Gluten in pharmaceutical products: a scoping review
Bibliographic record
Abstract
BACKGROUND: Celiac disease (CD) is one of the most common gluten-related disorders. Although the only effective treatment is a strict gluten-free diet, doubts remain as to whether healthcare professionals take this restriction into consideration when prescribing and dispensing medicines to susceptible patients. This scoping review aimed to find out the current evidence for initiatives that either describe the gluten content of medicines or intend to raise awareness about the risk of prescribing and dispensing gluten-containing medicines in patients with CD and other gluten-related disorders. METHODS: A scoping review was conducted using three search strategies in PubMed/MEDLINE, TripDatabase and Web of Science in April 2021, following the PRISMA extension for scoping reviews (PRISMA-ScR). References from included articles were also examined. Two researchers screened the articles and results were classified according to their main characteristics and outcomes, which were grouped according to the PCC (Population, Concept and Context) framework. The initiatives described were classified into three targeted processes related to gluten-containing medicines: prescription, dispensation and both prescription and dispensation. RESULTS: We identified a total of 3146 records. After the elimination of duplicates, 3062 articles remained and ultimately 13 full texts were included in the narrative synthesis. Most studies were conducted in the US, followed by Canada and Australia, which each published one article. Most strategies were focused on increasing health professional's knowledge of gluten-containing/gluten-free medications (n = 8), which were basically based on database development from manufacturer data. A wide variability between countries on provided information and labelling of gluten-containing medicines was found. CONCLUSION: Initiatives regarding the presence of gluten in medicines, including, among others, support for prescribers, the definition of the role of pharmacists, and patients' adherence problems due to incomplete labelling of the medicines, have been continuously developed and adapted to the different needs of patients. However, information is still scarce, and some aspects have not yet been considered, such as effectiveness for the practical use of solutions to support healthcare professionals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".