P-658 A 37-year prospective study of polycystic ovary syndrome (PCOS) patients: impact of free testosterone levels in youth on long-term morbidity and mortality
Bibliographic record
Abstract
Abstract Study question Does free testosterone level at young age, influence long-term morbidity and mortality in PCOS patients? Summary answer PCOS patients with higher youth free testosterone show increased psychiatric disorders and hypothyroidism, less autoimmune diseases, and no significant differences in mortality, or cardiovascular disease. What is known already PCOS is a complex endocrine disorder characterized by hyperandrogenism, ovulatory dysfunction, and metabolic disturbances, affecting long-term health. Elevated androgens, particularly free testosterone, are associated with increased insulin resistance, adverse lipid profiles, and heightened cardiovascular risk. While prior research links hyperandrogenism to metabolic complications and cardiovascular risk factors, its influence on chronic morbidity and mortality remains unclear. Some studies suggest elevated testosterone contributes to a pro-inflammatory state, while others highlight potential protective effects on muscle mass and bone density. The long-term effects of varying androgen levels on different organ systems, disease progression, and mortality in PCOS patients has not been established. Study design, size, duration A 37-year prospective cohort study conducted at McGill University Endocrinology Clinic included 513 women aged≥18 years diagnosed with PCOS between 1987-2005, with follow-up until 2024. PCOS was diagnosed based on hyperandrogenism and menstrual irregularities, excluding alternative diagnoses. Patients were divided into two groups: lower 50% (0.30-6.40pg/ml) and upper 50% (6.50-71.20pg/ml) of serum free testosterone (normal-range 0.10-6.40pg/ml) at recruitment. The study evaluated the association between free testosterone levels in early adulthood and long-term morbidity and mortality. Participants/materials, setting, methods Baseline data, including age, BMI, hormonal profile, and metabolic markers, were collected at recruitment. Follow-up assessed morbidity and mortality by tracking chronic diseases such as diabetes, cardiovascular disease, dyslipidemia, anticoagulation therapy needs, embolic events, ischemic heart disease, arrhythmias, sleep apnea, autoimmune disorders, thyroid dysfunction, neurological disorders, respiratory conditions, mental health conditions, cancers, gastrointestinal diseases, osteoporosis, rheumatic, kidney, and liver conditions. Statistical analyses included chi-square tests for categorical variables and t-tests for continuous data. Main results and the role of chance At recruitment, the upper 50% testosterone group was significantly younger (28.45±6.00 vs. 32.46±8.26 years, p < 0.001) and had higher basal serum FSH, LH, androstenedione, testosterone, DHEAS, and DHEA (all p < 0.001). They also had higher fasting insulin (12.74±8.48 vs. 11.02±6.55 mIU/L, p = 0.010), total cholesterol (4.48±1.50 vs. 4.02±1.76 mmol/L, p = 0.002), and triglycerides (1.14±0.74 vs. 0.97±0.70 mmol/L, p = 0.011). No significant differences were observed in BMI or fasting glucose. At final evaluation, mean age was 59.8±10.7 years in the lower testosterone group and 61.6±55.9 years in the high testosterone group (p = 0.602). Study duration was 27.3±7.7 years and 33.2±5.9 years, respectively (p = 0.097). Mortality rates did not differ significantly (5.03% vs. 3.13%, p = 0.277). No significant differences were found in diabetes, dyslipidemia, cardiovascular disease, hypertension, respiratory conditions, or malignancies. However, psychiatric disorders (22.09% vs. 30.20%, p = 0.037), specifically depression (14.73% vs. 23.14%, p = 0.015), were more prevalent in the lower testosterone group. Hypothyroidism was also more common in this group (25.49% vs. 17.44%, p = 0.026), while autoimmune diseases were more prevalent in the high testosterone group (0% vs. 2.35%, p = 0.015). Limitations, reasons for caution This single-center observational study has a relatively small sample size, limiting statistical power and generalizability. Loss to follow-up (17%) may introduce bias. A longer follow-up period might detect more significant differences in morbidity and mortality. Wider implications of the findings While higher free testosterone was linked to distinct metabolic and hormonal profiles in early adulthood, it did not significantly impact long-term morbidity or mortality. These findings suggest androgen levels alone are not a primary determinant of long-term health risks in PCOS, emphasizing the importance of broader risk assessments and interventions. Trial registration number No
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".