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Record W2794860561 · doi:10.5489/cuaj.4976

Early experience with topical meloxicam and lidocaine combination for the treatment of vulvodynia

2018· article· en· W2794860561 on OpenAlexaffvenue
Rufina Kim, Kerri‐Lynn Kelly, Merle S. Olson, J. Curtis Nickel

Bibliographic record

VenueCanadian Urological Association Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsFoothills Medical CentreUniversity of AlbertaQueen's University
Fundersnot available
KeywordsVulvodyniaMedicineLidocainePelvic painMeloxicamInterstitial cystitisLikert scaleTopical anestheticPhysical therapyAnesthesiaUrinary systemSurgeryInternal medicinePsychology

Abstract

fetched live from OpenAlex

INTRODUCTION: We report our early clinical observations on the use of topical meloxicam and lidocaine gel for patients with vulvodynia. METHODS: This is an early experience in participants with a history of vulvodynia evaluated and treated at the Queen's University Pelvic and Bladder Pain Clinic. Combination meloxicam 0.3% and lidocaine 5% were provided to the participants and they were instructed to apply 5 cc to the vulvar area twice daily. Standardized assessment was conducted for each participant before the start of the topical therapy and again at one week, and included Interstitial Cystitis Symptom Index (ICSI), Interstitial Cystitis Problem Index (ICPI), and pain scoring (Likert) for vulvar pain, in addition to a subjective global assessment after a week of treatment. RESULTS: Of the eight participants, six had a subjective improvement in their symptoms with the use of the combination gel. They reported between one- and four-point reductions on the Likert pain scale and mild to moderate improvement of symptoms. Common side effects reported were burning and stinging. CONCLUSIONS: The results from this early experience are promising for a potentially effective topical treatment for vulvodynia.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.025
GPT teacher head0.268
Teacher spread0.242 · 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

Citations11
Published2018
Admission routes2
Has abstractyes

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