Blood Calcification Propensity, Cardiovascular Events, and Survival in Patients Receiving Hemodialysis in the EVOLVE Trial
Why this work is in the frame
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Bibliographic record
Abstract
Background and objectives Patients receiving hemodialysis are at risk of cardiovascular events. A novel blood test ( T 50 test) determines the individual calcification propensity of blood. Design, setting, participants, & measurements T 50 was determined in 2785 baseline serum samples of patients receiving hemodialysis enrolled in the Evaluation of Cinacalcet Therapy to Lower Cardiovascular Events (EVOLVE) trial and the T 50 results were related to patient outcomes. Results Serum albumin, bicarbonate, HDL cholesterol, and creatinine were the main factors positively/directly and phosphate was the main factor negatively/inversely associated with T 50 . The primary composite end point (all-cause mortality, myocardial infarction [MI], hospitalization for unstable angina, heart failure, or peripheral vascular event [PVE]) was reached in 1350 patients after a median follow-up time of 619 days. After adjustments for confounding, a lower T 50 was independently associated with a higher risk of the primary composite end point as a continuous measure (hazard ratio [HR] per 1 SD lower T 50 , 1.15; 95% confidence interval [95% CI], 1.08 to 1.22; P <0.001). Furthermore, lower T 50 was associated with a higher risk in all-cause mortality (HR per 1 SD lower T 50 , 1.10; 95% CI, 1.02 to 1.17; P =0.001), MI (HR per 1 SD lower T 50 , 1.38; 95% CI, 1.19 to 1.60; P <0.001), and PVE (HR per 1 SD lower T 50 , 1.22; 95% CI, 1.05 to 1.42; P =0.01). T 50 improved risk prediction (integrated discrimination improvement and net reclassification improvement, P <0.001 and P =0.001) of the primary composite end point. Conclusions Blood calcification propensity was independently associated with the primary composite end point, all-cause mortality, MI, and PVE in the EVOLVE study and improved risk prediction. Prospective trials should clarify whether T 50 -guided therapies improve outcomes.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it