Bibliographic record
Abstract
There is growing evidence that vitamin D deficiency significantly increases the risk of adverse cardiovascular events and that a vitamin D status representing sufficiency or optimum is protective. Unfortunately, in clinical trials that address interventions for reducing risk of adverse cardiovascular events, vitamin D status is not generally measured. Failure to do this has now assumed greater importance with the report of a study that found rosuvastatin at doses at the level used in a recent large randomized lipid lowering trial (JUPITER) had a large and significant impact on vitamin D levels as measured by the metabolite 25-hydroxyvitamin D. The statin alone appears to have increased this marker such that the participants on average went from deficient to sufficient in two months. The difference in cardiovascular risk between those deficient and sufficient in vitamin D in observational studies was similar to the risk reduction found in JUPITER. Thus it appears that this pleiotropic effect of rosuvastatin may be responsible for part of its unusual effectiveness in reducing the risk of various cardiovascular endpoints found in JUPITER and calls into question the interpretation based only on LDL cholesterol and CRP changes. In addition, vitamin D status is a cardiovascular risk factor which up until now has not been considered in adjusting study results or in multivariate analysis, and even statistical analysis using only baseline values may be inadequate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".