Increased Prevalence of Adverse Health Outcomes Across the Lifespan in Those Affected by Polycystic Ovary Syndrome: A Canadian Population Cohort
Bibliographic record
Abstract
BACKGROUNDPolycystic Ovary Syndrome (PCOS) is the most common metabolic-endocrine disorder impacting the health and quality of life of women over the lifespan. It is important we have evidence-based data on the scope of adverse health outcomes in those affected by PCOS in order to improve health care and quality of life in this population. The aim of this study was to determine the prevalence of adverse health outcomes in those with PCOS compared to age-matched controls.METHODSWe conducted a retrospective observational case-control study in those diagnosed with PCOS and age-matched controls using the Alberta Health Services Health Analytics database and International Classification of Disease from 2002-2018 in Alberta, Canada.RESULTSThe cohort consisted of n=16531 exposed PCOS cases and n= 49335 age-matched un-exposed controls. Hypertension, renal disease, gastrointestinal disease, eating disorders, mental illness, depression-anxiety, rheumatoid arthritis, respiratory infections and all malignancies were 20-40% (p<0.0001) higher in those with PCOS compared to controls. The prevalence of obesity, dyslipidemia, non-alcoholic fatty liver disease and Type 2 diabetes was 2-3 fold higher in PCOS (p<0.001). Cardiovascular, cerebrovascular and peripheral vascular disease were 30-50% higher and occurred 3-4 yrs earlier in those with PCOS(p<0.0001), and there was a 2-fold higher prevalence of dementia in those with PCOS compared to controls.CONCLUSIONThese findings show PCOS is associated with a higher prevalence of morbidities over the lifespan, and provides evidence of the potential scope of health care burden in women affected by PCOS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".