Vitamin C Deficiency in a University Teaching Hospital
Bibliographic record
Abstract
OBJECTIVES: There is almost no information regarding the vitamin C status of patients treated in Canadian and American hospitals. We determined the prevalence and predictors of vitamin C deficiency in patients hospitalized on the acute-care wards of a Canadian teaching hospital, and tracked their plasma vitamin C concentrations while they were there. METHODS: This was a population-based cross-sectional and time course survey of 149 medical patients shortly after admission to a university teaching hospital. The procedure for sample handling, storage and analysis was validated by measuring the vitamin C concentrations of a reference sample of 141 presumably well nourished people and comparing the results with published norms. RESULTS: In keeping with published norms, 13% of people in the reference group had a subnormal vitamin C concentration (<28.4 micromol/L) and 3% were vitamin C deficient (<11.4 micromol/L). By contrast, 60% of hospitalized patients had a subnormal vitamin C concentration and 19% were deficient. A history of inadequate nutrition or failure to use a vitamin supplement prior to admission, low serum albumin, and male sex predicted plasma vitamin C deficiency, whereas use of a vitamin supplement prior to admission was associated with adequate vitamin C status in hospital. In a second measurement, obtained in 52 patients after an average of 17 days in hospital, vitamin C status had not improved. CONCLUSIONS: Vitamin C deficiency is prevalent and sustained in patients in a Canadian teaching hospital. The abnormality can be prevented by providing a diet sufficient in vitamin C or by prescribing a multiple vitamin tablet.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".