O-128 A 37-year prospective study of polycystic ovary syndrome patients: impact of body mass index at enrolment on long-term morbidity and mortality
Bibliographic record
Abstract
Abstract Study question Does weight classification (lean, overweight, obese) in polycystic ovary syndrome (PCOS) patients affect long-term morbidity and mortality? Summary answer Young obese-PCOS exhibited higher risks for chronic conditions later in life, including diabetes, hypertension and cardiovascular diseases, compared to those lean or overweight at enrolment. What is known already PCOS is a common hormonal disorder affecting women of reproductive age, characterized by hyperandrogenism, menstrual irregularities, and polycystic ovarian morphology. PCOS patients are at an increased risk of metabolic and cardiovascular diseases, including insulin resistance, dyslipidemia, and hypertension, contributing to a higher likelihood of developing type 2 diabetes and cardiovascular morbidity. Obesity further exacerbates these risks, intensifying metabolic disturbances and increasing the prevalence of chronic health conditions. Additionally, lean women with PCOS still exhibit a higher prevalence of metabolic complications compared to non-PCOS counterparts, emphasizing the complex interplay between PCOS and weight status in determining long-term health outcomes. Study design, size, duration This 37-year prospective cohort study at McGill University Endocrinology Clinic enrolled 650 women aged ≥18 years with PCOS from 1987 to 2005, with follow-up until 2024. PCOS was diagnosed based on hyperandrogenism and menstrual irregularities, with exclusions for alternative diagnoses. Participants were categorized by BMI at enrolment: lean (18.5-24.9 kg/m², n = 255), overweight (25.0-29.9 kg/m², n = 167), and obese (≥30.0 kg/m², n = 228). The study aimed to assess long-term morbidity and mortality across these weight categories. Participants/materials, setting, methods Data collected at recruitment included age, BMI, hormonal profile, and metabolic markers. Follow-up monitored mortality and chronic conditions including 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. Primary outcomes were long-term morbidity and mortality. Statistical analyses included chi-square tests for categorical variables and ANOVA for continuous data. Main results and the role of chance At recruitment, lean patients were younger (28.3±6.7 years) than overweight (30.3±7.1) and obese (30.9±7.5) patients (p < 0.001). BMI ranged from 21.4±2.4 kg/m² in lean patients, 27.2±1.3 in overweight patients, and 36.7±6.1 kg/m² in obese patients (p < 0.001). Obese patients had higher fasting insulin, fasting glucose, total cholesterol, and triglycerides (p < 0.001, all). Serum testosterone was significantly higher in obese patients (p < 0.001), while androstenedione, DHEAS, and DHEA, did not differ significantly between groups (p > 0.05). At follow-up, mean age was similar-(p = 0.179). Time in study was shorter for obese vs. lean-(p < 0.001). Obese patients had higher rates of insulin-dependent diabetes (7.0% vs. 1.2%, p < 0.001), non-insulin-dependent diabetes (35.1% vs. 11.4%, p < 0.001), dyslipidemia (30.3% vs. 18.8%, p = 0.024), hypertension (43.4% vs. 18.0%, p < 0.001), and sleep apnea (4.8% vs. 1.21%, p = 0.008). More obese patients required anticoagulation (6.1% vs. 0.4%, p < 0.001) and aspirin for cardiovascular disease (14.0% vs. 7.1%, p = 0.004). Obese individuals had higher asthma and COPD rates (21.5% vs. 9.0%, p = 0.001). No significant differences were seen in cancer, neurological, autoimmune, or psychiatric disorders. Mortality was higher in obese (5.7% vs. 2.7%, p = 0.272), but not statistically significant. Limitations, reasons for caution This observational, single-center study has a relatively small sample size, limiting statistical power and generalizability. Loss to follow-up (17%) may affect results. A longer follow-up period could impact morbidity and mortality findings. Wider implications of the findings This data confirms for the first time that being obese in youth affects long-term morbidity in women with PCOS. These findings suggest the importance of weight management in PCOS care. Further research should explore targeted therapies and lifestyle interventions to mitigate long-term health risks in this population. 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".