Vascular stiffness in incident peritoneal dialysis patients over time
Bibliographic record
Abstract
OBJECTIVE: Vascular stiffness is prevalent in end-stage renal disease patients and predicts adverse events. This study describes the prevalence of vascular stiffness and its associated factors in a cohort of incident peritoneal dialysis (PD) patients. METHODS: In a prospective observational study of 50 patients, carotid-femoral pulse wave velocity (PWV) were conducted at baseline, 3, 6 and 12 months after initiation of PD. Aortic calcification scores (ACS) were derived using plain lateral abdominal films. We examined the association of significant changes in PWV (defined as 1 m/s or 15% change from baseline) over 6 months in conjunction with demographic and clinical data. RESULTS: The mean age was 58 years, 67% were male, and 48% were Caucasian. One third was diabetic, and 23% had pre-existing cardiovascular disease. Median eGFR was 8.7 ml/ min. ACS was strongly correlated with PWV (r = 0.62, p < 0.0001). Over 6 months, 42% demonstrated significant increases, while 23% demonstrated decreases in their PWV. Factors shown to be associated with increasing PWV were Caucasian race (OR = 4.50; CI: 0.97 - 20.83), higher phosphate (OR = 8.36; CI: 1.10 - 63.51) and a lower baseline PWV (OR = 0.67; CI: 0.45 - 0.99). Decrease in PWV was associated with the absence of calcium based phosphate binder usage (OR = 0.11; CI: 0.02 - 0.73). Changes in weight and PWV at 12 months were significantly correlated (p = 0.007, r = 0.57). CONCLUSION: In this group of incident PD patients, we demonstrate a lower prevalence of vascular calcification than in hemodialysis patients, a correlation of calcification with PWV, and an important finding that PWV can change in either direction over a short period of time, which are associated with modifiable risk factors.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".