Association between Circulating Thrombopoietin Levels and Cardiovascular Risk Prediction Scores in Renal Transplant Recipients
Bibliographic record
Abstract
BACKGROUND/AIMS: The 7-year Major Adverse Cardiovascular Events Calculator (CRCRTR-MACE) predicts cardiovascular events (CVE) in renal transplant recipients (RTR), and thrombopoietin (TPO) is a humoral inflammatory factor implicated in cardiovascular disease (CVD). The aim of the study was to determine if circulating TPO levels in stable RTR are positively associated with variable(s) in the CRCRTR-MACE score. METHODS: CRCRTR-MACE scores were calculated in 95 stable RTR. TPO levels were measured by multiplexed fluorescent bead-based immunoassay in all patients and 48 controls. Multivariate analysis (MVA) was performed between TPO and CV risk variables and patient demographics. Stepwise regression with backward elimination of insignificant variables estimated the impact of risk variables on TPO levels. Significance was defined at p < 0.05. Normalized data were presented as mean ± SD and non-normalized data as median (maximum to minimum). RESULTS: The risk of a CVE within 7 years as predicted by the median was 9.97% (range 1.93-84.2). The percentage of patients who were above 20% risk for a CVE was 28.4%. Control TPO level of 170.41 (4.4-995.9) pg/ml was significantly lower than that of 237.90 (32.77-1,386.79) pg/ml in RTR (p = 0.010). TPO level correlated significantly with the total CRCRTR-MACE score (R = 0.310, p = 0.004), smoking (p = 0.009) and eGFR (R = -0.275, p = 0.012) but not with age, diabetes, LDL level or history of CVE. Only the total CRCRTR-MACE score (p = 0.013) and smoking (p = 0.009) remained significant in the MVA. Stepwise regression estimated that smoking increased TPO levels by 206.28 pg/ml and each 10% increase in CRCRTR-MACE score increased TPO levels by an additional 44.4 pg/ml. CONCLUSION: TPO levels are increased in RTR with high CRCRTR-MACE, particularly in smokers with diminished eGFR. Circulating TPO may serve as a biomarker and treatment target for CVD in 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 | 0.001 | 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".