Differences in weight change trajectory patterns in a publicly funded adult weight management centre
Bibliographic record
Abstract
OBJECTIVE: To describe differences in weight loss (WL) trajectory patterns at a publicly funded clinical weight management centre. METHODS: Groups with differences in the attainment of a 5% total body WL and percentage WL patterns over time were identified in 7,121 patients who attended a physician lead multi-disciplinary clinical lifestyle weight management that predominantly focused on education and diet counselling. Resultant health differences were examined. RESULTS: Patients had 3.2 ± 6.3%WL with 35% of patients achieving and maintaining a 5%WL. Half of these patients achieved the 5%WL within 6 months, while the other half had a more gradual approach. Another 10% achieved 5%WL, but regained weight after 6 months. There were seven distinct WL patterns identified: LargeWL (Mean WL: 21.2 ± 8.1%; Probability of group membership (PGM): 2.4%), ModerateWL (15.1 ± 5.1%WL; 5.4%PGM), SlowWL (6.7 ± 3.2%WL; 20.1%PGM) and MinimalWL (2.4 ± 2.2%WL; 34.6%PGM), WL Regain (9.4 ± 3.5%WL; 8.2%PGM), Weight Stable (1.2 ± 3.2%WL; 28.5%PGM) and Weight Gain (18.4 ± 11.2%WG; 0.8%PGM) groups. Improvements in blood pressure, lipids and glucose were generally related to the magnitude of WL achieved more than the pattern or speed of WL. CONCLUSIONS: There are large differences in the absolute WL attained and the pattern of WL during a publicly funded weight management program. Changes in clinical health markers appear to be more strongly related with the absolute WL attained as opposed to patterns of weight change. © 2016 The Authors. Obesity Science & Practice published by John Wiley & Sons Ltd, World Obesity and The Obesity Society.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".