MétaCan
Menu
Back to cohort
Record W2993002825 · doi:10.5539/jmbr.v9n1p67

Evaluation of Fractional CO2 Laser Treatment Efficacy and Comparison to Vaginal Conjugated Estrogen Cream in Postmenopausal Women with Vulvovaginal Atrophy: A Randomized Clinical Trial

2019· article· en· W2993002825 on OpenAlexvenueno aff
Mahin Najafian, Kobra Shojaei, Saadat Hajatzadeh

Bibliographic record

VenueJournal of Molecular Biology Research · 2019
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVaginal atrophyAtrophyRandomized controlled trialEstrogenSexual functionVaginaGynecologyClinical trialPostmenopausal womenInternal medicineObstetricsSurgery

Abstract

fetched live from OpenAlex

Background: Vulvovaginal atrophy is common and bothersome among postmenopausal women. Hence in this study, the fractional CO2 laser treatment efficacy was compared with vaginal conjugated estrogen cream in postmenopausal women with vulvovaginal atrophy was assessed. Materials and Methods: In this randomized clinical trial, 130 consecutive postmenopausal women with vulvovaginal atrophy attending to urogynecologic clinic in Imam-Khomeini hospital in Ahvaz in 2015 were enrolled and were randomly assigned to receive either fractional CO2 laser treatment or vaginal conjugated estrogen cream. The improvement of vulvovaginal atrophy symptoms, sexual satisfaction and function were compared across the groups after 12 weeks. Results: There improvement of vulvovaginal atrophy symptoms, sexual satisfaction, and function were 86.2%, 87.7%, and 87.7%, respectively in laser group and 53.8%, 52.3%, and 52.3%, respectively in primarin group showing statistically significant differences (P=0.0001). There were no side effects. Conclusion: Totally, according to obtained results, it may be concluded that efficacy of fractional CO2 laser was higher than vaginal conjugated estrogen cream in postmenopausal women with vulvovaginal atrophy.

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)0.013
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.131
GPT teacher head0.513
Teacher spread0.382 · 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 designRandomized 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Molecular Biology ResearchSame topicMenopause: Health Impacts and TreatmentsFrench-language works237,207