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DIAGNOSIS AND CONSERVATIVE TREATMENT OF FUNCTIONAL DISORDERS OF DEFECATION

2016· article· en· W2950136961 on OpenAlexaboutno aff
O. U. Fomenko, Andrei Titov, O. M. Birukov, А. А. Мудров, С. В. Белоусова, Д. В. Егорова

Bibliographic record

VenueKoloproktologia · 2016
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsnot available
Fundersnot available
KeywordsDyssynergiaDefecationMedicineBiofeedbackPelvic floorDefecographyConstipationFunctional constipationAnorectal manometryObstructed defecationPhysical therapySurgerySphincter

Abstract

fetched live from OpenAlex

90 patients (female 72 (80%), male 18 (20%), mean age 43,6±16,5 y.o.) with functional disorders of defecation (dyssynergic defecation and inadequate propulsion) were included in the study. All the patients conformed the Rome III (2006) criteria for functional constipation. Highresolution anorectal manometry (HRAM) procedures (London protocol) were performed using Solar GI system (MMS, The Netherland) with 8-channel water-perfusion catheters. All the patients underwent a course of biofeedback therapy for obstructive defecation (Urostim, Laborie, Canada). The course consisted of 10 daily 30-minutes long sessions. Treatment efficacy was evaluated after the completion of biofeedback therapy according to the control HRAM. CONCLUSIONS. Biofeedback is the method of choice for treatment of patients with obstructive defecation syndrome with pelvic floor dyssynergia and spasm of m.puborectalis. At the same time biofeedback therapy is ineffective in patients with type III of manometry pattern and in patients with an inadequate propulsion.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.039
GPT teacher head0.268
Teacher spread0.230 · 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 designNot applicable
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

Citations8
Published2016
Admission routes1
Has abstractyes

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