Bibliographic record
Abstract
We read with interest the recent systematic review and meta-analysis by Israni et al., published in JASN, examining cardiovascular screening strategies in kidney transplant candidates.1 The authors report that few patients undergoing pretransplant coronary artery screening have class 1 indications for revascularization, such as left mainstem stenosis or triple-vessel disease with severe left ventricular dysfunction. While these findings suggest low diagnostic yield of current screening practices, several aspects merit further discussion. The authors reference the International Study of Comparative Health Effectiveness With Medical and Invasive Approaches–CKD (ISCHEMIA-CKD) trial to support re-evaluation of routine screening. ISCHEMIA-CKD remains the largest study of coronary angiography in patients with advanced CKD (eGFR ≤30 ml/min per 1.73 m2), enrolling 777 patients, including 415 receiving dialysis.2 In patients with myocardial ischemia on stress testing, ISCHEMIA-CKD demonstrated no difference in death or nonfatal myocardial infarction between invasive and conservative strategies. However, of 194 patients listed for transplantation, only 51 received a transplant during follow-up. Consequently, any post hoc subgroup analysis is severely underpowered. In addition, only 50% of patients in the invasive arm of ISCHEMIA-CKD underwent revascularization, compared with 20% in the conservative arm. Among those undergoing angiography, only 75% had obstructive coronary artery disease. These data are consistent with long-recognized limitations of myocardial stress testing in advanced CKD and further support the need for better tools to triage potential transplant candidates for invasive assessment. The current meta-analysis included only observational studies, spanning two decades and with methodological heterogeneity, complicating interpretation. In addition, without linking screening findings to peritransplant or post-transplant outcomes, the clinical value of the detected lesions remains uncertain. Furthermore, the authors focused on conventional risk factors such as hypertension, which universally affects these patients, but did not explore other relevant factors such as dialysis status or CKD duration. While their results are consistent with a small retrospective study (n=197) showing no difference in post-transplant cardiovascular outcomes between patients who did or did not undergo pretransplant angiography, only 19% (n=22) of those who had angiography received revascularization.3 Overall, there remain few data defining the optimal cardiovascular screening strategy in patients assessed for kidney transplantation. While the Canadian-Australasian Randomised trial of Screening Kidney transplant candidates for Coronary Artery Disease trial will examine the role of repeat screening in waitlisted patients, it will not address whether screening at point of assessment improves outcomes.4 Future randomized controlled trials of cardiovascular risk screening tools incorporating hard clinical end points are needed to answer this question. In the absence of such trials, transplant programs must recognize that current widespread screening practices may offer limited benefit while imposing substantial delays and procedural risks.
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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 | 0.013 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".