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Right bundle branch block as a cause of false-negative ECG classification of inferior myocardial infarction

I Gussak1, S H Zhou, P Rautaharju

  • 1Division of Cardiology, Saint Louis University Health Science Center, Missouri 63117, USA.

Insights

Right bundle branch block (RBBB) can alter electrocardiogram (ECG) Q wave duration, potentially leading to false-negative myocardial infarction (MI) diagnoses. This finding is crucial for accurate MI classification in clinical trials.

Area of Science:

  • Cardiology
  • Electrocardiography
  • Medical Diagnostics

Background:

  • Right bundle branch block (RBBB) is generally not considered to interfere with electrocardiogram (ECG) diagnosis of myocardial infarction (MI).
  • The assumption is that RBBB does not significantly alter initial excitation wavefronts detected by ECG.
  • Myocardial revascularization procedures carry a risk of developing RBBB post-operatively.

Purpose of the Study:

  • To investigate the effect of newly developed RBBB on serial ECG Q wave duration in patients post-myocardial revascularization.
  • To determine if RBBB influences the ECG diagnosis of inferior myocardial infarction (MI).

Main Methods:

  • Compared serial ECG Q wave duration changes in inferior leads (II, III, aVF).
  • Studied 9 patients who developed RBBB post-revascularization (RBBB group) versus 41 controls without RBBB.
  • Analyzed ECGs obtained before and after revascularization procedures.

Main Results:

  • Q wave durations were similar between groups pre-procedure.
  • Significant Q wave duration shortening observed in the RBBB group compared to the control group.
  • Most pronounced shortening in lead aVF (-18.2 ms vs -3.8 ms, P < .0001), indicating altered spatial orientation of excitation wavefronts.

Conclusions:

  • Incident RBBB following revascularization can significantly alter ECG findings.
  • This alteration poses a risk for false-negative ECG diagnosis of inferior MI.
  • Serial ECG analysis in clinical trials needs to account for RBBB-induced changes for accurate MI classification.

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