Comparison of reducing epicardial fat by exercise, diet or bariatric surgery weight loss strategies: a systematic review and meta‐analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The objectives were to determine whether epicardial fat (EAT) is subject to modification, and whether various strategies accomplish this end point and the relationship between weight loss and EAT. A systematic review of the literature following meta-analysis guidelines was conducted using the search strategy 'epicardial fat' OR 'epicardial adipose tissue' AND 'diet' OR 'exercise' OR 'bariatric surgery (BS)' OR 'change in body weight' limited to humans. Eleven articles were identified with 12 intervention approaches of which eight studies showed a statistically significant reduction in EAT. A random-effects meta-analysis suggests an overall significant reduction of 1.12 standardized units (95% CI = [-1.71, -0.54], P value < 0.01). While there is a large amount of heterogeneity across study groups, a substantial amount of this variability can be accounted for by considering intervention type and change in body mass index (BMI). These variables were incorporated into a random-effects meta-regression model. Using this analysis, significant EAT reduction occurred with diet and BS but not with exercise. BMI reductions correlated significantly with EAT reductions for diet-based interventions, i.e. for some but not all interventions. In conclusion, EAT, a factor that is significantly associated with coronary artery disease, can be modified. The type of intervention, in addition to the amount of weight loss achieved, is predictive of the amount of EAT reduction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.049 | 0.017 |
| Bibliometrics | 0.000 | 0.003 |
| 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) | 0.000 | 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 it