Challenging the view that lack of fibre causes childhood constipation
Bibliographic record
Abstract
OBJECTIVES: childhood constipation'. DESIGN: Triangulation integrated three approaches: a systematic review NICE guideline CG99 examining effectiveness of increasing fibre; a cohort study, Avon Longitudinal Study of Parents and Children (ALSPAC), to assess if constipation (or hard stools) can precede fibre intake at weaning; and a literature search for twin studies to calculate heredity. SETTING: CG99 examined the literature regarding the effectiveness of increasing fibre. ALSPAC asked parents about: hard stools at 4 weeks, 6 months and 2.5 years and constipation at age 4-10 years, as well as fibre intake at 2 years. Twin studies and data from ALSPAC were pooled to calculate concordance of constipation comparing monozygotic and dizygous twin pairs. PARTICIPANTS: CG99 reported six randomised controlled trials (RCTs). ALSPAC hard stool data from 6796 children at 4 weeks, 9828 at 6 months and 9452 at 2.5 years plus constipation data on 8401 at 4-10 years were compared with fibre intake at 2 years. Twin studies had 338 and 93 twin pairs and ALSPAC added a further 45. RESULTS: Increasing fibre did not effectively treat constipation. Hard stools at 4 weeks predated fibre and at 6 months predicted lower fibre intake at 2 years (p=0.003). Heredity explained 59% of constipation. CONCLUSIONS: RCTs indicate that increasing fibre is not an effective treatment for constipation in children. Hard stools can precede and predict later fibre intake. Genetic inheritance explains most childhood constipation. Extended treatment with stool softeners may improve fibre intake and limit long-term damaging sequelae of constipation.
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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 | 0.131 | 0.313 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".