An Update on the Screening, Diagnosis, Management, and Treatment of Vitamin D Deficiency in Individuals with Cystic Fibrosis: Evidence-Based Recommendations from the Cystic Fibrosis Foundation
Bibliographic record
Abstract
OBJECTIVE: The objective was to develop evidence-based clinical care guidelines for the screening, diagnosis, management, and treatment of vitamin D deficiency in individuals with cystic fibrosis (CF). PARTICIPANTS: The guidelines committee was comprised of physicians, registered dietitians, a pharmacist, a nurse, a parent of an individual with CF, and a health scientist, all with experience in CF. PROCESS: Committee members developed questions specific to vitamin D health in individuals with CF. Systematic reviews were completed for each question. The committee reviewed and graded the available evidence and developed evidence-based recommendations and consensus recommendations when insufficient evidence was available. Each consensus recommendation was voted upon by an anonymous process. CONCLUSIONS: Vitamin D deficiency is common in CF. Given the limited evidence specific to CF, the committee provided consensus recommendations for most of the recommendations. The committee recommends yearly screening for vitamin D status, preferably at the end of winter, using the serum 25-hydroxyvitamin D measurement, with a minimal 25-hydroxyvitamin D concentration of 30 ng/ml (75 nmol/liter) considered vitamin D sufficient in individuals with CF. Recommendations for age-specific vitamin D intake for all individuals with CF, form of vitamin D, and a stepwise approach to increase vitamin D intake when optimal vitamin D status is not achieved are delineated.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".