Quality of Life of Infants with Functional Gastrointestinal Disorders: A Large Prospective Observational Study
Bibliographic record
Abstract
Background: Functional gastrointestinal disorders (FGID) are very common during infancy, leading to frequent medical consultations. The aim of this large, prospective study was to assess the quality of life (QoL) and clinical management of infants with FGID. Methods: Completely or partially bottle-fed infants under 5 months old, presenting one or more FGID (regurgitation, constipation, diarrhea, crying/fussing), were enrolled during initial consultation by 111 pediatricians in private practice throughout France and reassessed at one month. Parents were asked to complete the QUALIN QoL questionnaire at inclusion and at Day 15. Results: A total of 815 infants (mean age 2.1±1.2 months) were evaluable. Mean QoL score improved from +27.2±15.1 at inclusion to +38.0±12.9 at day 15 (p<0.0001) irrespective of FGID symptoms. Multivariate analysis indicated that younger age, dietary advice, and partial breastfeeding were associated with better QoL outcome. Gastrointestinal symptoms showed significant regression at Day 30. The number of bottle feeds followed by external reflux episodes decreased from 80.0±27.4% to 36.1±31.4% at Day 30 (p<0.0001), the weekly number of stools increasing from 3.9±4.0 to 8.0±3.7 (p<0.0001). Conclusion: Medical management based on information, reassurance, lifestyle advice and dietary intervention improved QoL in infants with FGID and led to a reduction in FGID symptoms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".