Clinical outcomes in end stage renal disease on dialysis and severe coronary artery disease: A real-world study.
Int J Cardiol 2023;
378:105-110. [PMID:
36796490 DOI:
10.1016/j.ijcard.2023.02.029]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 10/23/2022] [Accepted: 02/12/2023] [Indexed: 02/17/2023]
Abstract
BACKGROUND
The optimal management of patients with end-stage renal disease (ESRD) on dialysis with severe coronary artery disease (CAD) has not been determined.
METHODS
Between 2013 and 2017, all patients with ESRD on dialysis who had left main (LM) disease, triple vessel disease (TVD) and/or severe CAD for consideration of coronary artery bypass graft (CABG) were included. Patients were divided into 3 groups based on final treatment modality: CABG, percutaneous coronary intervention (PCI), optimal medical therapy (OMT). Outcome measures include in-hospital, 180-day, 1-year and overall mortality and major adverse cardiac events (MACE).
RESULTS
In total, 418 patients were included (CABG 11.0%, PCI 65.6%, OMT 23.4%). Overall, 1-year mortality and MACE rates were 27.5% and 55.0% respectively. Patients who underwent CABG were significantly younger, more likely to have LM disease and have no prior heart failure. In this non-randomized setting, treatment modality did not impact on 1-year mortality, although the CABG group had significantly lower 1-year MACE rates (CABG 32.6%, PCI 57.3%, OMT 59.2%; CABG vs. OMT p < 0.01, CABG vs. PCI p < 0.001). Independent predictors of overall mortality include STEMI presentation (HR 2.31, 95% CI 1.38-3.86), prior heart failure (HR 1.84, 95% CI 1.22-2.75), LM disease (HR 1.71, 95% CI 1.26-2.31), NSTE-ACS presentation (HR 1.40, 95% CI 1.03-1.91) and increased age (HR 1.02, 95% CI 1.01-1.04).
CONCLUSION
Treatment decisions for patients with severe CAD with ESRD on dialysis are complex. Understanding independent predictors of mortality and MACE in specific treatment subgroups may provide valuable insights into the selection of optimal treatment options.
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