Cardiometabolic health, visceral fat and circulating irisin levels: results from a real-world weight loss study
Bibliographic record
Abstract
BACKGROUND: The aim of this pragmatic intervention study was to investigate changes in cardiometabolic outcomes, irisin plasma concentration, and body composition during a 4-month intervention in unselected obese individuals. MATERIALS AND METHODS: In 111 obese women aged 36.73 ± 7.2 years, we measured changes in weight, lipid profiles, glucose, insulin, Homeostatic Model Assessment-Insulin Resistance Index (HOMA-IR), uric acid, aminotransferases, and irisin. Body composition including lean mass (LM) and total (TF), gynoid (GF), android (AF), and visceral fat (VF) was assessed using densitometry. Physical activity was assessed using the International Physical Activity Questionnaire (IPAQ). The participants received tailored written advice targeting lifestyle according to current guidelines. At follow-up, patients rated their adherence in the self-administered questionnaire. RESULTS: Mean weight loss in the whole group was 3.12 kg (- 3.3%); 26% of the women achieved the desired target of weight loss (> 5% of the initial weight), whereas weight decreased moderately in 50% and increased in 14%. In 86 women with weight loss, there were significant changes in HOMA-IR (- 13.8%), insulin (- 11.2%), alanine aminotransferase (- 8.0%), VF (- 7.0%), AF (- 5.4%), TF (- 4.7%), GF (- 2.8%) and LM (- 1.5%), whereas irisin and HDL-C levels and the mean IPAQ score did not change. CONCLUSIONS: In this real-world evidence study, a successful weight loss achieved only 26% of patients, with overall much better adherence to diet restriction than to exercise. However, even mild to moderate weight loss resulted in significant improvements in cardiometabolic health. Weight loss was associated with a modest LM decrease but did not influence plasma irisin.
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.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".