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Record W4236095482 · doi:10.21203/rs.3.rs-247137/v1

Current Practices on Diagnosis and Management of Women With Vulvodynia

2021· preprint· en· W4236095482 on OpenAlexafffund
Marcela Grigol Bardin, Paulo César Giraldo, Júlia Ferreira Fante, Camila Carvalho de Araújo, Marie‐Pierre Cyr, Andrea de Andrade Marques

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsUniversité de Sherbrooke
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorUniversité de Sherbrooke
KeywordsVulvodyniaMedicineLikert scalePelvic painPhysical therapySurgeryPsychology

Abstract

fetched live from OpenAlex

Abstract Introduction and hypothesis : To describe clinical characteristics, previous medical assessment, past treatments and vulvar pain relief among women with vulvodynia. Methods Brazilian women with vulvodynia (n = 144) were assessed for vaginal infection and vulvar pain intensity by means of a cotton swab test based on a numerical rate scale (NRS). All women answered the Female Sexual Function Index questionnaire and a structured instrument about present vulvar symptoms and previously experienced treatments. Vulvar pain relief achieved with previous treatments was qualified through a 4-point Likert-scale. Results Previous vulvar pain duration was 5.8 (± 4) years. More than 50% consulted with three or more physicians and 49% remained without a conclusive diagnosis. Diagnosis and treatment vulvovaginal infection was very common. The most commonly used treatments were lubricants (66%), topical anesthetics (36%) and vulvar care techniques (36%). All of then provided only low pain relief. Physical therapy and oral gabapentin provided strong vulvar pain relief. Conclusion Prolonged duration of vulvar pain, multiple visits to healthcare professionals and poor relief of pain are common aspects in the clinical history of women with vulvodynia. Vulvovaginal symptoms other than pain are common, highlighting the importance of the screening tests in order to avoid misdiagnosis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.307
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.194
GPT teacher head0.479
Teacher spread0.286 · 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 teacher head, 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
Published2021
Admission routes2
Has abstractyes

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