Determinants of Arterial Stiffness in Female Patients with Takayasu Arteritis
Bibliographic record
Abstract
OBJECTIVE: The assessment of pulse wave velocity (PWV) in Takayasu arteritis (TA) is complex because of many confounding factors. We evaluated PWV in female patients with TA and controls with comparable anthropometric and clinical variables and assessed a possible association of TA with disease variables. METHODS: We evaluated 27 patients with TA consecutively. Exclusion criteria were menopause, smoking, diabetes, renal insufficiency, poorly controlled hypertension, cardiac arrhythmias, obesity, inflammatory comorbidities, pregnancy, and surgical procedures involving the aorta. Disease activity was determined by clinical and laboratory variables. As healthy controls, 27 subjects with comparable age, blood pressure, height, and weight were selected. Carotid-femoral PWV measurements were obtained using the Complior system. RESULTS: The mean PWV in patients with TA was higher than in healthy controls (9.77 ± 3.49 vs 7.83 ± 1.06 m/s; p = 0.009). Despite our strict selection criteria, patients with TA had an average systolic blood pressure (SBP) 8 mmHg higher than controls (p = NS), and significantly higher pulse pressure values. The multivariate linear regression model shows that 93.8% of the PWV variability is explained by the variables age, mean BP, and the disease itself (adjusted R(2) = 0.938). Stepwise logistic analysis using the PWV cutoff value established by the receiver-operator characteristic curve (> 8.34 m/s) as dependent variable, and measures with significance in univariate analysis as independent variables revealed that TA (OR 4.69; 95% CI 1.31-16.72; p = 0.017) and mean BP (OR 1.06; 95% CI 1.00-1.12; p = 0.048) were independently associated with higher PWV. Further analysis of disease variables revealed that PWV values were not correlated with erythrocyte sedimentation rate, C-reactive protein, cumulative dose of glucocorticoid, or ejection fraction (p > 0.05). CONCLUSION: In our cohort of female patients with TA, the disease itself and mean BP were the strongest determinants associated with arterial stiffness.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".