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A Predictive Model for Super-Response to Cardiac Resynchronization Therapy: The QQ-LAE Score.

Xi Liu1, Yiran Hu1,2, Wei Hua1

  • 1State Key Laboratory of Cardiovascular Disease, Arrhythmia Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.

Cardiology Research and Practice
|September 10, 2020
PubMed
Summary
This summary is machine-generated.

A new QQ-LAE score helps identify super-responders for cardiac resynchronization therapy (CRT). This score predicts which patients will benefit most from CRT, improving treatment selection.

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Area of Science:

  • Cardiology
  • Medical Technology

Background:

  • Cardiac resynchronization therapy (CRT) effectiveness varies among patients.
  • Identifying super-responders is crucial for optimizing CRT benefits.

Purpose of the Study:

  • To develop a predictive scoring model for identifying super-responders to CRT.
  • To assess the model's ability to predict long-term clinical outcomes.

Main Methods:

  • Retrospective analysis of 387 CRT patients.
  • Multivariate logistic regression to identify predictors of super-response (≥15% LVEF increase).
  • Multivariate Cox regression to evaluate long-term outcomes across score categories.

Main Results:

  • 109 patients (28.2%) were super-responders.
  • Five independent predictors (QQ-LAE) identified: no fragmented QRS, QRS duration ≥170ms, LBBB, LA diameter <45mm, LVEDD <75mm.
  • Super-response rates were 14.6% (score 0-3), 40.3% (score 4), and 64.1% (score 5).
  • Higher scores significantly reduced risks of cardiac death/transplant, HF hospitalization, and all-cause mortality.

Conclusions:

  • The QQ-LAE score effectively predicts super-response to CRT.
  • This score aids in selecting optimal candidates for CRT in clinical practice.