Sex-specific impact of severe obesity in the outcomes of hospitalized patients with COVID-19: a large retrospective study from the Bronx,New York

It has been demonstrated that obesity is an independent risk factor for worse outcomes in patients with COVID-19. Our objectives were to investigate which classes of obesity are associated with higher in-hospital mortality and to assess the association between obesity and systemic inflammation. This was a retrospective study which included consecutive hospitalized patients with COVID-19 in a tertiary center. Three thousand five hundred thirty patients were included in this analysis (female sex: 1579, median age: 65 years). The median body mass index (BMI) was 28.8 kg/m². In the overall cohort, a J-shaped association between BMI and in-hospital mortality was depicted. In the subgroup of men, BMI 35–39.9 kg/m² and BMI ≥40 kg/m² were found to have significant association with higher in-hospital mortality, while only BMI ≥40 kg/m² was found significant in the subgroup of women. No significant association between BMI and IL-6 was noted. Obesity classes II and III in men and obesity class III in women were independently associated with higher in-hospital mortality in patients with COVID-19. The male population with severe obesity was the one that mainly drove this association. No significant association between BMI and IL-6 was noted.

     

Performance of seven consumer sleep-tracking devices compared with polysomnography

Study ObjectivesConsumer sleep-tracking devices are widely used and becoming more technologically advanced, creating strong interest from researchers and clinicians for their possible use as alternatives to standard actigraphy. We, therefore, tested the performance of many of the latest consumer sleep-tracking devices, alongside actigraphy, versus the gold-standard sleep assessment technique, polysomnography (PSG).MethodsIn total, 34 healthy young adults (22 women; 28.1 ± 3.9 years, mean ± SD) were tested on three consecutive nights (including a disrupted sleep condition) in a sleep laboratory with PSG, along with actigraphy (Philips Respironics Actiwatch 2) and a subset of consumer sleep-tracking devices. Altogether, four wearable (Fatigue Science Readiband, Fitbit Alta HR, Garmin Fenix 5S, Garmin Vivosmart 3) and three nonwearable (EarlySense Live, ResMed S+, SleepScore Max) devices were tested. Sleep/wake summary and epoch-by-epoch agreement measures were compared with PSG.ResultsMost devices (Fatigue Science Readiband, Fitbit Alta HR, EarlySense Live, ResMed S+, SleepScore Max) performed as well as or better than actigraphy on sleep/wake performance measures, while the Garmin devices performed worse. Overall, epoch-by-epoch sensitivity was high (all ≥0.93), specificity was low-to-medium (0.18–0.54), sleep stage comparisons were mixed, and devices tended to perform worse on nights with poorer/disrupted sleep.ConclusionsConsumer sleep-tracking devices exhibited high performance in detecting sleep, and most performed equivalent to (or better than) actigraphy in detecting wake. Device sleep stage assessments were inconsistent. Findings indicate that many newer sleep-tracking devices demonstrate promising performance for tracking sleep and wake. Devices should be tested in different populations and settings to further examine their wider validity and utility.     

Fibrosis-5 predicts end-stage renal disease in patients with microscopic polyangiitis and granulomatosis with polyangiitis without substantial liver diseases

Clinical and Experimental Medicine - We previously reported that fibrosis-4 (FIB-4) was associated with poor outcomes of microscopic polyangiitis (MPA) and granuloma with polyangiitis (GPA). We...     

The H2020 “NoHoW Project”: A Position Statement on Behavioural Approaches to Longer-Term Weight Management

There is substantial evidence documenting the effects of behavioural interventions on weight loss (WL). However, behavioural approaches to initial WL are followed by some degree of longer-term weight regain, and large trials focusing on evidence-based approaches to weight loss maintenance (WLM) have generally only demonstrated small beneficial effects. The current state-of-the-art in behavioural interventions for WL and WLM raises questions of (i) how we define the relationship between WL and WLM, (ii) how energy balance (EB) systems respond to WL and influence behaviours that primarily drive weight regain, (iii) how intervention content, mode of delivery and intensity should be targeted to keep weight off, (iv) which mechanisms of action in complex interventions may prevent weight regain and (v) how to design studies and interventions to maximise effective longer-term weight management. In considering these issues a writing team within the NoHoW Consortium was convened to elaborate a position statement, and behaviour change and obesity experts were invited to discuss these positions and to refine them. At present the evidence suggests that developing the skills to self-manage EB behaviours leads to more effective WLM. However, the effects of behaviour change interventions for WL and WLM are still relatively modest and our understanding of the factors that disrupt and undermine self-management of eating and physical activity is limited. These factors include physiological resistance to weight loss, gradual compensatory changes in eating and physical activity and reactive processes related to stress, emotions, rewards and desires that meet psychological needs. Better matching of evidence-based intervention content to quantitatively tracked EB behaviours and the specific needs of individuals may improve outcomes. Improving objective longitudinal tracking of energy intake and energy expenditure over time would provide a quantitative framework in which to understand the dynamics of behaviour change, mechanisms of action of behaviour change interventions and user engagement with intervention components to potentially improve weight management intervention design and evaluation.