FP313DETERMINANTS OF CHANGE IN ARTERIAL STIFFNESS OVER 5 YEARS IN EARLY CKD
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Arterial stiffness (AS) is an established risk factor for cardiovascular disease (CVD) associated with CKD but there have been few studies to evaluate progression of AS over time or factors that contribute to this, particularly in early CKD. We therefore investigated AS in an elderly population with CKD stage 3 over 5 years. METHODS: 1741 persons with estimated GFR 59-30mL/min/1.73m2 were recruited into the Renal Risk in Derby (RRID) study and assessed at baseline, year 1 and 5. Carotid to femoral pulse wave velocity (PWV) was measured as a marker of AS, using a Vicorder™ device (Skidmore Medical Ltd, Bristol, UK). 970 participants had PWV assessments at baseline and 5 years and are included in this analysis. RESULTS: Changes in important variables over time are shown in Table 1. PWV increased significantly by 1.1m/sec over 5 years. Univariate analysis revealed significant correlations between ΔPWV at year 5 and previously identified risk factors for CVD. Multivariable linear regression analysis identified independent determinants of ΔPWV (Table 2; R2=0.37 for equation). CONCLUSIONS: We observed a clinically significant increase in PWV over 5 years in a cohort of elderly persons with early CKD. Systolic BP was identified as the most important modifiable determinant of change in PWV suggesting that interventions to prevent arterial disease should focus on control of blood pressure in this population. Table 1. Characteristics of study cohort at 5 year follow-up n=970 *p<0.05 versus baseline value Table 2. Independent determinants of increase in PWV over 5 years
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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 | 0.000 | 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) | 0.001 | 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".