MON-178 Feasibility of Continuous Glucose Monitor Use and Glucose Pattern Analysis in Females With Polycystic Ovary Syndrome
Bibliographic record
Abstract
Abstract Disclosure: I. Safdar: None. R. Vettese: None. H. Hinz: None. H. Vanden Brink: None. E.A. Brennand: None. S.M. Dumanski: None. J.L. Benham: None. Background: Polycystic ovary syndrome (PCOS), characterized by hyperandrogenism, irregular menstrual cycles and polycystic ovarian morphology, affects >10% of females and has devastating impacts on metabolic, reproductive, and psychological health. Insulin resistance and dysglycemia are central metabolic disturbances involved in PCOS and contribute to an increased risk of early development of type 2 diabetes. Continuous glucose monitors (CGM) are readily available glucose sensors used in diabetes management. However, it is not known if CGM can be used in the management of people without diabetes at an increased risk for dysglycemia, including individuals living with PCOS. Objective:To evaluate the feasibility of using CGM and provide preliminary estimates of blood glucose (BG) patterns among individuals living with PCOS. Methods:We performed a pilot prospective cohort study of individuals with PCOS aged 18-45 years without a diagnosis of diabetes who did not use medication that could affect blood sugar or hormone levels. Participants underwent phenotyping to confirm PCOS diagnosis per Rotterdam criteria. Participants wore a FreeStyle Libre 2 CGM for 42 days, which recorded interstitial BG every 15 minutes. Feasibility outcomes were the recruitment rate, participant attrition, proportion of missing data from CGM, and participant satisfaction with CGM use. Secondary analysis examined glucose parameters: mean overall BG, overnight BG (23:00-07:00), daytime BG (07:01-22:59), and percent time in range (70-180 mg/dL), below range (<70 mg/dL), and above range (>180 mg/dL). BG parameters were stratified by biochemical hyperandrogenism status (elevated vs not) and compared using two-sided two-sample unequal-variance t-tests. Results:Out of 284 individuals screened, 35 met inclusion criteria and were enrolled, 30 completed the study, 4 (11.4%) withdrew, and 1 (2.9%) did not complete blood work. Reasons for withdrawal were declining to continue (n=2) and CGM adhesion difficulties (n=2). The mean recruitment rate was 5 participants/month. The median proportion of missing CGM data was 7.4% (IQR: 26.1%), with 4 participants (11%) having no missing data. Most participants (n=21, 60%) indicated they would use a CGM again if provided. As a result of their participation, two participants were diagnosed with type 2 diabetes. Mean daytime BG was higher in those with hyperandrogenism compared with those without (115.2 mg/dL vs 104.4 mg/dL, p=0.04). No significant differences between groups were observed for mean 42-day BG, overnight BG, and percent time in, above, or below range. Conclusion:We demonstrated the feasibility of CGM to assess dysglycemia among individuals living with PCOS. We observed a significant difference in daytime BG between those with hyperandrogenism and those without. Further research is needed to determine how CGM could be incorporated into PCOS management. Presentation: Monday, July 14, 2025
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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 | 0.001 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".