Framingham Risk Score and Novel Cardiovascular Risk Factors Underpredict Major Adverse Cardiac Events in Kidney Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Framingham Risk Score (FRS) is an insufficient cardiovascular event predictor in unselected kidney transplant recipients. Its role in different risk subgroups and the value of adding novel risk factor candidates to FRS is unknown. METHODS: We reviewed patients who underwent transplantation from 1998 to 2008 with minimum 3 months graft function, determining FRS-ascertained 10-year risk at 3 months along with relevant clinical and laboratory information. Major adverse cardiac events (MACE) (myocardial infarction, coronary artery revascularization, or cardiac death) 3 months posttransplant were captured. Time-to-MACE multivariate Cox modeling with FRS and novel risk factors (C-reactive protein, uric acid, urine albumin-to-creatinine ratio) as independent variables was performed. RESULTS: Of 956 patients, 89 experienced MACE (2.17 events/100 patient-years). FRS-predicted 10-year risk was 14.7% ± 10.0% in males with and 9.2% ± 8.2% in those without subsequent MACE (P < 0.0001), although FRS substantially underestimated MACE (actual-to-predicted event ratio 1.2-8.4 in different subgroups, all P < 0.0001). Although patients with MACE had a higher C-reactive protein (5.4 ± 6.0 vs. 3.8 ± 2.5 mg/L, P = 0.026) and uric acid (417 ± 109 vs. 386 ± 101 μmol/L, P = 0.012) level as well as lower 3-month estimated glomerular filtration rate (50.1 ± 20.1 vs. 54.8 ± 18.3 mL/min/1.73 m(2), P = 0.022), only FRS more than or equal to 10% (hazard ratio 2.313, 95% confidence interval 1.49-3.58, P = 0.0002) and estimated glomerular filtration rate less than 50 mL/min/1.73 m(2) (hazard ratio 2.291, 95% confidence interval 1.06-4.94, P = 0.034) predicted MACE in multivariate analysis. Adding novel risk factors to FRS did not improve FRS prediction. CONCLUSION: FRS substantially underpredicts MACE in kidney transplant recipients among all risk subgroups. Commonly available novel risk factors do not improve FRS predictive value.
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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) | 0.001 | 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".