Carotid femoral pulse wave velocity in type 2 diabetes and hypertension
Bibliographic record
Abstract
OBJECTIVE: Optimal medication use obscures the impact of physical activity on traditional cardiometabolic risk factors. We evaluated the relationship between step counts and carotid-femoral pulse wave velocity (cfPWV), a summative risk indicator, in patients with type 2 diabetes and/or hypertension. RESEARCH DESIGN AND METHODS: Three hundred and sixty-nine participants were recruited (outpatient clinics; Montreal, Quebec; 2011-2015). Physical activity (pedometer/accelerometer), cfPWV (applanation tonometry), and risk factors (A1C, Homeostatic Model Assessment-Insulin Resistance, blood pressure, lipid profiles) were evaluated. Linear regression models were constructed to quantify the relationship of steps/day with cfPWV. RESULTS: The study population comprised 191 patients with type 2 diabetes and hypertension, 39 with type 2 diabetes, and 139 with hypertension (mean ± SD: age 59.6 ± 11.2 years; BMI 31.3 ± 4.8 kg/m; 54.2% women). Blood pressure (125/77 ± 15/9 mmHg), A1C (diabetes: 7.7 ± 1.3%; 61 mmol/mol), and low-density lipoprotein cholesterol (diabetes: 2.19 ± 0.8 mmol/l; without diabetes: 3.13 ± 1.1mmol/l) were close to target. Participants averaged 5125 ± 2722 steps/day. Mean cfPWV was 9.8 ± 2.2 m/s. Steps correlated with cfPWV, but not with other risk factors. A 1000 steps/day increment was associated with a 0.1 m/s cfPWV decrement across adjusted models and in subgroup analysis by diabetes status. In a model adjusted for age, sex, BMI, ethnicity, immigrant status, employment, education, diabetes, hypertension, medication classes, the mean cfPWV decrement was 0.11 m/s (95% confidence interval -0.2, -0.02). CONCLUSIONS: cfPWV is responsive to step counts in patients who are well controlled on cardioprotective medications. This ability to capture the 'added value' of physical activity supports the emerging role of cfPWV in arterial health monitoring.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".