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Record W133052617 · doi:10.1155/2002/417530

The Physiology, Pharmacology and Therapeutic Manipulation of the Internal Anal Sphincter

2002· review· en· W133052617 on OpenAlexvenueno aff
Oliver Jones, Alison F. Brading, N J McC Mortensen

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2002
Typereview
Languageen
FieldMedicine
TopicAnorectal Disease Treatments and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsInternal anal sphincterMedicineSphincterUrethral sphincterIntensive care medicineMedical literatureAnal sphincterSurgeryAnal canalRectumUrinary incontinence

Abstract

fetched live from OpenAlex

Recent research into the physiology and pharmacology of the internal anal sphincter has elucidated the importance of this structure in health and disease. Its pharmacological manipulation for therapeutic gain has focused mainly on agents to reduce internal anal sphincter tone, a 'chemical sphincterotomy' that might heal chronic anal fissure. However, drugs to increase sphincter tone, and augment intermittent and appropriate relaxation are also being evaluated. The initial results with this medical approach to anorectal disease have often been disappointing, failing to match the results achievable with surgery, and many of these drugs have a high rate of side effects in the short term. However, clinical trials have yet to establish the optimum doses, dose intervals and routes of administration for many of these therapies. Furthermore, it is uncertain whether this medical approach should be applied to all patients or just to an as yet undefined subgroup. Certainly, even in the current environment of uncertainty, there is little reason not to try medical manipulation of the internal sphincter as first-line treatment. Surgery remains an option for treatment failures; patients responding to pharmacological manipulation of the internal anal sphincter are spared the long term risks of continence that are inherent in many surgical procedures on the anorectum.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.808
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.308
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations22
Published2002
Admission routes1
Has abstractyes

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