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Differences in ventricular wall composition may explain inter-patient variability in the ECG response to variations
Hassaan A Bukhari1,2,3,4, Carlos Sánchez1,2, Pablo Laguna1,2
1BSICoS Group, I3A Institute, University of Zaragoza, IIS Aragón, Zaragoza, Spain.
Insights
Inter-individual differences in heart cell distribution explain ECG variability in chronic kidney disease patients. This finding can improve serum electrolyte monitoring for preventing arrhythmias.
Area of Science:
- Cardiovascular Physiology
- Computational Biology
- Medical Diagnostics
Background:
- Chronic kidney disease (CKD) impairs electrolyte balance, increasing arrhythmia risk.
- Non-invasive monitoring of serum potassium [K+] and calcium [Ca2+] is crucial for CKD patients.
- Existing electrocardiogram (ECG) markers for electrolyte levels show high inter-patient variability.
Purpose of the Study:
- To investigate if variations in ventricular wall cell type distribution explain ECG marker variability in CKD patients.
- To correlate ECG changes with serum [K+] and [Ca2+] levels in a computational model and in patients.
- To assess the potential for improved non-invasive electrolyte monitoring in CKD.
Main Methods:
- Human heart-torso models with varying proportions of endocardial, midmyocardial, and epicardial cells were created.
- A reaction-diffusion model simulated ventricular electrical activity with modified Ten Tusscher-Panfilov dynamics.
- Simulated ECGs and data from 29 end-stage renal disease (ESRD) patients undergoing hemodialysis (HD) were analyzed.
Main Results:
- ECG markers strongly correlated with [K+] (r=0.68-0.98) and [Ca2+] (r=0.70-0.98) in both simulations and patients.
- Simulated ECG variability, influenced by cell type distribution, matched patient variability, especially at high [K+] and low [Ca2+].
- Variations in epicardial cell proportion significantly impacted ECG marker variability.
Conclusions:
- ECG marker changes reflect [K+] and [Ca2+] variations similarly in models and ESRD patients.
- Ventricular wall cell type distribution, particularly epicardial cells, explains inter-patient ECG variability.
- This understanding can enhance non-invasive electrolyte monitoring for CKD patients.
Abstract:
Objective: Chronic kidney disease patients have a decreased ability to maintain normal electrolyte concentrations in their blood, which increases the risk for ventricular arrhythmias and sudden cardiac death. Non-invasive monitoring of serum potassium and calcium concentration, [K+] and [Ca2+], can help to prevent arrhythmias in these patients. Electrocardiogram (ECG) markers that significantly correlate with [K+] and [Ca2+] have been proposed, but these relations are highly variable between patients. We hypothesized that inter-individual differences in cell type distribution across the ventricular wall can help to explain this variability. Methods: A population of human heart-torso models were built with different proportions of endocardial, midmyocardial and epicardial cells. Propagation of ventricular electrical activity was described by a reaction-diffusion model, with modified Ten Tusscher-Panfilov dynamics. [K+] and [Ca2+] were varied individually and in combination. Twelve-lead ECGs were simulated and the width, amplitude and morphological variability of T waves and QRS complexes were quantified. Results were compared to measurements from 29 end-stage renal disease (ESRD) patients undergoing hemodialysis (HD). Results: Both simulations and patients data showed that most of the analyzed T wave and QRS complex markers correlated strongly with [K+] (absolute median Pearson correlation coefficients, r, ranging from 0.68 to 0.98) and [Ca2+] (ranging from 0.70 to 0.98). The same sign and similar magnitude of median r was observed in the simulations and the patients. Different cell type distributions in the ventricular wall led to variability in ECG markers that was accentuated at high [K+] and low [Ca2+], in agreement with the larger variability between patients measured at the onset of HD. The simulated ECG variability explained part of the measured inter-patient variability. Conclusion: Changes in ECG markers were similarly related to [K+] and [Ca2+] variations in our models and in the ESRD patients. The high inter-patient ECG variability may be explained by variations in cell type distribution across the ventricular wall, with high sensitivity to variations in the proportion of epicardial cells. Significance: Differences in ventricular wall composition help to explain inter-patient variability in ECG response to [K+] and [Ca2+]. This finding can be used to improve serum electrolyte monitoring in ESRD patients.
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