Clinical prediction score of nonalcoholic fatty liver disease in adolescent girls with polycystic ovary syndrome (PCOS‐HS index)
Bibliographic record
Abstract
OBJECTIVE: Nonalcoholic fatty liver disease (NAFLD) is common in obese adolescents with polycystic ovary syndrome (PCOS), but there are no inexpensive ways to accurately identify NAFLD in PCOS. The objective was to develop a simple clinical score to screen for NAFLD risk in obese adolescents with PCOS. DESIGN: This is a secondary analysis of 3 cross-sectional studies on metabolic characterization of obese adolescents with PCOS. 108 overweight and obese adolescents with PCOS (BMI > 90th percentile, age 12-19 years) were enrolled from 2012 to 2018. METHODS: Magnetic resonance imaging was used to quantify hepatic fat fraction (HFF). A development cohort of 87 girls were divided by presence of NAFLD (HFF > 5.5%). A logistic regression model with the outcome of NAFLD and candidate predictor variables was fit. A simplified model (PCOS-HS index) was created using backwards stepdown elimination. Validation was performed using 200 bootstrapped sample and in a second cohort of 21 PCOS participants. RESULTS: 52% of the development cohort had NAFLD. The PCOS-HS index that included BMI percentile, waist circumference, ALT and SHBG had an AUCROC of 0.81, sensitivity 82%, specificity 69%, negative predictive value (NPV) 78% and positive predictive value 74%, using a threshold of 0.44 to predict HS. A threshold of 0.15 ruled out NAFLD with a NPV 90%. In the validation cohort, the model showed an accuracy of 81%, sensitivity of 91% and specificity of 70%. CONCLUSIONS: We developed a clinical index to identify NAFLD in girls with PCOS who would need further evaluation and treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".