Tissue factor pathway inhibitor levels and atherothrombotic events in patients with chronic kidney disease or diabetes
Bibliographic record
Abstract
Increased tissue factor pathway inhibitor (TFPI) has been associated with cardiovascular disease (CVD). We aim to evaluate the predictive capability of TFPI for atherothrombotic events (ATE) in patients with chronic kidney disease (CKD) and diabetes. A prospective observational study was performed at Northern Health, Australia. Patients with CKD (estimated glomerular filtration ratio (eGFR) < 30 ml/min/1.73m2) and/or diabetes were recruited. Baseline total TFPI was measured and the median follow-up was 3.35 years. All patients with egfr < 30 ml/min/1.73m2 were analysed as CKD cohort while the diabetes cohort analysis excluded those with egfr < 30 ml/min/1.73m2. The primary outcome was ATE (myocardial infarction, stroke/transient ischaemic attack, critical limb ischaemia or sudden cardiac death). 220 patients were recruited, median age 63.5 years (IQR 51.0, 72.5) and 59.1% males (n = 130). No differences were seen in TFPI levels between the CKD (n = 77) and diabetes (n = 143) cohorts (35.4 vs. 36.4 ng/mL, p = 0.44). TFPI did not correlate with creatinine or HbA1c levels. 46 episodes of ATE were captured (6.69/100-person years (100PY)), with a higher rate in the CKD compared to the diabetes cohort (16.03/100PY vs. 2.53/100PY). In the CKD cohort, those who experienced ATE had higher TFPI with an optimal calculated cut-off (61.36ng/mL) associated with a subhazard ratio of 3.23 (95%CI 1.59–6.57). In the diabetes cohort however, TFPI was not significantly higher in those who experience ATE (40.1 vs. 34.4ng/mL, p = 0.35). We found elevated TFPI may predict prospective ATE, particularly in patients with CKD. While further validation studies are required, these findings highlight that coagulation changes may differ between high-risk CVD populations. • Elevated tissue factor pathway inhibitor (TFPI) is associated with cardiovascular disease (CVD) but there are limited studies looking at the predictive potential for prospective cardiovascular events. • TFPI appears to predict subsequent atherothrombotic events (ATE) in patients with CKD (eGFR < 30 ml/min/1.73m2). • TFPI was not statistically significant in its ability to predict ATE in the diabetes cohort although this may be limited by small study numbers. • External validation studies are still required however, these results highlight that CVD predictive biomarkers may differ between various high CVD risk populations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".