Baseline characteristics of subjects enrolled in the Evaluation of Cinacalcet HCl Therapy to Lower Cardiovascular Events (EVOLVE) trial
Bibliographic record
Abstract
BACKGROUND: Secondary hyperparathyroidism (sHPT) and other abnormalities associated with chronic kidney disease-mineral bone disorder can contribute to dystrophic (including vascular) calcification. Dietary modification and variety of medications can be used to attenuate the severity of sHPT. However, it is unknown whether any of these approaches can reduce the high risks of death and cardiovascular disease in patients with end-stage renal disease. METHODS: The Evaluation of Cinacalcet HCl Therapy to Lower Cardiovascular Events (EVOLVE) trial was designed to test the hypothesis that treatment with the calcimimetic agent cinacalcet compared with placebo (on a background of conventional therapy including phosphate binders +/- vitamin D sterols) reduces time to death or non-fatal cardiovascular events (specifically myocardial infarction, unstable angina, heart failure and peripheral arterial disease events) among patients on hemodialysis with sHPT. This report describes baseline characteristics of enrolled subjects with a focus on regional variation. RESULTS: There were 3883 subjects randomized from 22 countries, including the USA, Canada, Australia, three Latin American nations, Russia and 15 European nations. The burden of overt cardiovascular disease at baseline was high (e.g. myocardial infarction 12.4%, heart failure 23.3%). The median plasma parathyroid hormone concentration at baseline was 692 pg/mL (10%, 90% range, 363-1694 pg/mL). At baseline, 87.2% of subjects were prescribed phosphate binders and 57.5% were prescribed activated vitamin D derivatives. Demographic data, comorbid conditions and baseline laboratory data varied significantly across regions. CONCLUSIONS: EVOLVE enrolled 3883 subjects on hemodialysis with moderate to severe sHPT. Inclusion of subjects from multiple global regions with varying degrees of disease severity will enhance the external validity of the trial results.
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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) | 0.001 | 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".