Feasibility of a clinical trial to assess the effect of dietary calcium<i>v.</i>supplemental calcium on vascular and bone markers in healthy postmenopausal women
Bibliographic record
Abstract
Whether supplemental Ca has similar effects to dietary Ca on vascular and bone markers is unknown. The present trial investigated the feasibility of applying dietary and supplemental interventions in a randomised-controlled trial (RCT) aiming to estimate the effect of supplemental Ca as compared with dietary Ca on vascular and bone markers in postmenopausal women. In total, thirteen participants were randomised to a Ca supplement group (CaSuppl) (750 mg Ca from CaCO3+450 mg Ca from food+20 µg vitamin D supplement) or a Ca diet group (CaDiet) (1200 mg Ca from food+10 µg vitamin D supplement). Participants were instructed on Ca consumption targets at baseline. Monthly telephone follow-ups were conducted to assess adherence to interventions (±20 % of target total Ca) using the multiple-pass 24-h recall method and reported pill count. Measurements of arterial stiffness, peripheral blood pressure and body composition were performed at baseline and after 6 and 12 months in all participants who completed the trial (n 9). Blood and serum biomarkers were measured at baseline and at 12 months. Both groups were compliant to trial interventions (±20 % of target total Ca intake; pill count ≥80 %). CaSuppl participants maintained a significantly lower average dietary Ca intake compared with CaDiet participants throughout the trial (453 (sd 187) mg/d v. 1241 (sd 319) mg/d; P<0·001). There were no significant differences in selected vascular outcomes between intervention groups over time. Our pilot trial demonstrated the feasibility of conducting a large-scale RCT to estimate the differential effects of supplemental and dietary Ca on vascular and bone health markers in healthy postmenopausal women.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".