Health care-related economic burden of polycystic ovary syndrome in the United States: Pregnancy-related and long-term health consequences - supplemental data
Bibliographic record
Abstract
Context: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder of reproductive-aged women, affecting approximately 5-20% of women of reproductive age. A previous estimate noted that the economic burden of PCOS approximates $3.7 billion annually in 2020 USD when considering only the costs of the initial diagnosis and of reproductive endocrine morbidities, not considering the costs of pregnancy-related and long-term morbidities. Objective: To estimate the excess prevalence and economic burden of pregnancy-related and long-term health morbidities attributable to PCOS. Data Sources: PubMed, EmBase and Cochrane Library. Study Selection: Studies in which the diagnosis of PCOS was consistent with the Rotterdam, National Institutes of Health (NIH), or Androgen Excess & PCOS (AE-PCOS) Society criteria, or that used electronic medical record diagnosis codes, or diagnosis based on histopathologic sampling were eligible for inclusion. Studies that included an outcome of interest and a control group of non-PCOS patients who were matched or controlled for body mass index (BMI) were included. Data Extraction: Two investigators working independently extracted data on study characteristics and outcomes. Data Synthesis: Data was pooled using random-effects meta-analysis. The I 2 statistic was used to assess inter-study heterogeneity. The quality of selected studies was assessed using the Newcastle-Ottawa Scale. Results: The additional total healthcare-related economic burden due to pregnancy-related and long-term morbidities associated with PCOS in the United States is estimated to be $4.3 billion annually in 2020 USD.
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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 | 0.007 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.016 | 0.020 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.052 | 0.002 |
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".