The relationship between ECG predictors of cardiac resynchronization therapy benefit
Josef Halamek1, Pavel Leinveber2, Ivo Viscor1
1Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic.
Insights
Cardiac resynchronization therapy (CRT) improves outcomes for left bundle branch block (LBBB) patients. New ECG analysis using ventricular electrical delay (VED) and QRS area may identify more patients who will benefit from CRT.
Area of Science:
- Cardiology
- Electrophysiology
- Medical Imaging
Background:
- Cardiac resynchronization therapy (CRT) is a key treatment for heart failure in patients with left bundle branch block (LBBB), reducing mortality and improving function.
- However, a significant portion of patients (around 30%) who meet current criteria for CRT do not experience substantial clinical benefit.
- This highlights the need for improved patient selection methods beyond traditional electrocardiogram (ECG) criteria.
Purpose of the Study:
- To concurrently analyze and compare three ECG-derived predictors of CRT benefit: strict left bundle branch block (SLBBB) classification, QRS area, and ventricular electrical delay (VED).
- To investigate the relationship and potential discordance between these predictors in a large patient cohort.
- To assess the potential of VED and QRS area in identifying non-SLBBB patients who may still benefit from CRT.
Main Methods:
- Utilized a subset of 602 records from the MADIT-CRT trial.
- Performed SLBBB classification by expert consensus.
- Computed QRS area and VED automatically, employing high-frequency QRS (HFQRS) maps to visualize conduction abnormalities.
Main Results:
- Found moderate correlations between SLBBB and VED (R=0.613) and QRS area (R=0.523).
- Analysis revealed that while most SLBBB patients (89%) are predicted to respond to CRT based on VED and QRS area, a notable proportion of non-SLBBB patients (34%) are also identified as potential responders.
- Scatter plot analysis highlighted discrepancies between the predictors, suggesting limitations of SLBBB alone.
Conclusions:
- The 'strict' left bundle branch block (SLBBB) classification may be too restrictive, potentially excluding patients who could benefit from CRT.
- QRS area and VED are clearly defined, automatically computable parameters that show promise for optimizing patient selection and biventricular stimulation.
- Detailed analysis of conduction abnormalities using HFQRS maps is recommended for comprehensive CRT optimization and improved patient outcomes.
Introduction:
Cardiac resynchronization therapy (CRT) is an effective treatment that reduces mortality and improves cardiac function in patients with left bundle branch block (LBBB). However, about 30% of patients passing the current criteria do not benefit or benefit only a little from CRT. Three predictors of benefit based on different ECG properties were compared: 1) "strict" left bundle branch block classification (SLBBB); 2) QRS area; 3) ventricular electrical delay (VED) which defines the septal-lateral conduction delay. These predictors have never been analyzed concurrently. We analyzed the relationship between them on a subset of 602 records from the MADIT-CRT trial.
Methods & Results:
SLBBB classification was performed by two experts; QRS area and VED were computed fully automatically. High-frequency QRS (HFQRS) maps were used to inspect conduction abnormalities. The correlation between SLBBB and other predictors was R = 0.613, 0.523 and 0.390 for VED, QRS area in Z lead, and QRS duration, respectively. Scatter plots were used to pick up disagreement between the predictors. The majority of SLBBB subjects- 295 of 330 (89%)-are supposed to respond positively to CRT according to the VED and QRS area, though 93 of 272 (34%) non-SLBBB should also benefit from CRT according to the VED and QRS area.
Conclusion:
SLBBB classification is limited by the proper setting of cut-off values. In addition, it is too "strict" and excludes patients that may benefit from CRT therapy. QRS area and VED are clearly defined parameters. They may be used to optimize biventricular stimulation. Detailed analysis of conduction irregularities with CRT optimization should be based on HFQRS maps.
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