Consensus on Safe Initiation and Monitoring of Transanal Irrigation to Optimize Adherence With Therapy
Bibliographic record
Abstract
BACKGROUND: Transanal irrigation is a well-established minimally invasive therapy that addresses symptoms of both constipation and incontinence. The therapy has been extended from just neurogenic bowel dysfunction patients to those with disorders of brain-gut interaction and postsurgical conditions. AIM: To summarized the literature on transanal irrigation and update the contraindication profile. MATERIALS AND METHODS: We undertook a literature review of transanal irrigation complications and outcomes. RESULTS: Initiation of therapy as part of a bowel care regime is becoming more common outside specialist centers. In addition, the concept of both high- and low-volume irrigation schedules has entered the treatment paradigm, and it is clear that there is a differing safety profile. We present an update from the previous long list of contraindications. DISCUSSION: We describe how optimizing long-term adherence depends on these factors in addition to a structured follow-up programme. CONCLUSION: Transanal irrigation is an increasingly used therapy, with a good safety profile, further improved by the advent of low-volume irrigation options. Key to safe and effective usage of transanal irrigation is careful patient selection allied to tailored initial training of the patient.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".