Centre for Heart Rhythm Disorders, University of Adelaide, Adelaide, Australia; Department of Cardiology, Royal Adelaide Hospital, Adelaide, Australia. Electronic address: prash.sanders@adelaide.edu.au.
Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Clinical Pharmacology, Research Center of Medical Sciences, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China.
Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Clinical Pharmacology, Research Center of Medical Sciences, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China.
Department of Medicine and Research Center Montreal Heart Institute and Université de Montréal, Montréal, Québec, Canada; Department of Cardiology, University Hospital of Saint-Étienne, University Jean Monnet, Saint-Étienne, France.
Department of Medicine and Research Center Montreal Heart Institute and Université de Montréal, Montréal, Québec, Canada; Department of Pharmacology and Therapeutics, McGill University Montréal, Montréal, Québec, Canada; Institute of Pharmacology, West German Heart and Vascular Center, Faculty of Medicine, University Duisburg-Essen, Essen, Germany; IHU LIRYC and Fondation Bordeaux Université, Bordeaux, France. Electronic address: stanley.nattel@icm-mhi.org.
Department of Cardiac Sciences, Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
Department of Physiology and Pharmacology, Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
Department of Cardiac Sciences, Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
Department of Physiology and Pharmacology, Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
Since the release of the contrastive language-image pre-training (CLIP) model designed by the OpenAI team, it has been applied in several fields owing to its high accuracy. Sleep staging is an importa...
Obstructive sleep apnea (OSA) is associated with polycystic ovarian syndrome (PCOS), a common cause of infertility. Understanding predictors and outcomes of OSA in women with infertility may guide tre...
A descriptive cross-sectional survey was performed to assess OSA in women presenting to an infertility clinic using validated sleep questionnaires to assess sleep and fertility outcomes. An Infertile-...
In 258 women, occurrences of OSA diagnosis (6%) and RLS (10%) were reported similar to women of child-bearing age in the general population. PCOS was unassociated with OSA risk. Predictors of OSA risk...
Similar to other populations, women with infertility and OSA risk have more health comorbidities and higher BMI and may present with insomnia symptoms. While the data are limited, this study supports ...
Tandem Control-IQ is an advanced hybrid closed loop (AHCL) system with a Sleep Activity Mode to intensify glycemic control overnight. The aim of the study is to evaluate the effectiveness of using Sle...
We performed a retrospective Tandem Control-IQ data download for patients followed at IRCCS G. Gaslini Pediatric Diabetes Centre. We divided the patients into group 1 (Sleep Mode users) and group 2 (n...
Group 1 (...
This is the first study that evaluates the real-life effectiveness of the use of Sleep Mode in young patients with T1D. Control-IQ Sleep Activity Mode may not be as effective in Italian patients as in...
To investigate sleep quality in juvenile fibromyalgia syndrome (JFS) and its effect on the global burden of the disease....
Consecutive patients with JFS who performed full-night polysomnography (PSG) were included in this cross-sectional study. JFS-related symptoms, neuropsychiatric features, and sleep quality were assess...
We included 25 patients (20 females, median age 15.7 yrs). Nonrestorative sleep was reported by 22 of 25 (88%) patients. Patients with JFS showed significantly longer sleep period time (...
Sleep complaints are a key hallmark of JFS and have significant effect on relevant clinical domains of the disease, such as pain and depression....
Sleep fragmentation determined by repetitive arousals from sleep in obstructive sleep apnea (OSA) is associated with hypertension. We aimed to quantify the independent association of arousals during r...
We included adults with 4 h of total sleep time and at least 30 min of REM sleep obtained from overnight in-laboratory polysomnography. Logistic regression models were fitted to explore the associatio...
The sample comprised of 11 643 patients, of which 10 055 were OSA patients. Fully adjusted models demonstrated significant dose-relationships between arousal index during REM sleep (AI-REM) and preval...
Our findings indicate that arousals during REM sleep are associated with prevalent hypertension. This is clinically relevant because treatment of OSA is often limited to the first half of the sleep pe...
Although many people suffer from sleep disorders, most are undiagnosed, leading to impairments in health. The existing polysomnography method is not easily accessible; it's costly, burdensome to patie...
Current evidence points to the importance of sleep for adolescent physical and mental health. To date, most studies have examined the association between sleep duration/quality and health in adolescen...
Almost one billion people worldwide are affected by Obstructive Sleep Apnea (OSA). Affected individuals experience disordered breathing patterns during sleep, which results in fatigue, daytime drowsin...
Patient-generated health data are important in the management of several diseases. Although there are limitations, information can be obtained using a wearable device and time-related information such...
To effectively use patient-generated health data related to time such as sleep, it is first necessary to understand the characteristics of the time response recorded by the user. Therefore, the aim of...
Sleep data were acquired for 2 weeks using a Fitbit. Participants' sleep records were collected daily through chatbot conversations while wearing the Fitbit, and the two sets of data were statisticall...
In total, 736 people aged 30-59 years were recruited for this study, and the sleep data of 543 people who wore a Fitbit and responded to the chatbot for more than 7 days on the same day were analyzed....
The chatbot sleep response and Fitbit measured time were similar on average and the study participants had a slight tendency to perceive a relatively long sleep time if the quality of sleep was self-r...
Depression, poor sleep duration and low self-efficacy are common in mothers of children with sleep problems. However, research rarely extends beyond the postpartum period. This study investigated the ...
