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Record W2596648157 · doi:10.12998/wjcc.v5.i3.124

Neurostimulation for fecal incontinence after correction of repair of imperforate anus

2017· article· en· W2596648157 on OpenAlexaff
Alexandre Bougie, Nathalie McFadden, Sandeep Mayer, Michel Lebel, Ghislain Devroede

Bibliographic record

VenueWorld Journal of Clinical Cases · 2017
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversité de SherbrookeCentre Hospitalier Universitaire de Sherbrooke
Fundersnot available
KeywordsImperforate anusMedicineFecal incontinenceAnusSurgeryNeurostimulation

Abstract

fetched live from OpenAlex

We are reporting the case of a 32-year-old female who had suffered from fecal incontinence (FI). She was born with an imperforate anus and a recto-vaginal fistula; she underwent repair at 6 mo of age. At 29 years of age, she was still fecally incontinent despite extensive pelvic floor reeducation. A magnetic resonance imaging and an anal electromyography were performed. Because her symptoms were considered to be probably due to extra-sphincteric implantation of the neo-anus, a redo was performed of the recto-neo-anal intra-sphincteric anastomosis. A neurostimulator device was subsequently implanted for persistent incontinence. Solid and liquid FI resolved, and her quality of life improved markedly. Combining surgery to correct the position of the neo-anus within the anal sphincter complex and neurostimulation could thus become a new approach in cases of refractory FI for patients with imperforate anus as a newborn. Follow-up into adulthood after pediatric imperforate anus surgery should be recommended for adult patients with persistent FI.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.422
Teacher spread0.347 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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

Citations1
Published2017
Admission routes1
Has abstractyes

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