Health Care-Related Economic Burden of Polycystic Ovary Syndrome in the United States: Pregnancy-Related and Long-Term Health Consequences
Bibliographic record
Abstract
CONTEXT: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder of reproductive-aged women, affecting approximately 5% to 20% of women of reproductive age. The economic burden of PCOS was previously estimated at approximately $3.7 billion annually in 2020 USD when considering only the costs of the initial diagnosis and of reproductive endocrine morbidities, without considering the costs of pregnancy-related and long-term morbidities. OBJECTIVE: This study aimed to estimate the excess prevalence and economic burden of pregnancy-related and long-term health morbidities attributable to PCOS. METHODS: PubMed, EmBase, and Cochrane Library were searched, and studies were selected in which the diagnosis of PCOS was consistent with the Rotterdam, National Institutes of Health, or Androgen Excess and PCOS Society criteria, or that used electronic medical record diagnosis codes, or diagnosis based on histopathologic sampling. Studies that included an outcome of interest and a control group of non-PCOS patients who were matched or controlled for body mass index were included. Two investigators working independently extracted data on study characteristics and outcomes. Data were pooled using random effects meta-analysis. The I2 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 of PCOS due to pregnancy-related and long-term morbidities in the United States is estimated to be $4.3 billion annually in 2020 USD. CONCLUSION: Together with our prior analysis, the economic burden of PCOS is estimated at $8 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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".