Prediction of resting energy expenditure for adolescents with severe obesity: A multi-centre analysis.

BACKGROUND AND OBJECTIVES: Resting energy expenditure (REE) assessments can help inform clinical treatment decisions in adolescents with elevated body mass index (BMI), but current equations are suboptimal for severe obesity. We developed a predictive REE equation for youth with severe obesity and obesity-related comorbidities and compared results to previously published predictive equations. METHODS: Data from indirect calorimetry, clinical measures, and body composition per Dual x-ray absorptiometry (DXA) were collected from five sites. Data were randomly divided into development (N = 438) and validation (N = 118) cohorts. A predictive equation was developed using Elastic Net regression, using sex, race, ethnicity, weight, height, BMI percent of the 95th%ile (BMIp95), waist circumference, hip circumference, waist/hip ratio, age, Tanner stage, fat and fat-free mass. This equation was verified in the validation cohort and compared with 11 prior equations. RESULTS: Data from the total cohort (n = 556, age 15 ± 1.7 years, 77% female, BMIp95 3.3 ± 0.94) were utilized. The best fit equation was REE = -2048 + 18.17 × (Height in cm) - 2.57 × (Weight in kg) + 7.88 × (BMIp95) + 189 × (1 = male, 0 = female), R2 = 0.466, and mean bias of 23 kcal/day. CONCLUSION: This new equation provides an updated REE prediction that accounts for severe obesity and metabolic complications frequently observed in contemporary youth.

Novel clinical algorithm for hypothalamic obesity in youth with brain tumours and factors associated with excess weight gain.

BACKGROUND: A standardized approach for identifying and treating hypothalamic obesity (HO) in children with hypothalamic tumours is lacking. OBJECTIVES: To describe children with hypothalamic tumours at risk for obesity, assess outcomes of a novel HO clinical algorithm, and identify factors associated with weight gain. METHODS: Retrospective analysis of youth with hypothalamic and suprasellar tumours, seen at a paediatric tertiary care centre from 2010 to 2020. RESULTS: The study cohort (n = 130, 50% female, median age at diagnosis 5 [range 0-17]y) had a median duration of follow up of 5 (0.03-17)y. At last recorded body mass index (BMI) measurement, 34% had obesity, including 17% with severe obesity. Median onset of overweight and obesity after diagnosis was 6.2 (0.3-134) and 8.9 (0.7-65) months, respectively. After algorithm implementation (n = 13), the proportion that had an early dietitian visit (within 6 months) increased from 36% to 54%, (p = 0.498) and weight management referrals increased from 51% to 83% (p = 0.286). Higher BMI z-score at diagnosis was associated with overweight and obesity development (p < 0.001). CONCLUSION: Patients with hypothalamic tumours commonly develop obesity. Use of a clinical algorithm may expedite recognition of HO. Further research is needed to identify predictors of weight gain and to develop effective treatment.

Medical management of children with type 1 diabetes on low-carbohydrate or ketogenic diets.

OBJECTIVES: Low-carbohydrate and ketogenic diets are becoming increasingly popular choices for people with type 1 diabetes (T1D) aiming to achieve optimal glycemic control. A carbohydrate-restricted diet in children has been associated with negative health effects including poor linear growth and inadequate bone mineralization. Guidelines for monitoring children and adolescents choosing to follow a carbohydrate-restricted diet do not exist. We aimed to create a clinical protocol outlining how to clinically and biochemically follow patients choosing a carbohydrate-restricted diet with the goal of medical safety. METHODS: An interdisciplinary committee was formed and reviewed current consensus guidelines for pediatric patients on carbohydrate-restricted diets for epilepsy and metabolic disorders. A literature search was done to determine management strategies for children with T1D on a low-carbohydrate or ketogenic diet. Key health parameters that require monitoring were identified: growth, glycemic control, bone health, cardiometabolic health, and nutritional status. These health outcomes were used to develop a protocol for monitoring children on carbohydrate-restricted diets. RESULTS: A one-page protocol for medical providers and educational materials for families interested in following a low-carbohydrate or ketogenic diet were developed and successfully implemented into clinical care. CONCLUSION: Implementing a protocol for children on carbohydrate-restricted diets in clinic allows medical providers to ensure medical safety while being open to discussing a family's dietary preferences. Following children in the protocol over time will lead to informed clinical guidelines for patients with T1D who choose to follow a carbohydrate-restricted diet.