Is There an Epidemic Vitamin D Deficiency in German Orthopaedic Patients?
Bibliographic record
Abstract
BACKGROUND: Vitamin D plays an essential role in bone health and muscle function. Some studies have shown a widespread rate of vitamin D deficiency in the general population, but few have reported on the vitamin D status of orthopaedic patients. QUESTIONS/PURPOSES: We investigated (1) the extent of hypovitaminosis D in orthopaedic patients, (2) seasonal variations in vitamin D levels, and (3) possible risk factors for insufficient vitamin D levels. METHODS: Vitamin D levels in 1119 patients consecutively admitted to an orthopaedic surgery department in 2011 were measured. To investigate the correlation between climate factors and vitamin D levels, the sunshine hours for each month in 2011 were collected by Deutscher Wetterdienst (the German weather service) in the region where most tested patients lived. The prevalence of normal (> 30 ng/mL), insufficient (20-30 ng/mL), and deficient (< 20 ng/mL) 25-hydroxyvitamin D levels was determined. Univariate and multivariate analyses were used to assess risk factors for insufficient vitamin D levels. RESULTS: Overall, 84% of patients had insufficient levels of vitamin D and 60% were vitamin D deficient. Only 15% were in the target range of 30 to 60 ng/mL. The prevalence of low vitamin D levels was greater during winter and months with fewer sunshine hours. Vitamin D levels did not vary according to age, sex, and disease. Individuals with obesity, hypertension, and osteoporosis were more likely to have low vitamin D levels compared with their healthy counterparts. CONCLUSIONS: There is an alarmingly high rate of hypovitaminosis D and vitamin D deficiency among orthopaedic patients in this region of Germany, whose latitude (50° N) is approximately the same as those of Vancouver (49°, 15' N) and Paris (48°, 51' N). Given the well-known effects on bone metabolism and muscle health, low vitamin D levels may negatively affect patients. Screening and treating hypovitaminosis D appears to be important in this patient population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".