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Could the anatomic location of Essure® device explain the impairment of quality of life?

2022· article· en· W4223979243 on OpenAlexaboutno aff
G. Chêne, E. Cerruto, Stéphanie Moret, E. Nohuz

Bibliographic record

VenueMinerva Obstetrics and Gynecology · 2022
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEssureQuality of life (healthcare)CohortVisual analogue scaleSurgeryMcGill Pain QuestionnairePhysical therapyInternal medicinePopulation

Abstract

fetched live from OpenAlex

BACKGROUND: Since health-related quality of life (HRQL) could improve after removal of Essure® (Bayer, Leverkusen, Germany) inserts in symptomatic patients, we aimed to assess whether such postoperative enhancement was linked to the anatomic placement of the device.METHODS: Correct and incorrect placed Essure® (Bayer) were identified in the electronic database of the French cohort Ablimco (cohort of consenting patients with laparoscopic Essure® [Bayer] removal). HRQL, pain and heavy menstrual bleeding were evaluated after Essure® (Bayer) removal with validated quality of life questionnaires (Short Form12 Questionnaire, Visual Analogue Scale, French version of the McGill Pain Questionnaire and the pictorial blood assessment chart PBAC).RESULTS: Sixty-five patients were included in the study divided in two groups (group A with correct placement: 45 patients and group B with incorrect placement: 20 patients). HRQL and Pain Index were improved in both groups at 6 months post-surgery. There was not any statistically significant difference between group A and B. The PBAC score increased at 6 months postoperatively in group A and B without any statistically significant difference between them.CONCLUSIONS: Postoperative improvement of quality of life and pain index was similar whatever the position of the implant. This suggests that symptomatology and quality of life are not related to the anatomic location of the Essure® (Bayer) implants.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalmedium
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.006
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 score0.142
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.037
GPT teacher head0.309
Teacher spread0.273 · 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

Labeled directly by 2 models reading the full record.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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