Interaction of Serum Phosphate with Age as Predictors of Cardiovascular Risk Scores in Stable Renal Transplant Recipients
Bibliographic record
Abstract
Abstract We calculated rate of changes in the cardiovascular risk calculator for renal transplant recipients (CRCRTR) major adverse cardiac events (MACE) in clinically stable renal transplant recipients (RTRs) to identify covariables that associate with fast cardiovascular (CV) risk progression. CRCRTR-MACE scores were calculated on 139 patients in 2011 and 2014. Score changes above and below median changes in scores were labeled fast or slow CV risk progression. Multivariate analysis (MVA) was performed to identify variables significant to percentage changes in scores. Receiver-operating characteristic (ROC) analysis was performed to define sensitivity and specificity of factors significant to fast score progression. Follow-up was 2.61 (2.02–4.47) years. Slow and fast progressions were present in 50.4 and 49.6% of patients, with a median change of 25.8% (− 92.1 to 1,444.7%). MVA showed percentage changes in age and serum phosphate were the only significant variables impacting fast progression in scores. ROC showed 2011 serum phosphate of 1.15 mmol/L to predict fast progression (area under the curve [AUC] of 0.628, p > 0.0126). Age older than 45 years combined with 2011 serum phosphate above 1.15 mmol/L had a significant AUC of 0.781, p < 0.0010 interleukin (IL)-1A and IL-28A were significant associates with serum phosphate above 1.1 mmol/L in the MVA. Changes in CV risk in RTR over time are highly variable. Serum phosphate, even within upper normal levels, predicts worsening of CV risk scores in stable RTR.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".