Highlights d Anakinra treatment was administered to eight severe COVID-19 patients d All patients had secondary hemophagocytic lymphohistiocytosis d Respiratory function was improved at the end of treatment d In one patient, the need for mechanical ventilation was prevented

Conflict of interest:All authors have no potential conflict of interest to report. Verheggen et al. 2 ABSTRACTExercise training ("exercise") and hypocaloric diet ("diet") are frequently prescribed for weight loss in obesity. Whilst body weight changes are commonly used to evaluate lifestyle interventions, visceral adiposity (VAT) is a more relevant and stronger predictor for morbidity and mortality. We performed a meta-analysis to assess the effects of exercise training or hypocaloric diet on VAT (quantified by radiographic imaging). Relevant databases were searched through May 2014. 117 Studies (n=4,815) were included. We found that both exercise and diet cause VAT loss (P<0.0001). When comparing diet versus training, diet caused a larger weight loss (P=0.04). In contrast, a trend was observed towards a larger VAT decrease in exercise (P=0.08). Changes in weight and VAT showed a strong correlation after diet (R²=0.737, P<0.001), and a modest correlation after exercise (R²=0.451, P<0.001). In the absence of weight loss, exercise is related to 6.1% decrease in VAT, whilst diet showed virtually no change (1.1%). In conclusion, both exercise and diet reduce VAT. Despite a larger effect of diet on total body weight loss, exercise tends to have superior effects in reducing VAT. Finally, total body weight loss does not necessarily reflect changes in VAT and may represent a poor marker when evaluating benefits of lifestyle-interventions.

BackgroundThe Body Mass Index (BMI) and Waist Circumference (WC) are well-used anthropometric predictors for cardiovascular diseases (CVD), but their validity is regularly questioned. Recently, A Body Shape Index (ABSI) and Body Roundness Index (BRI) were introduced as alternative anthropometric indices that may better reflect health status.ObjectiveThis study assessed the capacity of ABSI and BRI in identifying cardiovascular diseases and cardiovascular disease risk factors and determined whether they are superior to BMI and WC.Design and Methods4627 Participants (54±12 years) of the Nijmegen Exercise Study completed an online questionnaire concerning CVD health status (defined as history of CVD or CVD risk factors) and anthropometric characteristics. Quintiles of ABSI, BRI, BMI, and WC were used regarding CVD prevalence. Odds ratios (OR), adjusted for age, sex, and smoking, were calculated per anthropometric index.Results1332 participants (27.7%) reported presence of CVD or CVD risk factors. The prevalence of CVD increased across quintiles for BMI, ABSI, BRI, and WC. Comparing the lowest with the highest quintile, adjusted OR (95% CI) for CVD were significantly different for BRI 3.2 (1.4–7.2), BMI 2.4 (1.9–3.1), and WC 3.0 (1.6–5.6). The adjusted OR (95% CI) for CVD risk factors was for BRI 2.5 (2.0–3.3), BMI 3.3 (1.6–6.8), and WC 2.0 (1.6–2.5). No association was observed for ABSI in both groups.ConclusionsBRI, BMI, and WC are able to determine CVD presence, while ABSI is not capable. Nevertheless, the capacity of BRI as a novel body index to identify CVD was not superior compared to established anthropometric indices like BMI and WC.

Background: Physical activity is known to influence sleep efficiency. Relatively little is known about the relationship between physical activity and sleep efficiency in young and older humans and the impact of exercise training on sleep efficiency in healthy older individuals. Objectives: To determine the relationship between physical fitness and daily energy expenditure with sleep efficiency in young and older subjects, and assess the effect of 12-month exercise training on sleep efficiency in healthy older participants. Methods: The relationship between physical fitness (maximal cycling test) and daily energy expenditure (accelerometry) with sleep efficiency (accelerometry) was examined cross-sectionally in 12 healthy young adults (27 ± 5 years) and 21 healthy older participants (69 ± 3 years). Subsequently, the effect of 12-month exercise training (n = 11) or control period (n = 10) on sleep efficiency in older participants was examined using a randomized controlled trial. Results: Daily energy expenditure and sleep efficiency did not differ between young and older subjects. A significant correlation was found between energy expenditure and sleep efficiency (r = 0.627, p = 0.029) in young adults, but not in older participants (r = –0.158, p = 0.49). Physical fitness did not correlate with sleep efficiency in either group. Exercise training significantly improved physical fitness (15.0%, p < 0.001), but failed to alter sleep characteristics such as sleep efficiency, sleep onset latency and awakenings. Conclusions: We found that young adults with higher daily energy expenditure have greater sleep efficiency, whilst this relationship is diminished with advanced age. In contrast, we found no correlation between physical fitness and sleep characteristics in healthy young or older participants, which may explain the lack of improvement in sleep characteristics in older participants with 12-month exercise training. Exercise training may be more successful in subjects with existing sleep disturbancesto improve sleep characteristics rather than in healthy older subjects.

Statin use attenuated substrate use during maximal exercise performance, induced muscle fatigue during repeated muscle contractions, and decreased muscle mitochondrial oxidative capacity. This suggests disturbances in mitochondrial oxidative capacity occur with statin use even in patients without statin-induced muscle complaints.