The Effectiveness of Early Food Introduction in Preventing Childhood Allergic Diseases: Protocol for a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background Allergic diseases affect around 40% of the pediatric population worldwide. The coexistence of asthma, allergic rhinitis, eczema, and food allergy renders allergy treatment and prevention challenging. Infant feeding strategies recommend avoiding allergenic foods to prevent allergy development and anaphylaxis. However, recent evidence suggests that early consumption of food allergens during weaning in infants aged 4-6 months could result in food tolerance, thus reducing the risk of developing allergies. Objective The aim of this study is to systematically review and carry out a meta-analysis of evidence on the outcome of early food introduction for preventing childhood allergic diseases. Methods We will conduct a systematic review of interventions through a comprehensive search of various databases including PubMed, Embase, Scopus, CENTRAL, PsycINFO, CINAHL, and Google Scholar to identify potential studies. The search will be performed for any eligible articles from the earliest published articles up to the latest available studies in 2023. We will include randomized controlled trials (RCTs), cluster RCTs, non-RCTs, and other observational studies that assess the effect of early food introduction to prevent childhood allergic diseases. Results Primary outcomes will include measures related to the effect of childhood allergic diseases (ie, asthma, allergic rhinitis, eczema, and food allergy). PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines will be followed for study selection. All data will be extracted using a standardized data extraction form and the quality of the studies will be assessed using the Cochrane Risk of Bias tool. A summary of findings table will be generated for the following outcomes: (1) total number of allergic diseases, (2) rate of sensitization, (3) total number of adverse events, (4) improvement of health-related quality of life, and (5) all-cause mortality. Descriptive and meta-analyses will be performed using a random-effects model in Review Manager (Cochrane). Heterogeneity among selected studies will be assessed using the I2 statistic and explored through meta-regression and subgroup analyses. Data collection is expected to start in June 2023. Conclusions The results acquired from this study will contribute to the existing literature and harmonize recommendations for infant feeding with regard to the prevention of childhood allergic diseases. Trial Registration PROSPERO CRD42021256776; https://tinyurl.com/4j272y8a International Registered Report Identifier (IRRID) PRR1-10.2196/46816
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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 | 0.069 | 0.092 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.030 | 0.044 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.057 | 0.005 |
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".