The Role of Maternal and Infant Diet in the Management of Infantile Colic: A Comprehensive Review
Bibliographic record
Abstract
This systematic review aims to determine the effects of maternal and infant diet on the incidence and treatment of infant colic with emphasis on dietary modifications and its potential to reduce the symptoms. The role of maternal and infant diet on psychological health of the mother and breastfeeding practices as risk factors in reducing the frequency of colic episodes has been highlighted. The role of maternal gut microbiota composition especially the bacterial enterotypes has been discussed with relation to colic. Also, the efficacy of probiotics especially the Lactobacillus reuteri strains has been evaluated with variable results depending upon the strain and the dose used. The review discusses how the definitions and criteria used, for instance Wessel and Rome IV, influence the perception of incidence and nature of colic. It also includes descriptive content analysis of various researches where cultural and socio-economic factors including maternal empowerment in different contexts are discussed in relation to the management plans. The analysis of meta-analysis and risk of bias studies enhances the conclusions and offers practical recommendations on dietary interventions. The present study reveals that the personalized dietary approaches are effective and at the same time points out the need to fill the research gaps in order to provide better solutions for parents of colicky infants.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".