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Record W2016307022 · doi:10.1159/000328447

Effects of Percutaneous Tibial Nerve Stimulation Therapy on Chronic Pelvic Pain

2012· article· en· W2016307022 on OpenAlexfundno aff
Şule Gökyıldız Sürücü, Nezihe Kızılkaya Beji, Önay Yalçın, Ayse Istek

Bibliographic record

VenueGynecologic and Obstetric Investigation · 2012
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsnot available
FundersMcGill University
KeywordsMedicineQuality of life (healthcare)Pelvic painSexual lifePhysical therapyPercutaneousSurgeryGynecologyNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: This research is a prospective study which was designed to determine the effects of percutaneous tibial nerve stimulation (PTNS) therapy on the quality of life and sexual life of patients with chronic pelvic pain (CPP). METHODS: The sample consisted of an experimental group (n = 12) and a control group (n = 12), in total 24 patients. The experimental group was treated with PTNS once a week (in total 12 sessions), while the control group received routine intervention. RESULTS: The pain frequency and intensity in women who underwent PTNS decreased considerably. Women had less pain during sexual intercourse after PTNS. We determined in our study that PTNS improved the quality of life of women with CPP by decreasing the intensity of pain and contributed to a more comfortable performance of their daily activities. CONCLUSIONS: PTNS is a type of treatment which contributes to the quality of life of women with CPP by decreasing the intensity of pain.

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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.000

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 head0.029
GPT teacher head0.257
Teacher spread0.228 · 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 designNon-randomized trial
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

Citations57
Published2012
Admission routes1
Has abstractyes

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