The HERA (Hyper-response Risk Assessment) Delphi consensus for the management of hyper-responders in in vitro fertilization
Bibliographic record
Abstract
PURPOSE: To provide agreed-upon guidelines on the management of a hyper-responsive patient undergoing ovarian stimulation (OS) METHODS: A literature search was performed regarding the management of hyper-response to OS for assisted reproductive technology. A scientific committee consisting of 4 experts discussed, amended, and selected the final statements. 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. A total of 28/31 experts responded (selected for global coverage), anonymous to each other. RESULTS: A total of 26/28 statements reached consensus. The most relevant are summarized here. The target number of oocytes to be collected in a stimulation cycle for IVF in an anticipated hyper-responder is 15-19 (89.3% consensus). For a potential hyper-responder, it is preferable to achieve a hyper-response and freeze all than aim for a fresh transfer (71.4% consensus). GnRH agonists should be avoided for pituitary suppression in anticipated hyper-responders performing IVF (96.4% consensus). The preferred starting dose in the first IVF stimulation cycle of an anticipated hyper-responder of average weight is 150 IU/day (82.1% consensus). ICoasting in order to decrease the risk of OHSS should not be used (89.7% consensus). Metformin should be added before/during ovarian stimulation to anticipated hyper-responders only if the patient has PCOS and is insulin resistant (82.1% consensus). In the case of a hyper-response, a dopaminergic agent should be used only if hCG will be used as a trigger (including dual/double trigger) with or without a fresh transfer (67.9% consensus). After using a GnRH agonist trigger due to a perceived risk of OHSS, luteal phase rescue with hCG and an attempt of a fresh transfer is discouraged regardless of the number of oocytes collected (72.4% consensus). The choice of the FET protocol is not influenced by the fact that the patient is a hyper-responder (82.8% consensus). In the cases of freeze all due to OHSS risk, a FET cycle can be performed in the immediate first menstrual cycle (92.9% consensus). CONCLUSION: These guidelines for the management of hyper-response can be useful for tailoring patient care and for harmonizing future research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.187 | 0.142 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".