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Record W2888606526 · doi:10.4103/gmit.gmit_57_18

Effect of vaginal estriol use in total laparoscopic hysterectomy with gonadotropin-releasing hormone agonist therapy

2018· article· en· W2888606526 on OpenAlexaboutno aff
Go Hirata, Hiroshi Yoshida, Atsuko Furuno, Masakazu Kitagawa, Hideya Sakakibara

Bibliographic record

VenueGynecology and Minimally Invasive Therapy · 2018
Typearticle
Languageen
FieldMedicine
TopicUterine Myomas and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAgonistGonadotropin-releasing hormone agonistEstriolHysterectomyUrologyGynecologyHormoneGonadotropin-releasing hormoneInternal medicineSurgeryReceptorLuteinizing hormone

Abstract

fetched live from OpenAlex

Study Objectives: The aim of this study is to evaluate the effects of vaginal estriol therapy in total laparoscopic hysterectomy (TLH) with gonadotropin-releasing hormone agonist (GnRH-a) treatment.Design: Retrospective analysis.Design Classification: Canadian Task Force classification II-2.Settings: Department of Gynecology, Yokohama City University Medical Center, Japan.Methods: We retrospectively investigated 50 fibroid cases that had TLH with preoperative GnRH-a treatment and compared the surgical outcome with or without vaginal estriol use (1mg). Estriol was used administered for two weeks before TLH. Measurements and Main Results: A total of 12 patients (27%) received vaginal estriol (1 mg) for 14 days before TLH. As a result of vaginal estriol treatment, there were no group differences in uterus size reduction with GnRH-a treatment (22% vs. 15%, P = 0.20), uterine removal time through the vagina (12.5 min vs. 18.5 min, P = 0.18), rate of vaginal dehiscence (3% vs. 0%, P = 0.76) or in the rate of perineal laceration (33% vs. 34%, P = 0.55).Conclusion: The use of vaginal estriol treatment before TLH with GnRH-a therapy did not improve surgical outcomes.

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)0.000
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 score0.153
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.016
GPT teacher head0.273
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 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

Citations3
Published2018
Admission routes1
Has abstractyes

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