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Almusaad A, Sweidan R, Alanazi H, Jamiel A, Bokhari F, Al Hebaishi Y, Al Fagih A, Alrawahi N, Al-Mandalawi A, Hashim M, Al Ghamdi B, Amin M, Elmaghawry M, Al Shoaibi N, Sorgente A, Loricchio M, AlMohani G, Al Abri I, Benjamin E, Sudan N, Chami A, Badie N, Sayed M, Hersi A. Long-term reverse remodeling and clinical improvement by MultiPoint Pacing in a randomized, international, Middle Eastern heart failure study. J Interv Card Electrophysiol 2021; 63:399-407. [PMID: 34156610 PMCID: PMC8983631 DOI: 10.1007/s10840-020-00928-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 12/27/2020] [Indexed: 11/28/2022]
Abstract
Purpose Cardiac resynchronization therapy (CRT) with multipoint left ventricular (LV) pacing (MultiPoint™ Pacing, MPP) has been shown to improve CRT response, although MPP response using automated pacing vector programming has not been demonstrated in the Middle East. The purpose of this study was to compare the impact of MPP to conventional biventricular pacing (BiV) using echocardiographic and clinical changes at 6-month post-implant. Methods This prospective, randomized study was conducted at 13 Middle Eastern centers. After de novo CRT-D implant (Abbott Unify Quadra MP™ or Quadra Assura MP™) with quadripolar LV lead (Abbott Quartet™), patients were randomized to either BiV or MPP therapy. In BiV patients, the LV pacing vector was selected per standard practice; in MPP patients, the two LV pacing vectors were selected automatically using VectSelect. CRT response was defined at 6-month post-implant by a reduction in LV end-systolic volume (ESV) ≥ 15%. Results One hundred and forty-two patients (61 years old, 68% male, NYHA class II/III/IV 19%/75%/6%, 33% ischemic, 57% hypertension, 52% diabetes, 158 ms QRS, 25.8% ejection fraction [EF]) were randomized to either BiV (N = 69) or MPP (N = 73). After 6 months, MPP vs. BiV patients experienced greater ESV reduction (25.0% vs. 15.3%, P = 0.08), greater EF improvement (11.9% vs. 8.6%, P = 0.36), significantly greater ESV response rate (68.5% vs. 50.7%, P = 0.04), and significantly greater NYHA class improvement rate (80.8% vs. 60.3%, P = 0.01). Conclusions With MPP and automatic LV vector selection, more CRT patients in the Middle East experienced reverse remodeling and clinical improvement relative to conventional BiV pacing.
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Affiliation(s)
- Abdulmohsen Almusaad
- King Abdalaziz Medical City -National Guard Health Affairs, Riyadh, Kingdom of Saudi Arabia.
| | - Raed Sweidan
- King Fahad Armed Forces Hospital, Jeddah, Kingdom of Saudi Arabia
| | - Haitham Alanazi
- King Abdalaziz Medical City -National Guard Health Affairs, Riyadh, Kingdom of Saudi Arabia
| | - Abdelrahman Jamiel
- King Abdalaziz Medical City -National Guard Health Affairs, Riyadh, Kingdom of Saudi Arabia
| | - Fayez Bokhari
- King Fahad Armed Forces Hospital, Jeddah, Kingdom of Saudi Arabia
| | | | - Ahmed Al Fagih
- Prince Sultan Cardiac Center, Riyadh, Kingdom of Saudi Arabia
| | - Najib Alrawahi
- National Heart Center at the Royal Hospital, Muscat, Oman
| | | | | | - Bandar Al Ghamdi
- King Faisal Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia
| | | | | | - Naeem Al Shoaibi
- King Abdulaziz University Hospital, Jeddah, Kingdom of Saudi Arabia
| | | | | | | | - Ismail Al Abri
- National Heart Center at the Royal Hospital, Muscat, Oman
| | | | | | | | | | - Mohammed Sayed
- Aswan Heart Centre - Magdi Yacoub Heart Foundation, Aswan, Egypt
| | - Ahmad Hersi
- King Khalid University Hospital, Riyadh, Kingdom of Saudi Arabia
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García Guerrero JJ, Fernández de la Concha Castañeda J, Chacón Piñero A, Hidalgo Martínez C, Badie N, McSpadden L, Ryu K. Extending multipoint pacing CRT battery longevity by swapping left ventricular pulse configurations. J Interv Card Electrophysiol 2020; 57:481-487. [DOI: 10.1007/s10840-020-00720-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Accepted: 02/23/2020] [Indexed: 11/29/2022]
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Lee AWC, Costa CM, Strocchi M, Rinaldi CA, Niederer SA. Computational Modeling for Cardiac Resynchronization Therapy. J Cardiovasc Transl Res 2018; 11:92-108. [PMID: 29327314 PMCID: PMC5908824 DOI: 10.1007/s12265-017-9779-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 12/18/2017] [Indexed: 11/21/2022]
Abstract
Cardiac resynchronization therapy (CRT) is an effective treatment for heart failure (HF) patients with an electrical substrate pathology causing ventricular dyssynchrony. However 40-50% of patients do not respond to treatment. Cardiac modeling of the electrophysiology, electromechanics, and hemodynamics of the heart has been used to study mechanisms behind HF pathology and CRT response. Recently, multi-scale dyssynchronous HF models have been used to study optimal device settings and optimal lead locations, investigate the underlying cardiac pathophysiology, as well as investigate emerging technologies proposed to treat cardiac dyssynchrony. However the breadth of patient and experimental data required to create and parameterize these models and the computational resources required currently limits the use of these models to small patient numbers. In the future, once these technical challenges are overcome, biophysically based models of the heart have the potential to become a clinical tool to aid in the diagnosis and treatment of HF.
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Affiliation(s)
- Angela W C Lee
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | | | - Marina Strocchi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | | | - Steven A Niederer
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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