A Personalized Approach to Chronic Kidney Disease and Cardiovascular Disease: JACC Review Topic of the Week

Ashton C Lai1, Solomon W Bienstock1, Raman Sharma1

  • 1Icahn School of Medicine at Mount Sinai Hospital, New York, New York, USA.

Insights

Patients with end-stage renal disease (ESRD) face high cardiovascular death risk due to dialysis-induced shifts. Multimodality imaging offers new ways to predict and manage these cardiac risks in chronic kidney disease (CKD).

Area of Science:

  • Nephrology
  • Cardiology
  • Medical Imaging

Background:

  • Cardiovascular disease (CVD) is the leading cause of mortality in end-stage renal disease (ESRD) patients.
  • Dialysis initiation in ESRD exacerbates hemodynamic and electrolyte imbalances, contributing to cardiac complications.
  • Existing risk models inadequately predict cardiovascular mortality in chronic kidney disease (CKD).

Purpose of the Study:

  • To review the cardiovascular risks associated with hemodialysis.
  • To explore the pathophysiology of cardiovascular complications in CKD patients undergoing dialysis.
  • To examine the role of multimodality imaging in prognostication and risk stratification for these patients.

Main Methods:

  • Comprehensive literature review of cardiovascular risks in ESRD and dialysis.
  • Discussion of pathophysiological mechanisms linking kidney disease, dialysis, and cardiac events.
  • Exploration of multimodality imaging techniques for risk assessment.

Main Results:

  • Hemodialysis initiation causes significant fluid and electrolyte shifts, leading to subendocardial ischemia, left ventricular hypertrophy, and diastolic dysfunction.
  • These perturbations increase the incidence of acute coronary syndrome and sudden cardiac death in CKD patients.
  • Multimodality imaging presents a promising avenue for improved risk stratification and personalized patient management.

Conclusions:

  • Cardiovascular complications are a major concern for ESRD patients on dialysis, driven by unique pathophysiological processes.
  • Novel applications of multimodality imaging are crucial for enhancing prognostication and guiding personalized treatment strategies.
  • Further research integrating imaging into risk prediction models is warranted for better patient outcomes.

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