At-home urine estrone-3-glucuronide quantification predicts oocyte retrieval outcomes comparably with serum estradiol
Bibliographic record
Abstract
Objective: To investigate the feasibility of monitoring urine estrone-3-glucuronide (E3G) with an at-home device during gonadotropin stimulation for in vitro fertilization and oocyte cryopreservation. Design: Prospective, observational cohort study. Setting: Private fertility clinic. Patients: Thirty patients undergoing stimulation with a gonadotropin-releasing hormone antagonist protocol for in vitro fertilization or oocyte cryopreservation. Interventions: Daily collection of the first urine in the morning during stimulation and analysis performed at home by each patient with the Mira Fertility Tracker. Main Outcome Measures: Primary outcomes were correlation of urine E3G and serum estradiol (E2) concentrations on the day of trigger to the number of total and metaphase 2 oocytes (MII). Secondary outcomes of interest were the correlation of matched E3G and E2 measurements and the daily trends of E3G and E2 during stimulation. Results: = 0.485 vs. 0.391, respectively). The Pearson correlation coefficient for matched E3G and E2 levels was 0.761. The correlation coefficients of determination for daily trends of E3G and E2 during stimulation were 0.7066 and 0.6102, respectively. Conclusions: Measured on the day of trigger, urine E3G monitoring during gonadotropin stimulation was comparable with serum E2 for predicting oocyte retrieval outcomes. Matched daily samples confirmed good correlation of urine E3G and serum E2. The option of at-home estrogen monitoring with devices such as Mira offers an alternative to traditional serum monitoring that may improve patient experience. Clinical Trial Registration Number: NCT05493202.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".