Study on the feasibility of distinguishing ventricular and pre-excited arrhythmia rhythms by a new algorithm

Background

The differentiation and diagnosis of ventricular tachycardia (VT) and pre-excited tachycardia (PXT) remains a challenging task, especially when typical AV dissociation is not present. The purpose of this article is to study the feasibility of a new theoretical algorithm for identifying ventricular arrhythmias (VA) and pre-excited arrhythmias (PA) rhythms (which can be used to distinguish VT from PXT, etc.).

Method

This study involved the deduction of a new algorithm by combining knowledge of cardiac anatomy, vectorcardiography, and cardiac electrophysiology. The new algorithm evaluated the diagnostic value through intracardiac electrophysiology in 205 cases of VA and PA. The new algorithm diagnoses VA based on the following 4-step process:

• 1.
  The QRS complex in leads II, III, and aVF shows a unidirectional R wave, and lead aVR shows a QS pattern.
• 2.
  S waves are predominant in two or more of leads I, aVF, and V6.
• 3.
  Lead V2 shows ≥3 phase waves or returning branch notching (note: returning branch refers to the band of QRS complexes returning to the baseline).
• 4.
  Lead V5 shows a negative wave in the initial portion or returning branch notching.

If none of these criteria are met, the diagnosis is PA. The diagnostic value of the new algorithm is compared with the Steurer algorithm and the Vereckei algorithm (diagnosed based on the QRS waveform characteristics of the two algorithms during electrophysiological verification, excluding the diagnosis of atrioventricular dissociation).

Results

The new algorithm showed significant advantages in terms of AUC value (0.83 vs. 0.61 vs. 0.57), sensitivity (83.6 % vs. 23.3 % vs. 24.8 %), and accuracy (82.9 % vs. 48.3 % vs. 46.3 %) compared to the Steurer algorithm and Vereckei algorithm based on QRS waveform characteristics for diagnosing VA (137 cases) and PA (68 cases). This indicates that the new algorithm is more accurate in identifying idiopathic VA. While there was a significant difference in specificity between the New algorithm and Steurer algorithm (82.3 % vs. 98.5 %, p < 0.05), the difference with Vereckei algorithm (82.3 % vs. 89.7 %) was not significant.

In the New algorithm, the sensitivity and specificity for each step are as follows:

• -
  Step 1: Sensitivity 34.3 %, Specificity 94.1 %.
• -
  Step 2: Sensitivity 24.1 %, Specificity 98.5 %.
• -
  Step 3: Sensitivity 18.3 %, Specificity 100 %.
• -
  Step 4: Sensitivity 6.6 %, Specificity 89.7 %.

Step 1 had the highest AUC value, indicating the best overall diagnostic performance among all steps. Step 2 and Step 3 also performed well, while Step 4 had relatively poorer diagnostic performance.

Conclusion

The new algorithm is suitable for identifying the origin of VA and PA rhythms.