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Record W2343018619

Should we diagnose and treat minimal and mild endometriosis before medically assisted reproduction?

2016· article· en· W2343018619 on OpenAlexaff
Annie Leung, Michael H. Dahan

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsRoyal Victoria Hospital
Fundersnot available
KeywordsMedicineEndometriosisIntrauterine inseminationOvulation inductionPregnancyIn vitro fertilisationAssisted reproductive technologyOvulationObstetricsGynecologyFertilityPregnancy rateInfertilityHormoneEndocrinologyPopulation
DOInot available

Abstract

fetched live from OpenAlex

The treatment of minimal or mild endometriosis prior to assisted reproduction (ranging from intrauterine insemination to in vitro fertilization [IVF]) to improve the likelihood of success is controversial. Ovulation suppression is commonly used in endometriosis to decrease pain, however, there is little evidence to suggest improvements in fertility associated with this technique. Moreover, current evidence is sparse and does not support ovarian suppression prior to intrauterine insemination with or without ovulation induction, while there is some evidence favoring ovarian suppression with gonadotropin releasing hormone agonists prior to IVF to improve pregnancy rates. However, the majority of studies were performed in women with moderate to severe endometriosis. There is currently conflicting evidence regarding surgical ablation or removal of endometriomas prior to IVF, and its outcome on pregnancy rates. This review highlights the paucity of data in the management of endometriosis prior to assisted reproductive technologies and suggests that further studies are needed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.062
GPT teacher head0.305
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2016
Admission routes1
Has abstractyes

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Same venuePubMed→Same topicEndometriosis Research and Treatment→French-language works237,207→