Atheroma Progression in Chronic Kidney Disease
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Cardiovascular events are 10 to 100 times more frequent in chronic kidney disease (CKD). We tested the hypothesis that the rate of atherosclerotic plaque growth is faster in severe versus moderate CKD. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We performed a prospective cohort study in 318 prevalent CKD patients with initial creatinine clearance (CCr) between 20 and 50 ml/min/1.73 m(2). Baseline clinical and laboratory data were obtained on all patients. Plaque area was determined every 6 mo using bilateral carotid ultrasonography. Plaque area distribution was normalized using a cube root transformation. Unadjusted and adjusted associations between CCr quintiles and rate of change in the transformed plaque area were assessed using multiple linear regression. RESULTS: The rate of plaque progression appeared lower in patients with the lowest CCr. Median rate of plaque growth was 0.4 mm(2)/yr in the lowest quintile of CCr (< 23 ml/min/1.73 m(2)) versus 5.0 mm(2)/yr in the highest quintile (> 43 ml/min/1.73 m(2)). This association remained significant after adjustment for potential confounders. A secondary analysis using quintiles of Modification of Diet in Renal Disease (MDRD) GFR confirmed the absence of increased plaque growth at low GFR, although a reduced rate of growth in the lowest quintile of MDRD GFR was not observed. CONCLUSION: We did not observe accelerated plaque growth at low levels of renal function. We suggest that mechanisms other than plaque growth are responsible for the observed excess of cardiovascular disease in CKD patients.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".