Use of Cardioprotective Medications in Kidney Transplant Recipients
Bibliographic record
Abstract
Death with function causes half of late kidney transplant failures, and cardiovascular disease (CVD) is the most common cause of death in these patients. We examined the use of potentially cardioprotective medications in a prospective observational study at seven transplant centers in the United States and Canada. Among 935 patients, 87% received antihypertensive medications at both 1 and 6 months after transplantation. Similar antihypertensive regimens were used for patients with and without diabetes and CVD, but with wide variability among centers. In contrast, while 44% of patients were on angiotensin converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARB) at the time of transplantation, the proportion taking these agents dropped to 12% at month 1, then increased to 24% at 6 months. Fewer than 30% with CVD or diabetes received ACEI/ARB therapy 6 months posttransplant. Aspirin use was uncommon (<40% of patients). Even among those with diabetes and/or CVD, fewer than 60% received aspirin and only half received a statin at 1 and 6 months. This study demonstrates marked variability in the use of cardioprotective medications in kidney transplant recipients, a finding that may reflect, among several possible explanations, clinical uncertainty due the lack of randomized trials for these medications in this population.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".