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Record W4327811679 · doi:10.1007/s10815-023-02757-4

The HERA (Hyper-response Risk Assessment) Delphi consensus definition of hyper-responders for in-vitro fertilization

2023· article· en· W4327811679 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Assisted Reproduction and Genetics · 2023
Typearticle
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsMcGill University Health CentreOttawa Fertility Centre
Fundersnot available
KeywordsIn vitro fertilisationReproductive medicineRisk assessmentMedicineDelphi methodMEDLINEOncologyBiologyInternal medicineBioinformaticsComputer scienceGeneticsPregnancyArtificial intelligence

Abstract

fetched live from OpenAlex

PURPOSE: To provide an agreed upon definition of hyper-response for women undergoing ovarian stimulation (OS)? METHODS: A literature search was performed regarding hyper-response to ovarian stimulation for assisted reproductive technology. A scientific committee consisting of 5 experts discussed, amended, and selected the final statements in the questionnaire for the first round of the Delphi consensus. The questionnaire was distributed to 31 experts, 22 of whom responded (with representation selected for global coverage), each anonymous to the others. A priori, it was decided that consensus would be reached when ≥ 66% of the participants agreed and ≤ 3 rounds would be used to obtain this consensus. RESULTS: 17/18 statements reached consensus. The most relevant are summarized here. (I) Definition of a hyper-response: Collection of ≥ 15 oocytes is characterized as a hyper-response (72.7% agreement). OHSS is not relevant for the definition of hyper-response if the number of collected oocytes is above a threshold (≥ 15) (77.3% agreement). The most important factor in defining a hyper-response during stimulation is the number of follicles ≥ 10 mm in mean diameter (86.4% agreement). (II) Risk factors for hyper-response: AMH values (95.5% agreement), AFC (95.5% agreement), patient's age (77.3% agreement) but not ovarian volume (72.7% agreement). In a patient without previous ovarian stimulation, the most important risk factor for a hyper-response is the antral follicular count (AFC) (68.2% agreement). In a patient without previous ovarian stimulation, when AMH and AFC are discordant, one suggesting a hyper-response and the other not, AFC is the more reliable marker (68.2% agreement). The lowest serum AMH value that would place one at risk for a hyper-response is ≥ 2 ng/ml (14.3 pmol/L) (72.7% agreement). The lowest AFC that would place one at risk for a hyper-response is ≥ 18 (81.8% agreement). Women with polycystic ovarian syndrome (PCOS) as per Rotterdam criteria are at a higher risk of hyper-response than women without PCOS with equivalent follicle counts and gonadotropin doses during ovarian stimulation for IVF (86.4% agreement). No consensus was reached regarding the number of growing follicles ≥ 10 mm that would define a hyper-response. CONCLUSION: The definition of hyper-response and its risk factors can be useful for harmonizing research, improving understanding of the subject, and tailoring patient care.

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.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.050
GPT teacher head0.323
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