Constipation and fecal incontinence in children with cerebral palsy. Overview of literature and flowchart for a stepwise approach.
Bibliographic record
Abstract
BACKGROUND AND STUDY AIMS: Constipation and fecal incontinence are common problems in neurologically impaired children. This paper aims to give an overview on bowel problems in cerebral palsy children and to suggest a stepwise treatment approach. A pubmed search was performed looking at studies during the past 20 years investigating bowel problems in neurologically disabled children. RESULTS: The search revealed 15 articles. Prevalence and presentation was the subject of 8 papers, confirming the importance of the problem in these children. The other papers studied the results of different treatment modalities. No significant differences between treatment modalities could be demonstrated due to small studied cohorts. Therefore, no specific treatment strategy is currently available. An experienced based stepwise approach is proposed starting with normalization of fiber intake. The evaluation of the colon transit time could help in deciding whether desimpaction and eventually laxatives including both osmotic (lactulose, macrogol) as well as stimulant laxatives might be indicated. Or, in case of fast transit loperamide or psyllium can be tried. Surgery should be a last resort option. CONCLUSION: Studies investigating constipation and continence in neurologically impaired children are scarce, making it difficult to choose for the optimal treatment. A stepwise treatment approach is proposed, measuring the colon transit time to guide treatment choices.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.026 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".