Clinical Use of the Edmonton Obesity Staging System for the Assessment of Weight Management Outcomes in People with Class 3 Obesity
Bibliographic record
Abstract
We aimed to assess weight loss and metabolic outcomes by severity of weight-related complications following an intensive non-surgical weight management program (WMP) in an Australian public hospital. A retrospective cohort study of all patients aged ≥18 years with body mass index (BMI) ≥ 40 enrolled in the WMP during March 2018−March 2019 with 12-month follow-up information were stratified using the Edmonton Obesity Staging System (EOSS). Of 178 patients enrolled in the WMP, 112 (62.9%) completed at least 12 months’ treatment. Most patients (96.6%) met EOSS-2 (56.7%) or EOSS-3 (39.9%) criteria for analysis. Both groups lost significant weight from baseline to 12 months; EOSS-2: 139.4 ± 31.8 kg vs. 131.8 ± 31.8 kg (p < 0.001) and EOSS-3: 141.4 ± 24.2 kg vs. 129.8 ± 24.3 kg (p < 0.001). After adjusting for baseline age, sex and employment status, mean weight loss was similar but a greater proportion of EOSS-3 achieved >10% weight loss compared to EOSS-2, (40% vs. 15.9%, p = 0.024). Changes in metabolic parameters including HbA1c, BP and lipids did not differ between EOSS-2 and 3. Despite increased clinical severity, adult patients with class 3 obesity achieved clinically meaningful weight loss and similar improvements in metabolic parameters compared to patients with less severe complications after 12 months in an intensive non-surgical WMP.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".