Cardiovascular risk factors and kidney transplantation: a retrospective analysis
Bibliographic record
Abstract
Abstract Introduction Cardiovascular disease (CVD) poses a significant risk to end-stage kidney disease (ESKD) patients and remains the leading cause of morbidity and mortality among kidney transplant (KT) recipients. With a global rise in ESKD patients dependent on dialysis, transplant programs face growing pressure to consider candidates with a greater burden of CVD for KT despite potential long-term risks. Enhancing pre-KT cardiac risk assessment is crucial to prevent cardiovascular complications post-transplant and meet the demand for KT globally. Purpose High-quality studies evaluating pre-KT cardiovascular risk factors in patients with ESKD are lacking. Our study aims to evaluate the association between pre-KT cardiovascular risk factors and the development of major adverse cardiac events (MACE) post-KT. Methods This retrospective cohort study of ESKD patients at a tertiary center consisted of consecutive patients referred for cardiovascular assessment prior to KT between January 2013 and January 2023. Clinical and demographic data prior to KT and outcomes 1-year post-KT were extracted. Patients who underwent multi-organ transplantation were excluded. The primary endpoint was MACE, defined as all-cause death, myocardial infarction (MI), ischemic stroke, coronary revascularization, heart failure requiring hospitalization, and cardiac resuscitation. Results A total of n=233 patients were referred for cardiac evaluation prior to KT. Of these, n=145 (62%) patients had a KT, n=69 (30%) patients died pre-KT, and n=19 (8%) patients were removed from the transplant program. Of the n=143 KT recipients that met our inclusion criteria, 122 (85%) were free of MACE, while 21 (15%) met the primary endpoint in the year following KT. Patients with MACE were significantly older (mean age = 65 vs. mean age = 59, p < 0.001), and more likely to have coronary artery disease (85.7% vs. 50.8%, p = 0.01), cardiomyopathy (42.9% vs. 17.2%, p = 0.04), smoking history (71.4% vs. 46.7%, p = 0.04), and diabetes (85.7% vs. 49.2%, p = 0.02). Furthermore, deceased donor KT was associated with a greater likelihood of MACE (85.0% vs. 57.5%, p = 0.02) compared to living donor recipients. There were no significant differences with respect to left ventricular ejection fraction, diagnosis of heart failure, or prior MI between MACE and non-MACE groups (p > 0.17 for all). Conclusion Among pre-KT patients with CVD, there is a high mortality rate (30%) prior to KT. Following a successful KT, 15% of patients experienced MACE within 1-year. Our findings underscore the urgency of developing strategies to facilitate timely kidney transplantation, particularly in light of the anticipated rise in demand for kidney transplants. The elevated incidence of major adverse events in the year following a successful KT emphasizes the necessity of collaborative care by cardiologists and nephrologists for these patients, and the need for further studies to improve long-term outcomes.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".