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.
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.
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.
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