WELCOME : improving WEight controL and CO-Morbidities in children with obesity via Executive function training : study protocol for a randomized controlled trial

Background: Obesity is a widespread problem that not only leads to medical and psychological diseases in adults, but also in children and adolescents at an early stage in life. Because of its global burden on both the individual and society, it is necessary to develop effective evidence-based treatments. Current " Multidisciplinary Obesity Treatments" (MOT) already provide significant weight loss, but still leave room for more long-lasting improvements. In this protocol paper, we outline the research goals of the WELCOME trial, based on a substantial proof of concept. Methods: In this Randomized Controlled Trial (RCT) - conducted in both an inpatient and two outpatient treatment settings -existing MOT will be supplemented with an Executive Function (EF) training and compare effects on various parameters in an experimental versus an active control group of obese youngsters (8-18 years old). WELCOME aims to (a) train youngsters' executive functions to facilitate effects on weight loss, psychological and medical comorbidities, (b) to enhance the long-term effects by continuing the training in the daily home context with booster sessions, and (c) to investigate its effects until a 6-month follow-up. In comparison to the active control group, better progress is expected in the experimental group on following variables: weight, psychological comorbidities (unhealthy eating behavior, internalizing symptoms, impaired self-esteem) and medical comorbidities (metabolic syndromes, endothelia dysfunction, tonsillar hypertrophy and sleep obstruction). Discussion: It is stated that this EF-training for enhancing self-control abilities is necessary for a long-lasting effect of childhood obesity treatment interventions

Abnormalities in autonomic function in obese boys at-risk for insulin resistance and obstructive sleep apnea.

Study objectivesCurrent evidence in adults suggests that, independent of obesity, obstructive sleep apnea (OSA) can lead to autonomic dysfunction and impaired glucose metabolism, but these relationships are less clear in children. The purpose of this study was to investigate the associations among OSA, glucose metabolism, and daytime autonomic function in obese pediatric subjects.MethodsTwenty-three obese boys participated in: overnight polysomnography; a frequently sampled intravenous glucose tolerance test; and recordings of spontaneous cardiorespiratory data in both the supine (baseline) and standing (sympathetic stimulus) postures.ResultsBaseline systolic blood pressure and reactivity of low-frequency heart rate variability to postural stress correlated with insulin resistance, increased fasting glucose, and reduced beta-cell function, but not OSA severity. Baroreflex sensitivity reactivity was reduced with sleep fragmentation, but only for subjects with low insulin sensitivity and/or low first-phase insulin response to glucose.ConclusionsThese findings suggest that vascular sympathetic activity impairment is more strongly affected by metabolic dysfunction than by OSA severity, while blunted vagal autonomic function associated with sleep fragmentation in OSA is enhanced when metabolic dysfunction is also present

Nocturnal Oximetry-based Evaluation of Habitually Snoring Children

Rationale: The vast majority of children around the world undergoing adenotonsillectomy for obstructive sleep apnea–hypopnea syndrome (OSA) are not objectively diagnosed by nocturnal polysomnography because of access availability and cost issues. Automated analysis of nocturnal oximetry (nSpO2), which is readily and globally available, could potentially provide a reliable and convenient diagnostic approach for pediatric OSA. Methods: DeidentifiednSpO2 recordings froma total of 4,191 children originating from13 pediatric sleep laboratories around the worldwere prospectively evaluated after developing and validating an automated neural network algorithm using an initial set of single-channel nSpO2 recordings from 589 patients referred for suspected OSA. Measurements and Main Results: The automatically estimated apnea–hypopnea index (AHI) showed high agreement with AHI from conventional polysomnography (intraclass correlation coefficient, 0.785) when tested in 3,602 additional subjects. Further assessment on the widely used AHI cutoff points of 1, 5, and 10 events/h revealed an incremental diagnostic ability (75.2, 81.7, and 90.2% accuracy; 0.788, 0.854, and 0.913 area under the receiver operating characteristic curve, respectively). Conclusions: Neural network–based automated analyses of nSpO2 recordings provide accurate identification of OSA severity among habitually snoring children with a high pretest probability of OSA. Thus, nocturnal oximetry may enable a simple and effective diagnostic alternative to nocturnal polysomnography, leading to more timely interventions and potentially improved outcomes.Supported in part by project VA037 U16 from the Consejer´ıa de Educacio´ n de la Junta de Castilla y Leo´ n and the European Regional Development Fund (FEDER), project RTC-2015-3446-1 from the Ministerio de Econom´ıa y Competitividad and FEDER, and project 153/2015 of the Sociedad Espan˜ ola de Neumolog´ıa y Cirug´ıa Tora´ cica (SEPAR). L.K.-G. is supported by NIH grant 1R01HL130984. M.F.P. was supported by a Fellowship Educational grant award from the Kingdom of Saudi Arabia. D.´A. was in receipt of a Juan de la Cierva grant from the Ministerio de Econom´ıa y Competitividad. The funders played no role in the study design, data collection, data analysis, interpretation, and writing of the manuscript

Nocturnal Oximetry-based Evaluation of Habitually Snoring Children

Rationale: The vast majority of children around the world undergoing adenotonsillectomy for obstructive sleep apnea–hypopnea syndrome (OSA) are not objectively diagnosed by nocturnal polysomnography because of access availability and cost issues. Automated analysis of nocturnal oximetry (nSpO2), which is readily and globally available, could potentially provide a reliable and convenient diagnostic approach for pediatric OSA. Methods: DeidentifiednSpO2 recordings froma total of 4,191 children originating from13 pediatric sleep laboratories around the worldwere prospectively evaluated after developing and validating an automated neural network algorithm using an initial set of single-channel nSpO2 recordings from 589 patients referred for suspected OSA. Measurements and Main Results: The automatically estimated apnea–hypopnea index (AHI) showed high agreement with AHI from conventional polysomnography (intraclass correlation coefficient, 0.785) when tested in 3,602 additional subjects. Further assessment on the widely used AHI cutoff points of 1, 5, and 10 events/h revealed an incremental diagnostic ability (75.2, 81.7, and 90.2% accuracy; 0.788, 0.854, and 0.913 area under the receiver operating characteristic curve, respectively). Conclusions: Neural network–based automated analyses of nSpO2 recordings provide accurate identification of OSA severity among habitually snoring children with a high pretest probability of OSA. Thus, nocturnal oximetry may enable a simple and effective diagnostic alternative to nocturnal polysomnography, leading to more timely interventions and potentially improved outcomes.Supported in part by project VA037 U16 from the Consejer´ıa de Educacio´ n de la Junta de Castilla y Leo´ n and the European Regional Development Fund (FEDER), project RTC-2015-3446-1 from the Ministerio de Econom´ıa y Competitividad and FEDER, and project 153/2015 of the Sociedad Espan˜ ola de Neumolog´ıa y Cirug´ıa Tora´ cica (SEPAR). L.K.-G. is supported by NIH grant 1R01HL130984. M.F.P. was supported by a Fellowship Educational grant award from the Kingdom of Saudi Arabia. D.´A. was in receipt of a Juan de la Cierva grant from the Ministerio de Econom´ıa y Competitividad. The funders played no role in the study design, data collection, data analysis, interpretation, and writing of the manuscript

Eating disorders in weight-related therapy (EDIT): protocol for a systematic review with individual participant data meta-analysis of eating disorder risk in behavioural weight management

The Eating Disorders In weight-related Therapy (EDIT) Collaboration brings together data from randomised controlled trials of behavioural weight management interventions to identify individual participant risk factors and intervention strategies that contribute to eating disorder risk. We present a protocol for a systematic review and individual participant data (IPD) meta-analysis which aims to identify participants at risk of developing eating disorders, or related symptoms, during or after weight management interventions conducted in adolescents or adults with overweight or obesity. We systematically searched four databases up to March 2022 and clinical trials registries to May 2022 to identify randomised controlled trials of weight management interventions conducted in adolescents or adults with overweight or obesity that measured eating disorder risk at pre- and post-intervention or follow-up. Authors from eligible trials have been invited to share their deidentified IPD. Two IPD meta-analyses will be conducted. The first IPD meta-analysis aims to examine participant level factors associated with a change in eating disorder scores during and following a weight management intervention. To do this we will examine baseline variables that predict change in eating disorder risk within intervention arms. The second IPD meta-analysis aims to assess whether there are participant level factors that predict whether participation in an intervention is more or less likely than no intervention to lead to a change in eating disorder risk. To do this, we will examine if there are differences in predictors of eating disorder risk between intervention and no-treatment control arms. The primary outcome will be a standardised mean difference in global eating disorder score from baseline to immediately post-intervention and at 6- and 12- months follow-up. Identifying participant level risk factors predicting eating disorder risk will inform screening and monitoring protocols to allow early identification and intervention for those at risk