Impaired endothelial function in pediatric patients with turner syndrome and healthy controls: a case-control study
Bibliographic record
Abstract
BACKGROUND: Turner Syndrome women are at high risk of vascular disease and the assessment of early risk factors in Turner Syndrome girls is an emerging focus of research. Our objective was to evaluate endothelial function (EF), a preclinical measure of atherosclerosis, in Turner Syndrome girls compared with controls. METHODS: A cross-sectional case-control study of Turner Syndrome girls and healthy controls. Subjects underwent fasting insulin and glucose with calculation of HOMA-IR, fasting lipid profile, anthropometrics, and EF testing using peripheral arterial tonometry (PAT). Subjects, aged 10-18 years, had karyotype-confirmed Turner Syndrome; growth hormone (GH), thyroxine and estrogen use were not exclusion criteria. Controls were age- and BMI-matched healthy girls. Fifteen Turner Syndrome and 15 controls were recruited. RESULTS: Turner Syndrome girls had lower height, higher HDL and higher waist:height ratio than controls. PAT-hyperemia ratio (RH-PAT) scores were lower in Turner Syndrome (1.64 ± 0.34 vs. 2.08 ± 0.32, p = 0.002) indicating impaired EF. Among Turner Syndrome, RH-PAT did not vary with estrogen therapy or with karyotype 45,XO compared with other karyotypes. However, endothelial function was better in GH-treated compared with GH-untreated Turner Syndrome (1.80 ± 0.36 vs. 1.4 + 0.22, p = 0.02) although there were no differences in HOMA-IR, adiponectin or IGF-1. CONCLUSION: Girls with Turner Syndrome exhibit impaired endothelial function compared with controls, which may explain higher risk for vascular disease. GH may protect endothelial function in Turner Syndrome.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".