Clinical factors associated with unexpected poor or suboptimal response in Poseidon criteria patients
Bibliographic record
Abstract
RESEARCH QUESTION: What clinical factors are associated with 'unexpected' poor or suboptimal responses to IVF ovarian stimulation per POSEIDON's criteria, and which AMH and AFC threshold values distinguish this population? DESIGN: Tri-centre retrospective cohort study (2015-2017) involving first-time IVF and ICSI cycles with conventional ovarian stimulation (≥150 IU/day of FSH). Eligibility criteria included sufficient ovarian reserve markers according to POSEIDON's classification (AMH ≥1.2 ng/ml; AFC ≥5). Ovarian response categories were poor (<4 oocytes), suboptimal (4-9 oocytes) and normal (≥9 oocytes). Primary outcomes included clinical factors associated with an unexpected poor or suboptimal response to conventional ovarian stimulation using logistic regression analyses, and the threshold values of AMH and AFC predicting increased risk of such responses using ROC curves. RESULTS: A total of 7625 patients met the inclusion criteria: 204 (9.3%) were poor and 1998 (90.7%) were suboptimal responders. Logistic regression identified significant clinical predictors for a poor or suboptimal response, including AFC, AMH, total gonadotrophin dose, gonadotrophin type and trigger type (P ≤ 0.02). The ROC curves indicated that AMH 2.87 ng/ml (AUC 0.740) and AFC 12 (AUC 0.826) were the threshold values predicting a poor or suboptimal response; AMH 2.17 ng/ml (AUC 0.741) and AFC 9 (AUC 0.835) predicted a poor response; and AMH 2.97 ng/ml (AUC 0.722) and AFC 12 (AUC 0.801) predicted a suboptimal response. CONCLUSIONS: The threshold values of AMH and AFC predicting 'unexpected' poor or suboptimal response were higher than expected. These findings have critical implications for tailoring IVF stimulation regimens and dosages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".