“Vitamin D supplementation and bone health in adults with diabetic nephropathy: the protocol for a randomized controlled trial”
Bibliographic record
Abstract
BACKGROUND: Suboptimal vitamin D status is highly prevalent in Northern communities, particularly in those patients with chronic diseases such as diabetes and chronic renal disease. Emerging literature suggests that adherence to daily vitamin D supplementation may be an important factor influencing vitamin D status and overall bone health, but compliance with therapies for bone health is a major challenge. It is unknown what level of vitamin D supplementation will ameliorate or improve suboptimal vitamin D status in patients with diabetic nephropathy or contribute to improved bone health, particularly for those living in northern climates. METHODS/DESIGN: The study purpose was to examine two different strategies of vitamin D3 supplementation; daily dosing of 2000 IU per day verses monthly dosing of 40,000 IU per month on markers of vitamin D status, bone health and to examine whether adherence, quality of life and patient satisfaction with the supplementation strategy differs between the two vitamin D strategies in adults diagnosed with diabetic nephropathy. DISCUSSION: The need for RCTs assessing higher doses of vitamin D3 supplementation at varying frequencies of administration and its impact on bone health in adults with diabetes and chronic kidney disease are needed. TRIAL REGISTRATION: ClinicalTrials.gov NCT01476501.
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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 | 0.043 | 0.041 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.008 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.055 | 0.009 |
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".