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Record W6995496826

Office vaginoscopic hysteroscopic in infertle women: effects of gynecologist experience, instrument size and distention medium on patients discomfort

2010· article· en· W6995496826 on OpenAlexaboutno aff

Bibliographic record

VenueCINECA IRIS Institutial research information system (University of Pisa) · 2010
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsnot available
Fundersnot available
KeywordsVisual analogue scaleHysteroscopyPatient satisfactionSalineRandomized controlled trialMulticenter studyProspective cohort studyInfertility
DOInot available

Abstract

fetched live from OpenAlex

STUDY OBJECTIVE: To assess the roles of instrument diameter (5.0- or 3.5-mm external sheath), uterine distention medium (carbon dioxide [CO(2)] or saline solution), and hysteroscopist experience in diagnostic hysteroscopy. DESIGN: Prospective, randomized, multicenter trial (Canadian Task Force classification I). SETTING: Two university medical centers in Italy. PATIENTS: One hundred eighty-four women attending an infertility clinic. INTERVENTIONS: Patients were randomly assigned to undergo conventional hysteroscopy (group 1, n = 92) or minihysteroscopy (group 2, n = 92) with CO(2) or saline solution as distention medium. The procedures were performed by hysteroscopists with varying degrees of experience. Patient discomfort was analyzed using the visual analog score. Procedure complications and patient satisfaction rate were also recorded. MEASUREMENTS AND MAIN RESULTS: Independent of hysteroscopist experience, less pain, fewer complications, and higher satisfaction rates were observed with minihysteroscopy. In addition, procedures in which saline solution was used resulted in less pain and fewer complications than those in which CO(2) was used, but only when performed by inexperienced hysteroscopists. CONCLUSION: Instrument diameter and hysteroscopist experience, but not the distention medium, seem to be the primary variables that affect the perception of discomfort during office hysteroscopy.

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)0.001
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 score0.020
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.307
Teacher spread0.282 · 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
Published2010
Admission routes1
Has abstractyes

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