Predictors of cardiovascular events and death in paediatric renal transplant recipients
Bibliographic record
Abstract
Cardiovascular (CV) disease is the leading cause of death in pediatric renal transplant patients (pRTx). We examined the roles of hypertension, donor type, estimated glomerular filtration rate (eGFR), pre-transplant dialysis and post transplant diabetes (PTDM) on fatal and non-fatal CV events and all-cause mortality in pRTx. The study design is a population-based retrospective cohort study of 226 children with end-stage renal disease who received 1st renal transplants during 1980--2000 using record linkage between medical charts and administrative health databases. Primary outcomes were time to death and first fatal or non-fatal CV events. 71% of all CV events were non-fatal events. Pre-emptive transplantation was associated with decreased hazard of CV events (HR 0.30, 95% CI 0.09-0.99, p = 0.05). eGFR
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".