Cruise Control Study: Simplification of IVF Monitoring in a Mixed Protocol Using a Novel Dosing Regimen
Bibliographic record
Abstract
ABSTRACT Objective To identify the subset of the in vitro fertilization (IVF) population suitable for minimal monitoring by implementing a novel dosing regimen. Methods A retrospective study conducted between April 2021 and August 2022. Eligible participants were aged 18 or older, had undergone IVF stimulation using an antagonist protocol, and were prescribed a combination of follitropin delta and human menopausal gonadotropin. The dosage was either based on a patient-specific dosing regimen developed by the ovo clinic utilizing weight and AMH levels (Group 1, n=356) or determined through clinical evaluation by the physician (Group 2, n=358). On day 6, ultrasound and serum hormone analyses were performed, with adjustments made solely to the menotropin dosage in necessary. Results The study enrolled a total of 714 patients. In Group 1, 80,3% of patients were stimulated at maximal doses compared to 14,5% in Group 2. No cases of moderate or severe cases of ovarian hyperstimulation syndrome (OHSS) were recorded. The frequency of dose adjustments before day 10 was minimal. Patients treated with non-maximal doses according to the dosing regimen showed significantly fewer adjustments on day 6 compared to those treated according to physician’s assessment (24.6% versus 46.9%, p<0.001). Among this subgroup, OHSS risk was observed in 30.4% of cases. Conclusion Our innovative dosing regimen suggests that initial monitoring on day 10 would suffice for IVF patients with low ovarian reserve undergoing maximal stimulation.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".