Prevalence and Risk Factors of Elevated Liver Enzymes in Japanese Women With Polycystic Ovary Syndrome
Bibliographic record
Abstract
BACKGROUND: Polycystic ovary syndrome (PCOS) is a common endocrine disorder among reproductive-aged women. While PCOS is associated with an increased risk of obesity and insulin resistance, little is known regarding the prevalence of and risk factors for nonalcoholic fatty liver disease (NAFLD) among Japanese women with PCOS. We estimated the prevalence of and risk factors for elevated liver enzymes, as the index of NAFLD, in Japanese women with PCOS. METHODS: We retrospectively reviewed 102 reproductive-aged women who visited the Department of Gynecology, Kyoto Medical Center in Japan from January 2000 to September 2016. Inclusion criterion was confirmed diagnosis of PCOS using International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10) codes. Exclusion criteria were women with a history of liver diseases, missing body mass index (BMI) and serum alanine aminotransferase (ALT) data, and pregnancy. Data regarding age; BMI; and levels of blood glucose, serum lipid, liver enzymes, and sex hormones were obtained from medical records. Elevated liver enzymes was defined as ALT > 19 IU/L. Optimal cutoffs for risk factors for elevated liver enzymes were calculated to determine predictors of elevated liver enzymes using area under the curve (AUC) by receiver-operating characteristics (ROC). RESULTS: , P < 0.05). ROC analyses were performed using BMI and blood glucose and testosterone levels because BMI and blood glucose showed differences between the groups and testosterone is related to fatty liver. AUC of the model including BMI and blood glucose and testosterone levels was 0.861 (sensitivity, 66.7%; specificity, 100%). CONCLUSIONS: These findings suggest that elevated liver enzymes are common in women with PCOS. An algorism using BMI and blood glucose and testosterone levels might be useful to determine elevated liver enzymes in women with PCOS. Our finding may be useful for the study of NAFLD among Japanese women with PCOS since several previous studies have indicated elevated liver enzymes to be related to the potential presence of NAFLD. Further examination, including abdominal ultrasonography and/or liver biopsy data, is required to confirm these results.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".