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预测心脏再同步治疗反应的生存能力测试

Viability Test in Prediction of Response to Cardiac Resynchronization Therapy.

作者信息

Grozdic Milojevic Isidora, Radovanovic Nikola N, Petrovic Jelena, Sobic-Saranovic Dragana, Artiko Vera

机构信息

Center for Nuclear Medicine and PET, University Clinical Center of Serbia, 11000 Belgrade, Serbia.

Faculty of Medicine, University Belgrade, 11000 Belgrade, Serbia.

出版信息

J Clin Med. 2025 Jul 29;14(15):5341. doi: 10.3390/jcm14155341.

DOI:10.3390/jcm14155341
PMID:40806963
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12347201/
Abstract

: This study aimed to evaluate myocardial scar burden and distribution, as well as other nuclear imaging parameters, in predicting cardiac resynchronization therapy (CRT) responses and long-term outcomes in patients selected for CRT with ischemic HF etiology. : Seventy-one patients were prospectively included. They all had NYHA class II/III despite optimal medical therapy, LVEF ≤ 35%, wide QRS complexes, and ischemic HF etiology. All were indicated for de novo CRT implantation and underwent a SPECT MPI viability test prior to CRT implantation. Two-dimensional echocardiography was performed one day before CRT implantation and 6 months after the intervention. The follow-up examination was conducted six months after the CRT implantation and, after 5 years, patients underwent a telephone follow-up to assess survival. : Most patients (85%) were male, with an average age of 66.26 ± 9.25 yrs. SPECT MPI revealed large myocardial scars (44.53 ± 20.94%) with high summed rest scores (SRSs) of 25.02 ± 11.29 and low EFs of 26.67 ± 7.71%. At the 6-month follow-up, after the CRT implantation, the NYHA class significantly changed and 35% of the patients were classified as CRT responders. The only difference between responders and non-responders was in the SRS and myocardial scar size ( < 0.001). A scar size of 19.5% was an optimal cutoff for the prediction of CRT response (AUC 0.853, Sn 85% and 1-sp 94%). : SPECT MPI parameters are valuable in predicting responses and long-term survival in patients with CRT. Patients with myocardial scars of less than 19.5% may be suited to CRT and experience better cardiovascular survival.

摘要

本研究旨在评估心肌瘢痕负荷及分布,以及其他核成像参数,以预测缺血性心力衰竭病因且入选心脏再同步治疗(CRT)的患者的CRT反应及长期预后。前瞻性纳入71例患者。尽管接受了最佳药物治疗,但他们均为纽约心脏协会(NYHA)心功能II/III级,左心室射血分数(LVEF)≤35%,QRS波群增宽,且为缺血性心力衰竭病因。所有患者均适合首次CRT植入,并在CRT植入前接受了单光子发射计算机断层扫描心肌灌注显像(SPECT MPI)存活测试。在CRT植入前一天和干预后6个月进行二维超声心动图检查。在CRT植入后6个月进行随访检查,5年后,患者接受电话随访以评估生存率。大多数患者(85%)为男性,平均年龄为66.26±9.25岁。SPECT MPI显示存在大面积心肌瘢痕(44.53±20.94%),静息总分(SRS)较高,为25.02±11.29,EF较低,为26.67±7.71%。在CRT植入后的6个月随访中,NYHA心功能分级显著改变,35%的患者被归类为CRT反应者。反应者与无反应者之间的唯一差异在于SRS和心肌瘢痕大小(<0.001)。瘢痕大小为19.5%是预测CRT反应的最佳截断值(曲线下面积[AUC]为0.853,敏感度[Sn]为85%,1-特异度[1-sp]为94%)。SPECT MPI参数在预测CRT患者的反应及长期生存方面具有重要价值。心肌瘢痕小于19.5%的患者可能适合CRT,并具有更好的心血管生存率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a04/12347201/bdf3b7896912/jcm-14-05341-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a04/12347201/b4c1cda50e1e/jcm-14-05341-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a04/12347201/bde0f9576926/jcm-14-05341-sch001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a04/12347201/37ac6d306cb5/jcm-14-05341-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a04/12347201/bdf3b7896912/jcm-14-05341-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a04/12347201/b4c1cda50e1e/jcm-14-05341-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a04/12347201/bde0f9576926/jcm-14-05341-sch001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a04/12347201/37ac6d306cb5/jcm-14-05341-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a04/12347201/bdf3b7896912/jcm-14-05341-g003.jpg

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Coronary Plaque Radiomic Phenotypes Predict Fatal or Nonfatal Myocardial Infarction: Analysis of the SCOT-HEART Trial.冠状动脉斑块放射组学表型预测致命或非致命性心肌梗死:SCOT-HEART试验分析
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Cardiac Magnetic Resonance Identifies Responders to Cardiac Resynchronization Therapy with an Assessment of Septal Scar and Left Ventricular Dyssynchrony.
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J Clin Med. 2023 Nov 20;12(22):7182. doi: 10.3390/jcm12227182.
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Myocardial Perfusion SPECT Imaging Radiomic Features and Machine Learning Algorithms for Cardiac Contractile Pattern Recognition.心肌灌注 SPECT 成像的放射组学特征及机器学习算法在心脏收缩模式识别中的应用。
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