Effects of vitamin C and vitamin D on mood and distress in acutely hospitalized patients
Bibliographic record
Abstract
Hypovitaminosis C and D are highly prevalent in acute‐care hospitals, but their clinical implications have not been investigated. Because deficiencies of these vitamins can adversely affect mood, we conducted a double‐blind randomized clinical trial to determine the effect of vitamin C (500 mg twice daily) or D (5000 IU daily) supplementation on psychological status, as assessed using two different validated instruments. At baseline, 73% of patients had a subnormal plasma vitamin C concentration (< 28.4 μM) and 79% had a subnormal plasma 25OHD concentration (< 75 nM). Vitamin C provision for a mean of 8.2 days (n = 26) normalized plasma vitamin C concentrations (P < 0.0001) and resulted in a 71% reduction in Profile of Mood States R total mood disturbance score (from 24.0 ± 18.2 to 6.9 ± 14.4, mean ± SD; P = 0.0002) and a 51% reduction in psychological distress as measured using the Distress Thermometer (from 4.5 ± 2.9 to 2.2 ± 2.2; P = 0.0002). By contrast, high‐dose vitamin D provision for a mean of 8.1 days (n = 26) increased plasma 25OHD concentrations (P < 0.0001), but not into the normal range, and had statistically insignificant effects on mood (21.7 ± 17.3 to 14.6 ± 17.7; P = 0.067) and distress (3.7 ± 2.6 to 3.4 ± 2.8; P = 0.45). Conclusion Hypovitaminosis C and D are highly prevalent in acutely hospitalized patients. Vitamin C supplementation improves mood and reduces distress in these patients. Supported by the Lotte and John Hecht Foundation and a Faculty of Medicine student research bursary. Grant Funding Source : Lotte and John Hecht Foundation
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".