25-Hydroxyvitamin D variability within-person due to diurnal rhythm and illness: a case report
Bibliographic record
Abstract
BACKGROUND: Vitamin D nutrition research requires accurate measures of circulating 25-hydroxyvitamin D. Our objectives were to test whether a diurnal fluctuation in blood-spot concentrations of 25-hydroxyvitamin D can be demonstrated statistically in a single individual, and whether such fluctuation is affected by the pre-dose versus post-dose timing of the blood draw. CASE PRESENTATION: The participant in this case study was a generally healthy Caucasian woman in her 40s who has taken 5000 IU vitamin D3 supplement at midday for over 1 year. Each blood sample was drawn individually from a finger prick onto filter paper at morning, midday, or night, on 4 days (three groups of five individual blood samples per collection day). On days 1 and 2, the midday samples were collected approximately 1 hour after the supplement was taken; on days 3 and 4, the midday samples were collected within an hour prior to supplementation (the classical, daily "trough" value for a drug). There was a significant daily pattern of variation in 25-hydroxyvitamin D concentrations (analysis of variance p ≤ 0.02 for 3 of the 4 days): peak midday mean 25-hydroxyvitamin D was approximately 20% higher than in the morning, and approximately 13% higher than in the evening. Trough sampling produced no significant difference in 25-hydroxyvitamin D compared to sampling an hour after the dose. An incidental finding was that acute illness during the study was related to acutely lower 25-hydroxyvitamin D at every sampling time in the day (p < 0.00001). CONCLUSIONS: There was a consistent diurnal variation in 25-hydroxyvitamin D, with the peak at midday. There was no difference between trough versus post-dose blood draws. Acute illness may acutely lower serum 25-hydroxyvitamin D levels. Because within-person, within-day variability in 25-hydroxyvitamin D is approximately 20%, sampling time introduces systematic error in vitamin D nutritional assessment that is bigger than random analytical error or choice of assay method.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".