Preventing food allergy: protocol for a rapid systematic review
Bibliographic record
Abstract
BACKGROUND: The European Academy of Allergy and Clinical Immunology is developing guidelines about how to prevent and manage food allergy. As part of the guidelines development process, a systematic review is planned to examine published research about the prevention of food allergy. This systematic review is one of seven inter-linked evidence syntheses that are being undertaken in order to provide a state-of-the-art synopsis of the current evidence base in relation to epidemiology, prevention, diagnosis and clinical management, and impact on quality of life, which will be used to inform clinical recommendations. The aim of this systematic review will be to assess the effectiveness of approaches for the primary prevention of food allergy. METHODS: Seven bibliographic databases will be searched from their inception to September 30, 2012 for systematic reviews, randomized controlled trials, quasi-randomized controlled trials, controlled clinical trials, controlled before-and-after studies, interrupted time series and cohort studies. Cohort studies will be included due to an inability to randomize with interventions such as breastfeeding. Studies that focused on the development of either food sensitization (a proxy measure) or food allergy will also be eligible for inclusion. Studies will be critically appraised using the Critical Appraisal Skills Program and Cochrane Risk of Bias tools, as appropriate. DISCUSSION: There is a lack of rigorous evidence to support recommendations about how to prevent the development of food allergy. It would appear that it is important to see the prevention of food allergy in the context of individual, family and wider factors that may influence its development. There is much left to learn about preventing food allergy, and this is a priority given the high societal and healthcare costs involved. This systematic review will help to further this learning.
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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 | 0.105 | 0.156 |
| Meta-epidemiology (narrow) | 0.007 | 0.007 |
| Meta-epidemiology (broad) | 0.020 | 0.017 |
| Bibliometrics | 0.013 | 0.018 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.168 | 0.029 |
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".