Benefit–risk balance of native vitamin D supplementation in chronic hemodialysis: what can we learn from the major clinical trials and international guidelines?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
For some years, there has been a great renewal of interest in native vitamin D and its major involvement in osseous and non-osseous effects in the organism. Patients in chronic hemodialysis (CHD) constitute a specific population with different physiopathologic characteristics and needs, since morbidity and mortality are strongly correlated with vitamin D insufficiency. Vitamin D supplementation raises very pertinent questions for which we have only partial answers and we lack solid scientific proof to establish certain truths. Thus, we try through this mini-review to analyze the results of the main randomized clinical trials conducted during the last decade, and to discuss international guidelines concerning native vitamin D supplementation in CHD patients. Seven double-blind randomized clinical trials have evaluated native Vitamin D supplementation in CHD patients. These clinical trials began between 2007 and 2013 and studied relatively small samples of patients with an average of 50. All of these trials are important, but do not provide sufficient scientific proof concerning the advantages, consequences, and secondary effects of native vitamin D supplementation in CHD. None of the European, American, English, Asian, Australian, or Canadian recommendations have specified the targets, doses, duration, or the molecule of vitamin D supplementation in the patient on CHD. In 2017, the long-awaited KDIGO recommendations were published and despite the results of clinical trials conducted, the recommendations on native vitamin D supplementation in CHD were very imprecise and sparse, limited to suggesting correction of any state of vitamin D insufficiency or deficiency.
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.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.000 | 0.001 |
| 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