Elevated inflammation supra-additively promotes the progression from prediabetes to diabetes: a prospective cohort study
Bibliographic record
Abstract
Background: Factors impacting on the conversion of prediabetes to diabetes or normoglycemia remain unclear. This study aimed to investigate the role of subclinical inflammation, assessed by high-sensitivity C-reactive protein (hsCRP), in the progression to diabetes from prediabetes, assessed by impaired fasting glucose (IFG). Methods: Time-to-event survival analyses were conducted among 82 475 participants without diabetes from Kailuan Study (a real-life prospective cohort in China) to access the isolated and joint effect of hsCRP and IFG on diabetes risk, and quantify their relative contribution to incident diabetes. Results: Over a median 11-year follow-up, 14 215 diabetes cases were recorded. IFG and hsCRP independently and jointly increased diabetes risk. Diabetes incidence was higher in those with elevated inflammation (hsCRP≥2 mg/L: 90.45 vs. 66.76 per 1000 person-years). The joint effect risk (hazard ratios (HR) = 4.96; 95% confidence interval (CI) = 4.66-5.28) exceeded the sum of individual risks (HR = 4.29; 95% CI = 4.09-4.49 for IFG and HR = 1.11; 95% CI = 1.06-1.16 for elevated inflammation), with a relative excess risk due to interaction of 0.56 (95% CI = 0.23-0.89). Attributable proportions were 83.08% for IFG, 2.78% for hsCRP, and 14.14% for their interaction. The joint risks and the additive interaction were significant in both men and women, and were more pronounced among individuals aged <60 years than those aged ≥60 years. Conclusions: Elevated inflammation synergistically amplifies diabetes risk in prediabetes among Chinese adults, particularly in those <60 years.
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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".