Efficacy and Safety of Different Treatment Strategies in Pediatric Fecal Incontinence: A Systematic Review
Bibliographic record
Abstract
Background Fecal incontinence (FI) in children is a challenging condition with significant impacts on quality of life (QoL). Multiple therapeutic approaches, including neuromodulation techniques such as sacral nerve stimulation (SNS), biofeedback therapy, botulinum toxin (Botox) injections, and transcutaneous functional electrical stimulation (TFES), have been explored. This systematic review evaluates the efficacy and safety of these interventions in pediatric patients. Methods A thorough investigation was performed in PubMed, Scopus, Web of Science, and the Cochrane Library databases up to February 2025. Studies assessing the effectiveness and safety of SNS, biofeedback, Botox injections, and other interventions in pediatric FI were included. Risk of bias was assessed using the Newcastle-Ottawa Scale (NOS) for observational studies and the Cochrane Risk of Bias 2.0 tool for randomized controlled trials (RCTs). Results A total of 12 studies were included, comprising RCTs and observational cohort studies. Biofeedback therapy demonstrated consistent improvements in incontinence scores, anorectal pressures, and QoL. SNS was effective in refractory cases but was linked to an increased incidence of complications. Botox injections showed promising short-term benefits, particularly in Hirschsprung’s disease, while TFES exhibited potential as a noninvasive alternative. Comparisons between interventions highlighted the need for individualized treatment selection based on patient characteristics and response to initial therapy. Conclusion Neuromodulation techniques and adjunctive therapies provide effective management options for pediatric FI. Biofeedback and TFES serve as viable first-line therapies, while SNS and Botox injections are effective in refractory cases. Further high-quality, long-term studies are needed to refine treatment algorithms and optimize patient outcomes.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".