A Systematic Review of Telehealth Utilization for Bowel Management Programs in Pediatric Colorectal Surgery
Bibliographic record
Abstract
Recent advancements in pediatric surgery have embraced telehealth (TH) modalities, transitioning from traditional in-person consultations to virtual care. This shift has broadened access to healthcare, potentially enhancing affordability, patient and caregiver satisfaction, and clinical outcomes. In pediatric colorectal surgery, telehealth has been effectively utilized to support Bowel Management Programs (BMPs) for children suffering from constipation and fecal incontinence. A systematic review was conducted to assess the effectiveness of virtual BMPs, analyzing studies from January 2010 to December 2023, sourced from MEDLINE (via PubMed), Embase, and the Cochrane Library, with five studies included. Remote BMPs, implemented through video or telephone consultations, reported satisfaction rates exceeding 75% among families, indicating a strong preference for virtual interactions over traditional visits. Significant findings from the studies include improvements in Vancouver and Baylor scores, reductions in the duration of multidisciplinary consultations, enhancements in pediatric quality of life and Cleveland scores, and decreased frequency of laxative treatments. The implementation of TH has facilitated patient-led care, enabling timely adjustments in treatment and efficient distribution of medical supplies. The findings suggest that virtual BMPs are a viable and effective alternative to conventional approaches, yielding high caregiver satisfaction and superior clinical outcomes while promoting patient independence.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".