<scp>LEADER</scp> 2: baseline calcitonin in 9340 people with type 2 diabetes enrolled in the <scp>L</scp> iraglutide <scp>E</scp> ffect and <scp>A</scp> ction in <scp>D</scp> iabetes: <scp>E</scp> valuation of cardiovascular outcome <scp>R</scp> esults ( <scp>LEADER</scp> ) trial: preliminary observations
Bibliographic record
Abstract
AIMS: To report preliminary data on baseline serum calcitonin concentrations and associated clinical characteristics in a global population with type 2 diabetes before liraglutide or placebo randomization. METHODS: The ongoing LEADER trial has enrolled 9340 people with type 2 diabetes and at high risk of cardiovascular disease at 410 centres worldwide. People with baseline serum calcitonin ≤ 50 ng/l were randomized to liraglutide once daily or placebo and will be followed for up to 5 years. Serum calcitonin was measured at baseline and will be measured annually thereafter. An independent committee of thyroid experts will oversee calcitonin monitoring throughout the trial and will review all calcitonin concentrations ≥ 20 ng/l. RESULTS: The mean age of participants was 64.3 ± 7.2 years, 64.3% were men, and mean the body mass index was 32.5 ± 6.3 kg/m(2). The median (interquartile range) baseline serum calcitonin values were 3.9 (1.0 to >7.6) ng/l in men and 1.0 (1.0 to >1) ng/l in women. Serum calcitonin was >10 ng/l in 14.6% of men and in 0.96% of women. In sex-specific multivariable linear analysis of covariance models, a reduced glomerular filtration rate (GFR) was associated with higher serum calcitonin concentrations that were statistically significant. A 20 ml/min/1.73 m(2) decrease in estimated GFR (eGFR) was associated with a 14% increase in serum calcitonin in women and an 11% increase in men. CONCLUSIONS: In the LEADER population, the prevalence of elevated serum calcitonin concentrations at baseline was high, and there was an inverse association between eGFR and serum calcitonin concentrations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".