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American Heart Association

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Final ID: Sa2102

ECG correlates of chronic right ventricular pacing: QT interval predicts pacing-induced cardiomyopathy while QRS duration predicts cardiac resynchronization therapy response

Abstract Body (Do not enter title and authors here): Background: Some patients with chronic right ventricular (RV) pacing develop pacing-induced cardiomyopathy (PICM) and benefit from upgrade to cardiac resynchronization therapy (CRT). However, there are no established ECG screening criteria for PICM.
Aim: We sought to evaluate ECG correlates of (i) PICM and (ii) CRT response.
Methods: We retrospectively identified all CRT upgrades (biventricular pacing) for PICM (LVEF <50%) at our center 2014-2018 and gauged CRT response (LVEF increase >5% on echocardiogram 3-12 months post CRT). Patients with ≥5 ECGs all demonstrating RV pacing over ≥2 years and all echocardiographic LVEF ≥50% served as controls. Root-mean-squared (3D) ECG was obtained from reconstructed orthogonal X, Y, Z leads. We used logistic regressions to predict PICM and CRT response from ECG intervals and voltage-time-integrals (VTI).
Results: 108 patients [74±11 years, 28% female, LVEF 29±8%, QRS duration (QRSd) 167±25 ms, QTc 515±39 ms] with CRT upgrade for PICM were compared to 186 controls (77±14 years, 53% female, LVEF 57±5%, QRSd 144±21 ms, QTc 473±33 ms). Discrimination of PICM was highest with QTc (AUC 0.80) followed by QRSd (0.77) and VTIQRS-3D (0.75, Table 1, Figure 1). QTc >480 ms detected PICM with sensitivity 84% and specificity 74%. With CRT upgrade, LVEF improved by 14±11%. CRT response (ΔLVEF >5%) occurred in 77/108 (71%). Lack of CRT response was best predicted by QRSd (AUC 0.65) followed by ΔVTIQRS-3D (0.61, Table 2). Lack of CRT response was noted in 52% with QRSd >180 ms, while 78% with QRS duration ≤180 ms showed CRT response.
Conclusions: In patients with chronic RV pacing, QTc >480 ms identifies those susceptible to PICM, and QRSd >180 ms identifies those who may not respond to CRT.
  • Gupta, Amulya  ( , Kansas City , Kansas , United States )
  • Shahab, Ahmed  ( , Kansas City , Kansas , United States )
  • Harvey, Christopher  ( , Kansas City , Kansas , United States )
  • Sheldon, Seth  ( , Kansas City , Kansas , United States )
  • Reddy, Madhu  ( , Kansas City , Kansas , United States )
  • Noheria, Amit  ( , Kansas City , Kansas , United States )
  • Author Disclosures:
    Amulya Gupta: DO NOT have relevant financial relationships | Ahmed Shahab: DO NOT have relevant financial relationships | Christopher Harvey: DO NOT have relevant financial relationships | Seth Sheldon: DO have relevant financial relationships ; Speaker:Boston Scientific:Active (exists now) ; Consultant:Medtronic:Active (exists now) ; Speaker:Medtronic:Past (completed) ; Consultant:Biosense Webster (J&J):Active (exists now) | Madhu Reddy: No Answer | Amit Noheria: DO NOT have relevant financial relationships
Meeting Info:

Scientific Sessions 2024

2024

Chicago, Illinois

Session Info:

We’ve Got Rhythm! Insights From ECG and Rhythm Monitoring

Saturday, 11/16/2024 , 10:30AM - 11:30AM

Abstract Poster Session

More abstracts from these authors:
Learning Curve for Left Bundle Branch Area Pacing Lead Implantation

Clark Maci, Zerr Hannah, Ose Benjamin, Fritz David, Trupp Caroline, Gupta Amulya, Shahab Ahmed, Noheria Amit, Sheldon Seth

Classifying Left Ventricular Hypertrophy from ECG in Overall Population and Bundle Branch Blocks: Machine Learning Models are Superior to Published ECG Criteria

Debauge Ashley, Harvey Christopher, Gupta Amulya, Noheria Amit

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