Arterial Stiffness in Hemodialysis: Which Parameter to Measure to Predict Cardiovascular Mortality?
Bibliographic record
Abstract
In previous studies, different parameters of arterial stiffness were related to cardiovascular mortality in hemodialysis patients, but their relative prognostic value has not previously been evaluated in 1 cohort. Carotid-femoral pulse wave velocity (PWV), the carotid augmentation index, carotid pulse pressure (CPP) and carotid-brachial pulse pressure amplification (AMP) were measured in 98 patients before and after hemodialysis. Patients were followed for a median of 29 months (1-34) and the association of these parameters with cardiovascular mortality were assessed using log-rank tests and Cox proportional hazards regressions. During follow-up, 25 patients died of cardiovascular causes. Increasing pre- and postdialysis PWV tertiles and decreasing predialysis AMP tertiles were significantly related to cardiovascular mortality (p = 0.012 and 0.011 for PWV, respectively; < 0.001 for AMP). Neither the carotid augmentation index nor carotid pulse pressure were related to cardiovascular mortality. The adjusted hazard ratios for 1 m/s higher pre- and postdialysis PWV were 1.24 (1.07-1.44) and 1.17 (1.06-1.28), respectively. The hazard ratio for 10% lower predialysis AMP was 1.41 (1.03-1.92). When included in the same model, both predialysis PWV and AMP remained significantly associated with cardiovascular mortality. Among different stiffness parameters, PWV is consistently related to cardiovascular mortality, irrespective of the timing of measurement. Predialysis AMP seems to provide additional prognostic information.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".