Risk Stratification in MADIT II Type Patients

MADIT II 型患者的风险分层

• 批准号: 7071782
• 负责人: Wojciech Zareba
• 金额: $ 74.42万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2009-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7071782
• 关键词: atrial fibrillation; bioimaging /biomedical imaging; cardiovascular disorder therapy; clinical research; computer assisted medical decision making; computer program /software; cost effectiveness; electrocardiographic monitor; electrocardiography; human mortality; human subject; implantable defibrillators; mathematical model; medical implant science; model design /development; myocardial infarction; noninvasive diagnosis; patient safety /medical error; prognosis; quality of life; sudden cardiac death; tachycardia; ventricular fibrillation

DESCRIPTION (provided by applicant): Recently, the Multicenter Automatic Defibrillator Implantation Trial II (MADIT II) demonstrated that post-infarction patients with advanced left ventricular dysfunction, defined by ejection fraction equal to or < 30%, have a very high 19.6% 20-month mortality which was reduced by 28% with prophylactic implantation of a cardioverter-defibrillators. Over 30% of patients with SCDs receive appropriate therapy for ventricular tachycardia or ventricular fibrillation. Similar reduction in mortality associated with ICD therapy was recently reported from the Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT). Since the population of patients eligible for an ICD following MADIT II indications is very large, there is a great interest in developing methods and algorithms for identifying high- and low-risk individuals among MADIT ll-type patients to prioritize them for ICD therapy. Based on previous experience and recent preliminary analyses from the MADIT II data, we hypothesize that a combination of clinical variables and noninvasive ECG parameters, indicating contribution of different mechanisms that predispose to arrhythmias and sudden death, will allow identification of patients with increased benefit and those with little benefit from ICD therapy. Therefore, the primary aims of this study are: 1) to evaluate the predictive value of a multivariate model consisting of pre-specified clinical and ECG parameters for predicting arrhythmic events in MADIT II type postinfarction patients with severe left ventricular dysfunction; 2) to develop a multivariate risk-stratification model, based on a broader spectrum of pre-specified clinical covariates and ECG parameters, and from it a risk-scoring algorithm identifying high-risk and low-risk patient groups; this algorithm will be validated by a cross-validation study. Such an algorithm will enable an ordering of patients who may benefit most, and benefit least, from ICD therapy. The secondary objectives of this study are: 1) to determine the prognostic significance of clinical and noninvasive ECG variables for predicting non-sudden (non-arrhythmic) cardiac mortality in MADIT II type patients; identifying such individuals will further refine clinical practice and cost-effectiveness of primary prevention of SCO with ICD therapy; 2) to identify ECG predictors of inappropriate therapy delivered for episodes of atrial fibrillation or supraventricular tachyarrhythmias and evaluate the association between inappropriate therapy and the risk of ventricular tachyarrhythmias; 3) to determine whether clinical and ECG predictors contribute to identification of patients with worsening quality of life, and compare changes in quality of life of patients experiencing ICD therapy with those who do not, after adjusting for clinical and ECG parameters.

描述（由申请人提供）：最近，多中心自动除颤器植入试验II（MADIT II）表明，晚期左心室功能障碍（定义为射血分数等于或<30%）的梗死后患者的20个月死亡率非常高，为19.6%，预防性植入心律转复除颤器后死亡率降低了28%。超过30%的SCD患者接受了适当的室性心动过速或室颤治疗。最近在心力衰竭心源性猝死试验（SCD-HeFT）中报告了与ICD治疗相关的死亡率类似的降低。由于符合MADIT II适应症的ICD的患者人群非常大，因此开发用于在MADIT II型患者中识别高风险和低风险个体以优先考虑他们进行ICD治疗的方法和算法具有很大的兴趣。基于先前的经验和最近对MADIT II数据的初步分析，我们假设，临床变量和无创ECG参数的组合，表明易患心律失常和猝死的不同机制的贡献，将允许识别ICD治疗获益增加的患者和获益很少的患者。因此，本研究的主要目的是：1）评估由预先指定的临床和ECG参数组成的多变量模型对MADIT II型心肌梗死后严重左室功能不全患者发生心肌梗死事件的预测价值; 2）基于更广泛的预先指定的临床协变量和ECG参数，开发多变量风险分层模型，并从其中识别高风险和低风险患者组的风险评分算法;该算法将通过交叉验证研究进行验证。这样的算法将使得能够对可能从ICD治疗中受益最多和受益最少的患者进行排序。本研究的次要目的是：1）确定临床和无创ECG变量对预测非突发性MADIT II型患者的（非糖尿病）心源性死亡率;识别此类个体将进一步完善临床实践和ICD治疗一级预防SCO的成本效益; 2）识别针对房颤或室上性快速性心律失常发作提供的不适当治疗的ECG预测因子，并评估不适当治疗和室性快速性心律失常风险之间的关联; 3）确定临床和ECG预测因素是否有助于识别生活质量恶化的患者，并在调整临床和ECG参数后，比较接受ICD治疗的患者与未接受ICD治疗的患者的生活质量变化。