Remote Lifestyle Counseling Influences Cardiovascular Health Outcomes in Youth with Overweight or Obesity and Congenital Heart Disease
Bibliographic record
Abstract
Background: Children with overweight/obesity and congenital heart disease are at increased cardiovascular risk. A lifestyle intervention may help reduce these risks. We sought to determine the feasibility of a smartphone-based lifestyle intervention to improve cardiovascular health outcomes in children with overweight/obesity and congenital heart disease. Methods: We examined the effect of bi-weekly nutrition and fitness counseling delivered via smartphone over 12 months. Thirty-four youth, previously diagnosed with congenital heart disease and with overweight or obesity, participated in the intervention. They were divided into two groups depending on whether the heart disease required surgical correction (operated, n=19) or not (non-operated, n=15). Anthropometry, body composition cardiorespiratory exercise capacity and cardio-metabolic risk factors were assessed at baseline, 6 months, and 12 months. Results: Statistically significant decreases in waist circumference, body mass index z-score, waist circumference z-score and waist to height ratio z-score were observed at 6 and 12 months in the operated group. A significant linear increase in lean body mass was observed in both groups. The study also had a high retention rate and a low attrition rate. Conclusions: The observed changes in anthropometry were positive with significant improvement to some cardiovascular and metabolic risk indicators. However, this was only observed in the operated group suggesting that other factors, such as perception of condition and self-efficacy, may influence lifestyle behaviors. The results from this pilot study clearly demonstrate the feasibility to perform a larger controlled study on remote lifestyle intervention in children with congenital heart defects and overweight or obesity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".