Range and Consistency of Cardiovascular Outcomes Reported by Clinical Trials in Kidney Transplant Recipients: A Systematic Review
Bibliographic record
Abstract
Cardiovascular disease is a major cause of morbidity and mortality in kidney transplant recipients. Trial evidence to improve cardiovascular outcomes is limited by inconsistent reporting of outcomes, which may also lack patient-relevance. This study aimed to assess the range and consistency of cardiovascular outcomes reported by contemporary trials in kidney transplant recipients. Methods: A systematic review of all randomized controlled trials involving adult kidney transplant recipients that reported at least 1 cardiovascular outcome from January 2012 to December 2019 was performed, including Embase, MEDLINE, Cochrane, and ClinicalTrials.gov electronic databases. Trial characteristics were extracted and all levels of specification of the cardiovascular outcome measures reported were analyzed (the measure definition, metric' and method of aggregation). Measures assessing a similar aspect of cardiovascular disease were categorized into outcomes. Results: From 93 eligible trials involving 27 609 participants, 490 outcome measures were identified. The outcome measures were grouped into 38 outcomes. A cardiovascular composite was the most common outcome reported (40 trials, 43%) followed by cardiovascular mortality (42%) and acute coronary syndrome (31%). Cardiovascular composite was also the most heterogeneous outcome with 77 measures reported followed by cardiovascular mortality (n = 58) and inflammatory biomarkers (n = 51). The most common cardiovascular composite outcome components reported were major cardiovascular events (18 trials), stroke unspecified (11 trials), and myocardial infarction unspecified (10 trials). Conclusions: There is substantial heterogeneity in cardiovascular outcome reporting in kidney transplant trials.
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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 | 0.119 | 0.402 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.014 |
| Bibliometrics | 0.020 | 0.019 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".