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Record W2552584623 · doi:10.5489/cuaj.3703

A sequential comparison of postoperative voiding function between two different transobturator sling procedures

2016· article· en· W2552584623 on OpenAlexvenueno aff
Don Kyoung Choi, Ha Bum Jung, Young Goo Lee, Ki Kyung Kim, Sung Tae Cho

Bibliographic record

VenueCanadian Urological Association Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsnot available
Fundersnot available
KeywordsSling (weapon)MedicineUrologySurgery

Abstract

fetched live from OpenAlex

INTRODUCTION: ) in patients with stress urinary incontinence. METHODS: Ninety-one women diagnosed with urodynamic stress incontinence were randomly assigned to the study. All enrolled patients underwent Monarc or ALIGN procedure. They were postoperatively evaluated at one day, one week, one month, three months, 12 months, and 24 months. The voiding function was evaluated with uroflowmetry and post-void residual urine. Patients were asked if voiding had changed after surgery and had to complete the incontinence quality of life scale (I-QoL) questionnaire at 12 months. RESULTS: The Monarc (n=47) and ALIGN (n=44) groups had similar demographic characteristics. The maximal flow rate (Qmax) was significantly decreased on the first day after surgery and gradually increased during the following weeks. Comparing the two groups at one week, the ALIGN group had a significantly decreased Qmax than the Monarc group (17.6 ± 5.2 vs. 20.7 ± 5.0; p=0.004). However, at one, three, 12, and 24 months, there were no significant differences between the two groups. CONCLUSIONS: This study demonstrated that an absorbable tensioning suture in the Monarc mesh could increase Qmax compared to ALIGN at one week after surgery. An absorbable tensioning suture may reduce the risk of an early postoperative voiding dysfunction compared to other meshes that do not have this.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.026
GPT teacher head0.283
Teacher spread0.257 · 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 designObservational
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

Citations0
Published2016
Admission routes1
Has abstractyes

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