O-186 The implementation of a novel algorithm for monitoring ovulation in an IVF mixed protocol may simplify stimulation monitoring
Bibliographic record
Abstract
Abstract Study question Which patients are eligible to skip ovulation monitoring before day 10 in In Vitro Fertilization (IVF) and what are the financial implications? Summary answer Thanks to our innovative gonadotropin prescription algorithm, patients with low ovarian reserve and maximum ovarian stimulation may not require monitoring until day 10 of IVF. What is known already In most fertility clinics, the standard procedure for IVF is early monitoring on day 6 of ovarian stimulation. Our focus is on personalizing the stimulation protocol by identifying the optimal dose of gonadotropin. With the aid of our unique algorithm, we aim to streamline monitoring. Frequent ultrasound examinations required for IVF can impose restrictions and create a burden for patients, resulting in increased costs for both patients and physicians. Study design, size, duration In a retrospective study conducted from April 2021 to August 2022 at the OVO clinic in Montreal (Canada), participants included all patients over 18 years old who underwent an IVF stimulation cycle utilizing an antagonist protocol and a customized mixed protocol prescription consisting of follitrophin delta and human menopausal gonadotropin, based on the patient's weight and anti-Mullerian hormone level. The sudy was approved by Veritas IRB, an independent ethic committee. Tracking number of study :2023-3189-13659-2 Participants/materials, setting, methods In the study, gonadotropin dosages were assigned either based on our algorithm (group 1) or at the physician's discretion (group 2). Ultrasound and hormonal analysis were performed on day 6. Following the physician's evaluation, adjustments to the gonadotropin dosage were made if necessary. The common trigger criteria was the presence of at least three follicles measuring between 16 and 22mm. Main results and the role of chance The study included 714 patients meeting the inclusion criteria. In group 1, there was a high percentage of patients stimulated with the maximum doses (80.3% compared to 22.5% in group 2). No dosage modifications or incidents of ovarian hyperstimulation syndrome were observed in group 1. Only 4.5% of patients (n = 16) triggered ovulation before day 10 (on day 9). In the non-maximal dose population, patients treated according to the algorithm (group A) experienced significantly fewer changes to the gonadotropin dosage at day 6 compared to patients treated based on the physician's discretion only (group B) (24.6% vs 46.9%, p < 0.001). The dosage of gonadotropins was notably more frequent adjusted in group B (46.9% vs 24.6%, p < 0.001). A higher risk of ovarian hyperstimulation syndrome was significantly more frequent in the non-maximal dose population compared to the maximal dose population (64.6% vs 27.5%, p < 0.01). These findings suggest that ovulation monitoring may not be necessary in the population stimulated to the maximum dose. This could result in 478 ultrasound and blood tests being avoided in the context of this study. Limitations, reasons for caution The data was obtained through a retrospective analysis. However, not monitoring before day 10 could pose a risk of delaying the cancellation of the IVF cycle, resulting in unnecessary treatment continuation. Wider implications of the findings This significant study indicates that, thanks to our algorithm, monitoring only on day 10 would be adequate for patients with low ovarian reserve who are stimulated to the maximum dose. Further validation of this strategy can be conducted through a randomized prospective study or with the use of different gonadotropins. Trial registration number non applicable
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".