Increased resting energy expenditure in children with attention-deficit-hyperactivity disorder.
Bibliographic record
Abstract
BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is one of the most frequently reported neuropsychiatric disorders in childhood. However, there is limited data on the biological basis for this disorder. Disturbances in neurotransmitters have been suggested to play a pathophysiologic role. Phenotypically an increased prevalence of obesity has been reported. OBJECTIVE: To investigate resting energy expenditure (REE) and diet-induced thermogenesis in stimulant medication-naïve children with ADHD. DESIGN: Case control study of 12 pre-pubertal boys with ADHD of the hyperactive-impulsive type and 12 control boys without ADHD. Anthropometric testing and indirect calorimetry were performed before and after a standardized meal. REE and thermogenesis were measured in each subject at 2 time points. In an independent group of 60 boys with ADHD, BMI standard deviation scores (BMI-SDS) were compared to age-adapted reference values. RESULTS: REE was on average 6.5 kcal/kg fat free mass/day higher in the ADHD compared to the control group (p<0.01). In contrast, the thermogenic effect of food was not different between the two groups (average increase by 16%, p=n.s.). The repeat measurements, an average of 5±1 months apart, were highly reproducible in all subjects. Age and restlessness did not explain the differences in REE. Boys with ADHD had similar BMI-SDS values (mean BMI-SDS -0.10±0.98) as reference groups. CONCLUSIONS: REE, in contrast to diet-induced thermogenesis, is higher in medication-naïve boys with ADHD. The normal BMI levels suggest increased energy intake in these children.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".