Person-specific and pooled prediction models for binge eating, alcohol use and binge drinking in bulimia nervosa and alcohol use disorder.

BACKGROUND: Machine learning could predict binge behavior and help develop treatments for bulimia nervosa (BN) and alcohol use disorder (AUD). Therefore, this study evaluates person-specific and pooled prediction models for binge eating (BE), alcohol use, and binge drinking (BD) in daily life, and identifies the most important predictors. METHODS: A total of 120 patients (BN: 50; AUD: 51; BN/AUD: 19) participated in an experience sampling study, where over a period of 12 months they reported on their eating and drinking behaviors as well as on several other emotional, behavioral, and contextual factors in daily life. The study had a burst-measurement design, where assessments occurred eight times a day on Thursdays, Fridays, and Saturdays in seven bursts of three weeks. Afterwards, person-specific and pooled models were fit with elastic net regularized regression and evaluated with cross-validation. From these models, the variables with the 10% highest estimates were identified. RESULTS: The person-specific models had a median AUC of 0.61, 0.80, and 0.85 for BE, alcohol use, and BD respectively, while the pooled models had a median AUC of 0.70, 0.90, and 0.93. The most important predictors across the behaviors were craving and time of day. However, predictors concerning social context and affect differed among BE, alcohol use, and BD. CONCLUSIONS: Pooled models outperformed person-specific models and the models for alcohol use and BD outperformed those for BE. Future studies should explore how the performance of these models can be improved and how they can be used to deliver interventions in daily life.

The impact of COVID-19-related smell and taste disorders on a patient with bulimia nervosa: a case report.

A large number of patients with COVID-19 will suffer from long-term smell and taste disorders (STD). These STD symptoms could have a significant impact on patients with an eating disorder (ED). To highlight this issue, a case is presented of a patient with bulimia nervosa who experienced COVID-19-relate STD symptoms. Clinicians should reassess patients with an ED who suffer from COVID-19 with STD symptomatology and potentially redirect treatment. More research is needed on STD symptoms in patients with an ED to improve our knowledge on the role of smell and taste in disordered eating behaviors and improve treatment guidelines.

Association between cerebral cannabinoid 1 receptor availability and body mass index in patients with food intake disorders and healthy subjects: a [(18)F]MK-9470 PET study.

Although of great public health relevance, the mechanisms underlying disordered eating behavior and body weight regulation remain insufficiently understood. Compelling preclinical evidence corroborates a critical role of the endocannabinoid system (ECS) in the central regulation of appetite and food intake. However, in vivo human evidence on ECS functioning in brain circuits involved in food intake regulation as well as its relationship with body weight is lacking, both in health and disease. Here, we measured cannabinoid 1 receptor (CB1R) availability using positron emission tomography (PET) with [(18)F]MK-9470 in 54 patients with food intake disorders (FID) covering a wide body mass index (BMI) range (anorexia nervosa, bulimia nervosa, functional dyspepsia with weight loss and obesity; BMI range=12.5-40.6 kg/m(2)) and 26 age-, gender- and average BMI-matched healthy subjects (BMI range=18.5-26.6 kg/m(2)). The association between regional CB1R availability and BMI was assessed within predefined homeostatic and reward-related regions of interest using voxel-based linear regression analyses. CB1R availability was inversely associated with BMI in homeostatic brain regions such as the hypothalamus and brainstem areas in both patients with FID and healthy subjects. However, in FID patients, CB1R availability was also negatively correlated with BMI throughout the mesolimbic reward system (midbrain, striatum, insula, amygdala and orbitofrontal cortex), which constitutes the key circuit implicated in processing appetitive motivation and hedonic value of perceived food rewards. Our results indicate that the cerebral homeostatic CB1R system is inextricably linked to BMI, with additional involvement of reward areas under conditions of disordered body weight.