International experience of drug correction of vitamin D level depending on its initial level in blood serum and the age of the patient (review and mathematical analysis)
Bibliographic record
Abstract
Vitamin D deficiency is a global public health problem and poses a particular threat to the elderly and those with comorbidities such as obesity, diabetes, hypertension, respiratory disease, recurrent infections, immunodeficiency, and patients infected with SARS-CoV-2. D-avitaminosis is extremely common among pregnant women and has a huge impact not only on the health of the mother, but also on the health of the child throughout his later life. There is an inverse correlation between human serum 25(OH)D levels and incidence of twelve types of cancer, with prevalence of myocardial dysfunction, mortality due to heart failure, and sudden cardiac death. In this paper, an analysis of documents regulating the procedure for increasing the level of vitamin D for therapeutic purposes was carried out. It is shown that many documents are replete with contradictions and need to be corrected. Uncertainty in research results, recommendations and guidelines leads to wide variability in the knowledge, attitudes and behavior of doctors, which translates into an equally wide variability in doctors’ advice to patients on types of supplements, dosage, frequency and duration of vitamin D intake. In this regard, based on the results of numerous clinical experiments on increasing the level of 25(OH)D in the blood serum of residents of Europe, the USA and Canada, we have obtained multiple correlation equations that describe the relationship between the level of the required daily dosage of cholecalciferol and calcifediol supplements with the patient’s age, the initial level of calcifediol in the blood serum, the required value of its increase and duration of taking the drug, which can be used by practitioners when choosing a daily dosage of a vitamin for each patient, taking into account international experience. The results of multiple correlations in the authors’ studies, largely echoing some of the results of studies by foreign scientists, suggest the possibility of revising the currently existing stereotypes about the usage of higher daily doses of vitamin D to increase the level of calcifediol concentration in the blood serum of elderly patients, compared to younger ones.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".