Multimorbidity in a prospective cohort: Prevalence and associations with weight loss and health status in severely obese patients
Bibliographic record
Abstract
OBJECTIVE: To examine the prevalence of multimorbidity (≥2 chronic conditions) in severely obese patients and its associations with weight loss and health status over 2 years. METHODS: In a prospective cohort including 500 severely obese adults, self-reported prevalence of 20 chronic conditions was calculated at baseline and 2 years. Multivariable logistic regression models were fitted to test the covariate-adjusted associations between ≥5% weight reduction and reduction in multimorbidity and the association between health status (visual analogue scale [VAS]) and reduction in multimorbidity over 2 years. RESULTS: After 2 years, mean weight change was -12.9 ±18.7 kg, 53% had ≥5% weight reduction, mean change in VAS was 11.5 ± 21.2, and 53.5% had ≥10% increase in VAS. Multimorbidity was reported in 95.4% and 92.8% patients at baseline and 2 years, respectively. Weight loss (≥5%) over 2 years was associated with reduction in multimorbidity (adjusted OR = 1.7, 95% CI 1.1-2.7). Reduction in multimorbidity was associated with clinically important improvements (≥10% increase in VAS) in health status (adjusted OR = 2.5, 95% CI 1.6, 4.0). CONCLUSIONS: Multimorbidity is common in severely obese patients. Having ≥5% weight reduction over 2 years was associated with a reduction in multimorbidity, which was also associated with improvements in health status.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".