Impact of Neurodevelopmental Disorders on Bowel Management Outcomes in Children with Functional Constipation
Bibliographic record
Abstract
OBJECTIVES: Patients experiencing functional constipation (FC) can participate in structured bowel management programs (BMPs) to manage constipation or fecal incontinence when standard management fails. We sought to evaluate the efficacy of BMPs for children with FC with and without neurodevelopmental disorders. METHODS: We performed a retrospective review of children with FC who participated in our BMP from 2014 to 2021. Stool/urinary continence, bowel regimen, surgical history, parent-reported outcomes measures (PROMs: Cleveland Clinic Constipation Score, Baylor Continence Scale, Vancouver Symptom Score for Dysfunctional Elimination), and Pediatric Quality of Life Inventory (PedsQL) were assessed pre- and at least 9 months post-BMP. RESULTS: The cohort included 156 patients with a median age of 9 years and follow-up of 627 days (IQR: 389-808 days). Two sub-cohorts included patients with FC only (69%) and FC plus a neurodevelopmental disorder (31%): 59% attention-deficit/hyperactivity disorder, 33% autism spectrum disorder, and 8% obsessive-compulsive disorder. Both groups had significantly improved follow-up bowel movement frequency and continence (39%-90% neurodevelopmental, 44%-82% FC only, P < 0.001) and urinary continence (65%-90% neurodevelopmental, 69%-91% FC only, P < 0.02). There was a significant improvement in most of the PROMs at follow-up. Both groups experienced a clinically meaningful improvement in overall PedsQL scores (pre- and postBMP difference of >4.5). CONCLUSIONS: Patients with FC with and without a neurodevelopmental disorder had significant improvement in stool and urinary continence after undergoing a BMP. Further studies are needed to see if this improvement is durable over a longer period of time in this challenging cohort.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".