Transanal surgery for obstructed defecation syndrome: Literature review and a single-center experience
Bibliographic record
Abstract
Obstructed defecation syndrome (ODS) is a functional disorder commonly encountered by colorectal surgeons and gastroenterologists, and greatly affects the quality of life of patients from both societal and psychological aspects. The underlying anatomical and pathophysiological changes of ODS are complex. However, intra-rectal intussusception and rectocele are frequently found in patients with ODS and both are thought to play an important role in the pathogenesis of ODS. With the development of evaluation methods in anorectal physiology laboratories and radiology studies, a great variety of new operative procedures, especially transanal procedures, have been invented to treat ODS. However, no procedure has been proved to be superior to others at present. Each operation has its own merits and defects. Thus, choosing appropriate transanal surgical procedures for the treatment of ODS remains a challenge for all surgeons. This review provides an introduction of the current problems and options for treatment of ODS and a detailed summary of the essential assessments needed for patient evaluation before carrying out transanal surgery. Besides, an overview of the benefits and problems of current transanal surgical procedures for treatment of ODS is summarized in this review. A report of clinical experience of some transanal surgical techniques used in the authors' center is also presented.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".