background: A large number of symptomatic individuals with central sleep apnea (CSA) in clinical practice have an indication for adaptive servo-ventilation (ASV) therapy.

Research Question: What are the effects of ASV therapy on sleep quality and PROMs in patients with CSA across a range of devices and indications.

Methods: This prospective, multicenter, observational cohort study was conducted in France and enrolled participants from June 2017 to February 2020.

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Obstructive sleep apnoea (OSA) contributes to cerebrovascular diseases and cognitive decline. Preclinical studies support the deleterious impact on the brain of intermittent hypoxia (IH), one of the main components of OSA, but heterogeneity in rodent species and brain regions studied, or induced by IH paradigms, can challenge interpretation of the studies. Hence, we conducted a systematic review and meta-analysis to evaluate the impact of IH on rodent brain oxidative stress, inflammation, apoptosis and the expression of brain-derived neurotrophic factor (BDNF) and hypoxia-inducible factor 1 (HIF-1).

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Background: Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder for which the identification of phenotypes might help for risk stratification for long-term mortality. Thus, the aim of the study was to identify distinct phenotypes of OSA and to study the association of phenotypes features with long-term mortality by using machine learning.

Methods: This retrospective study included patients diagnosed with OSA who completed a 15-year follow-up and were adherent to continuous positive airway pressure (CPAP) therapy.

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