EDMONTON OBESITY STAGING SYSTEM IMPLEMENTATION AND EFFECTIVENESS IN AN AUSTRALIAN MULTIDISCIPLINARY WEIGHT MANAGEMENT CLINIC OVER A TWO-YEAR PERIOD
Bibliographic record
Abstract
INTRODUCTIONMultidisciplinary weight management clinics (MWMC) are being established globally to manage the ever-growing obesity epidemic. However, among Australian MWMC, there is a relative paucity of published clinical outcomes, particularly on assessing holistic patient outcomes. The Edmonton Obesity Staging System (EOSS) provides a framework based on metabolic, anthropometric and psychological factors for holistic obesity management, based on a 5-class scale [0-4 (highest-risk class)]. The EOSS has greater health and mortality predictability than traditional BMI or metabolic syndrome measures. To evaluate the implementation and changes in patient outcomes based on an EOSS model in an Australian university hospital-based MWMC. METHODLOGY A retrospective review of a cohort of patients (n=76) from the Healthy Weight Clinic, Sydney, over at least 2-year period of regular (<6 monthly) consults. All patients received intervention from at least an endocrinologist, dietitian and exercise physiologist. RESULTS Mean baseline EOSS class was 1.56 (SD 0.84) and after 24 months mean EOSS class statistically improved to 1.05 (SD 0.88) (P<0.05). Baseline mean BMI was 38.0 kg/m² (SD 7.1) and mean BMI at last follow-up was 33.4 kg/m² (SD 6.4), also statistically significant (P<0.05). All features of the EOSS scale, namely, anthropometric data, deranged liver function tests, dyslipidaemia and prediabetes state showed clinically significant reductions towards normal levels. Almost three quarters of our patients (72%) dropped reduced at least one EOSS class. CONCLUSIONCare from MWMC can produce significant reductions in EOSS classes, leading to improved patient outcomes across multiple comorbidities over 2 years. Future studies should compare this framework across Australian MWMC, to establish a standardised approach to biopsychosocial obesity management.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".