Cardiac Biomarkers Predict Major Adverse Cardiac Events (MACE) in Incident Haemodialysis Patients: Results from a Global Federated Database — Elin Davies (2025) | RDL Network
Cardiac Biomarkers Predict Major Adverse Cardiac Events (MACE) in Incident Haemodialysis Patients: Results from a Global Federated Database
Article 2025 en
Authors
ED
Elin Davies
BB
Benjamin J. R. Buckley
PA
Philip Austin
Abstract
1 min read
<b>Background:</b> Despite its many advantages, haemodialysis (HD) has been shown to be associated with significant cardiovascular events, especially in patients commencing HD. Currently, there is no specific method to risk-stratify incident HD patients. Blood-based biomarkers provide insight into myocardial injury and stress. We aimed to evaluate the association of increased circulating biomarker concentration in incident HD with incident major adverse cardiac events (MACE). <b>Methods:</b> This was a retrospective cohort study of incident haemodialysis cases within 3 months of treatment initiation (≥18 years) from the TriNetX database. Cohorts were grouped by biomarker thresholds: Troponin I: ≥50 ng/L, BNP ≥ 100 pg/mL and 1:1 propensity-score matched for demographic characteristics, baseline cardiovascular risk, laboratory values, and cardiovascular medication. Primary outcome: Incidence of major adverse cardiac events (MACE) censored prior to index event of HD. Secondary outcome: Risk of each individual component of the composite outcome. Cox regression reported hazard ratios (95% CI) for the outcomes. <b>Results:</b> In total, 62,206 and 10,476 patients were included in the troponin I and BNP cohorts, respectively. In the troponin I cohort, 5878 developed MACE (HR 1.33 (95% CI 1.26-1.41, <i>p</i> < 0.0001)). In the BNP cohort, 1050 developed MACE (HR 1.28 (95% CI 1.13-1.44, <i>p</i> < 0.0001)). <b>Conclusions:</b> In incident HD, routine clinical laboratory biomarkers can predict incident MACE. The results suggest the clinical need for CV mortality and morbidity risk profiling in incident HD using a combination of clinical and laboratory variables.
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