Evaluation of Cinacalcet Therapy to Lower Cardiovascular Events (EVOLVE)
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The dramatically high rates of mortality and cardiovascular morbidity observed among dialysis patients highlights the importance of identifying and implementing strategies to lower cardiovascular risk in this population. Results from clinical trials undertaken thus far, including trials on lipid reduction, normalization of hematocrit, and increased dialysis dosage, have been unsuccessful. Available data indicate that abnormalities in calcium and phosphorus metabolism, as a result of either secondary hyperparathyroidism alone or the therapeutic measures used to manage secondary hyperparathyroidism, are associated with an increased risk for death and cardiovascular events. However, no prospective trials have evaluated whether interventions that modify these laboratory parameters result in a reduction in adverse cardiovascular outcomes. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Evaluation of Cinacalcet Therapy to Lower Cardiovascular Events is a global, phase 3, double-blind, randomized, placebo-controlled trial evaluating the effects of cinacalcet on mortality and cardiovascular events in hemodialysis patients with secondary hyperparathyroidism. Approximately 3800 patients from 22 countries will be randomly assigned to cinacalcet or placebo. Flexible use of traditional therapies will be permitted. The primary end point is the composite of time to all-cause mortality or first nonfatal cardiovascular event (myocardial infarction, hospitalization for unstable angina, heart failure, or peripheral vascular disease, including lower extremity revascularization and nontraumatic amputation). RESULTS: The study will be event driven (terminated at 1882 events) with an anticipated duration of approximately 4 yr. CONCLUSIONS: Evaluation of Cinacalcet Therapy to Lower Cardiovascular Events will determine whether management of secondary hyperparathyroidism with cinacalcet reduces the risk for mortality and cardiovascular events in hemodialysis patients.
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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 | 0.002 | 0.003 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".