Expert opinion on refined and extended key performance indicators for individualized ovarian stimulation for assisted reproductive technology
Bibliographic record
Abstract
OBJECTIVE: To assess the adequate ovarian follicular development and oocyte recovery between ovarian potential (antral follicle count [AFC]) before the start of ovarian stimulation (OS) and oocyte quantity and quality at oocyte retrieval. A holistic overview of the current key performance indicators (KPIs) was applied to identify the complementary strengths and identify where the current repertoire can be expanded. DESIGN: Expert opinion. INTERVENTION: None. MAIN OUTCOME MEASURES: To formulate a proposal for a refined and expanded repertoire of KPIs for individualized OS for assisted reproductive technology. RESULTS: The performance and outcomes of OS on ovarian follicular development can be evaluated through the application of defined KPIs. Current KPIs for OS are the ovarian sensitivity index, follicular output rate (FORT), oocyte retrieval rate, and follicle-to-oocyte index (FOI). Notably, there are no specific KPIs dedicated to the assessment of follicular development (i.e., recruitment, selection, growth, and dominance). In light of this, we recommend expanding the current KPIs for OS to include "early FORT" (accounting for the number of follicles measuring ≥10 to 11 mm on day 5/6 of OS relative to AFC) and "modified FORT" (the ratio between the number of follicles measuring ≥12 mm at the time of oocyte maturation triggering and AFC); the extension of oocyte retrieval rate to include two discrete categories at oocyte retrieval-follicles measuring ≥12 mm and ≥16 mm-to ensure that all responsive follicles are accounted for; and FOI to be measured at oocyte maturation triggering and oocyte retrieval ("advanced FOI"). CONCLUSION: Once validated and adopted in clinical practice, we envisage that the proposed expanded KPIs measuring the effect of OS on follicular development (recruitment, selection, growth, and dominance) will increase the understanding of the relationship between ovarian reserve, measured by AFC, and oocyte quantity and quality at oocyte retrieval. This understanding will enable physicians to better evaluate the direct effect of different gonadotropins and doses on ovarian response, leading to a more personalized approach to OS in the context of assisted reproductive technology treatment.
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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 | 0.048 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".