Acute effects of cinacalcet on arterial stiffness and ventricular function in hemodialysis patients
Bibliographic record
Abstract
BACKGROUND: Serum calcium concentration (Ca) plays an essential role in a vascular muscle tone and myocardial contractility. Previously, we showed that acutely lowering Ca by hemodialysis reduced arterial stiffness. Cinacalcet is a calcimimetic that lowers Ca and parathyroid hormone (PTH). The aim of the present study was to examine whether acute lowering of Ca by cinacalcet improves vascular stiffness and myocardial diastolic dysfunction. METHOD: This is a double-blinded randomized placebo-controlled crossover study that included 21 adult patients with end-stage kidney disease undergoing chronic hemodialysis. Subjects were assigned to placebo-cinacalcet (30 mg) or cinacalcet-placebo sequence. After each treatment period (7 days), aortic, brachial, and carotid stiffness were determined by examining carotid-femoral pulse wave velocity (cf-PWV), carotid-radial PWV (cr-PWV), and carotid distension. A central pulse wave profile was determined by radial artery tonometry and cardiac function was evaluated by echocardiography. RESULTS: Cinacalcet reduced PTH (483 [337-748] to 201 [71-498] ng/L, P < .001) and ionized Ca (1.11 [1.08-1.15] to 1.05 [1.00-1.10] mmol/L, P = .04). Cinacalcet did not reduced cf-PWV significantly (12.2 [10.4-15.4] to 12.2 [11.0-14.6] m/s, P = .16). After adjustments for mean blood pressure, sequence, carryover, and treatment effects, cf-PWV was not significantly lowered by cinacalcet (-0.35 m/s, P = .139). There were no significant changes in central blood pressures, brachial and carotid stiffness, and echocardiographic parameters. CONCLUSION: In this study, 30 mg daily cinacalcet for 1 week did not have any significant impact on peripheral and central blood pressures, arterial stiffness parameters, or cardiac function (NCT01250405).
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".