The global impact of the DRACMA guidelines cow’s milk allergy clinical practice
Bibliographic record
Abstract
BACKGROUND: The 2010 Diagnosis and Rationale for Action against Cow's Milk Allergy (DRACMA) guidelines are the only Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidelines for cow's milk allergy (CMA). They indicate oral food challenge (OFC) as the reference test for diagnosis, and suggest the choice of specific alternative formula in different clinical conditions. Their recommendations are flexible, both in diagnosis and in treatment. OBJECTIVES & METHODS: Using the Scopus citation records, we evaluated the influence of the DRACMA guidelines on milk allergy literature. We also reviewed their impact on successive food allergy and CMA guidelines at national and international level. We describe some economic consequences of their application. RESULTS: DRACMA are the most cited CMA guidelines, and the second cited guidelines on food allergy. Many subsequent guidelines took stock of DRACMA's metanalyses adapting recommendations to the local context. Some of these chose not to consider OFC as an absolute requirement for the diagnosis of CMA. Studies on their implementation show that in this case, the treatment costs may increase and there is a risk of overdiagnosis. Interestingly, we observed a reduction in the cost of alternative formulas following the publication of the DRACMA guidelines. CONCLUSIONS: DRACMA reconciled international differences in the diagnosis and management of CMA. They promoted a cultural debate, improved clinician's knowledge of CMA, improved the quality of diagnosis and care, reduced inappropriate practices, fostered the efficient use of resources, empowered patients, and influenced some public policies. The accruing evidence on diagnosis and treatment of CMA necessitates their update in the near future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.062 | 0.290 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.020 | 0.021 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".