Multiple functional gastrointestinal disorders are frequent in formula‐fed infants and decrease their quality of life
Bibliographic record
Abstract
AIM: This prospective study evaluated the incidence of functional gastrointestinal disorders (FGIDs) during infancy, on their own or combined with other symptoms. METHODS: We asked 273 French paediatricians with a specific interest in FGIDs to provide feedback on 2757 infants aged zero to six months from March 2013 to January 2014. Gastrointestinal health status was assessed by two questionnaires at inclusion and at a four-week follow-up visit. FGIDs were assessed according to the Rome III criteria and quality of life (QoL) was monitored. RESULTS: Combined FGIDs were diagnosed in 2145 (78%) infants: 63% with two disorders and 15% with three or more disorders. The most frequently combined FGIDs were gas/bloating and colic (28%), colic and regurgitation (17.0%) and gas/bloating and regurgitation (8%). Compared to infants with a single FGID, combined FGID were associated with lower body weight (4.63 vs 4.79 kg, p = 0.009), shorter breastfeeding duration (33 vs 43 days, p < 0.001), a decreased QoL score (5.9 vs 6.5, p < 0.001), more frequent drug prescriptions (25% vs 13%, p < 0.001) and significantly greater improvements in QoL scores after four weeks (p = 0.003). CONCLUSION: Combined FGIDs were extremely common in infants up to six months of age and had a negative impact on breastfeeding, weight gain and QoL.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".