Self‐rated health scores predict mortality among people with type 2 diabetes differently across three different country groupings: findings from the ADVANCE and ADVANCE‐ON trials
Bibliographic record
Abstract
AIMS: To explore whether there is a different strength of association between self-rated health and all-cause mortality in people with type 2 diabetes across three country groupings: nine countries grouped together as 'established market economies'; Asia; and Eastern Europe. METHODS: The ADVANCE trial and its post-trial follow-up were used in this study, which included 11 140 people with type 2 diabetes from 20 countries, with a median follow-up of 9.9 years. Self-rated health was reported on a 0-100 visual analogue scale. Cox proportional hazard models were fitted to estimate the relationship between the visual analogue scale score and all-cause mortality, controlling for a range of demographic and clinical risk factors. Interaction terms were used to assess whether the association between the visual analogue scale score and mortality varied across country groupings. RESULTS: The visual analogue scale score had different strengths of association with mortality in the three country groupings. A 10-point increase in visual analogue scale score was associated with a 15% (95% CI 12-18) lower mortality hazard in the established market economies, a 25% (95% CI 21-28) lower hazard in Asia, and an 8% (95% CI 3-13) lower hazard in Eastern Europe. CONCLUSIONS: Self-rated health appears to predict 10-year all-cause mortality for people with type 2 diabetes worldwide, but this relationship varies across groups of countries.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".