Risk Stratification and Prevention of Sudden Death in Patients with Heart Failure

For almost the past decade, recommendations for the use of implantable cardioverter defibrillators (ICDs) for primary prevention of sudden cardiac death have been based upon the left ventricular ejection fraction (LVEF). Current guidelines recommend an ICD for heart failure patients with LVEF ≤35% and NYHA functional class of II or III; however, because the majority of heart failure patients who qualify for ICD implantation based on these criteria will never have an event requiring ICD therapy over several years of follow-up, additional methods of risk stratification for sudden death are clearly needed. Additionally, most of the nearly 300,000 cardiac arrests that occur each year occur in patients without heart failure or significant left ventricular dysfunction. To improve the identification of patients at risk for sudden death, several criteria other than ejection fraction have been proposed and studied. Markers of autonomic tone, including heart rate turbulence and QT dynamicity, have shown some ability to predict total mortality but not arrhythmic events. Microvolt T-wave alternans testing was initially thought to be highly predictive of life-threatening arrhythmias, but prospective large sub-studies of the MADIT II and SCD-HeFT trials have failed to show a predictive value for T-wave alternans testing. Newer markers for risk are based upon the detection of myocardial fibrosis, which forms the substrate for re-entrant and malignant ventricular tachyarrhythmias. Markers of collagen turnover or quantification of myocardial scar by MRI may hold the best promise for identifying patients at highest risk for sudden cardiac death and may also identify patients at high risk but with an ejection fraction above 35%, who are not currently recommended for ICD implantation.     

Biomarkers for Risk Prediction in Acute Decompensated Heart Failure

Risk prediction in patients admitted with acute decompensated heart failure (ADHF) remains a challenge. Biomarkers may improve risk prediction, which in turn may help to better inform patients regarding short-term and long-term prognosis, therapy and care. Most data on biomarkers have been derived from patient cohorts with chronic heart failure. In ADHF, currently, risk tools largely rely on common clinical and biochemical parameters. However, ADHF is not a single disease. It presents in various manners and different etiologies may underlie ADHF, which are reflected by different biomarkers. In the last decade, many studies have reported the prognostic value of these biomarkers. These studies have attempted to describe a value for statistical modeling, e.g., reclassification indices, in an effort to report incremental value over a clinical model or the “gold standard”. However, the overall incremental predictive value of biomarkers has been modest compared to already existing clinical models. Natriuretic peptides, e.g., (NTpro-)BNP, are the benchmark, but head-to-head comparisons show that there are novel biomarkers with comparable prognostic value. Multimarker strategies may provide superior risk stratification. Future studies should elucidate cost-effectiveness of single or combined biomarker testing. The purpose of this review was to provide an update on current biomarkers and to identify new promising biomarkers than can be used in prognostication of acute heart failure.     

The Usefulness of the MEESSI Score for Risk Stratification of Patients With Acute Heart Failure at the Emergency Department

Introduction and objectives

The MEESSI scale stratifies acute heart failure (AHF) patients at the emergency department (ED) according to the 30-day mortality risk. We validated the MEESSI risk score in a new cohort of Spanish patients to assess its accuracy in stratifying patients by risk and to compare its performance in different settings.

Risk Stratification in Acute Coronary Syndromes

Accurate and readily available systems for risk stratification and a wide array of antithrombotic agents, on top of classical anti-ischemic drugs, provide the noninvasive cardiologist admitting the patient in the CCU with an effective and reliable armamentarium for the safe management of most patients with ACS. From the interventionalist’s perspective, the immediate knowledge of the coronary anatomy yields the most valuable information to address the most appropriate treatment. The sooner angiography is performed the higher the benefit for patients at moderate to high risk, but if performed by expert teams and with the correct use of modern drugs and devices, the invasive approach has the potential to reduce costs and length of hospital stay also in low-risk patients. Although still some reluctance remains to equalize treatment strategies for patients with STEMI to those with NSTEMI, such differences will likely disappear in the near future with upcoming new evidence. Cardiac surgery may represent a life-saving alternative for patients presenting with NSTEMI evolving in cardiogenic shock or with mechanical complications, or in patients unsuitable for PCI or with failed PCI attempts. In stabilized conditions after the treatment of the culprit lesion, patients with severe multivessel disease may benefit from cardiac surgery to complete myocardial revascularization. Indications for CABG in this setting should be evaluated in the context of a local “heart team” or through prespecified protocols in centers without cardiac surgery on site.     

Combination Biomarkers for Risk Stratification in Patients With Chronic Heart Failure Biomarkers Prognostication in HF

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Heart Rate Variability in Risk Stratification of Cardiac Patients

Heart rate (HR) variability has been extensively studied in cardiac patients, especially in patients surviving an acute myocardial infarction (AMI) and also in patients with congestive heart failure (CHF) or left ventricular (LV) dysfunction. The majority of studies have shown that patients with reduced or abnormal HR variability have an increased risk of mortality within a few years after an AMI or after a diagnosis of CHF/LV dysfunction. Various measures of HR dynamics, such as time-domain, spectral, and non-linear measures of HR variability have been used in risk stratification. The prognostic power of various measures, except of those reflecting rapid R–R interval oscillations, has been almost identical, albeit some non-linear HR variability measures, such as short-term fractal scaling exponent have provided somewhat better prognostic information than the others. Abnormal HR variability predicts both sudden and non-sudden cardiac death. Because of remodeling of the arrhythmia substrate after AMI, early measurement of HR variability to identify those at high risk should likely be repeated later in order to assess the risk of fatal arrhythmia events. Future randomized trials using HR variability/turbulence as one of the pre-defined inclusion criteria will show whether routine measurement of HR variability/turbulence will become a routine clinical tool for risk stratification of cardiac patients.     

急性胸痛早期危险分层的研究进展

急性胸痛是急诊常见病症,早期危险分层识别高危和低危急性胸痛,既可缩短治疗时间,改善临床预后,又可避免过度诊疗,节约医疗资源。目前急性胸痛风险评估策略不断改善,急性胸痛早期危险分层的准确度逐步提高,但是危险分层工具的敏感性和特异性不一。现对目前急性胸痛早期危险分层的现状进行综述。     

Novel Biomarkers in Acute Heart Failure

Heart failure goes beyond mechanical dysfunction and involves an interplay of multiple pathophysiologic mechanisms, including inflammation, tissue remodeling, neurohormonal and endocrine signaling, and interactions with the renal and nervous systems. This article highlights some novel biomarkers that may aid in diagnosis, treatment, and prognosis of acute heart failure, specifically focusing on ST2, endoglin, galectin-3, cystatin C, neutrophil gelatinase–associated lipocalin, midregional pro-adrenomedullin, chromogranin A, adiponectin, resistin, and leptin and their emerging clinical roles.     

Fast Strain-Encoded Cardiac Magnetic Resonance for Diagnostic Classification and Risk Stratification of Heart Failure Patients

ObjectivesThe purpose of this study was to compare the ability of fast-strain encoded magnetic resonance (fast-SENC) cardiac magnetic resonance (CMR) to classify and risk stratify all-comer patients with different stages of chronic heart failure (Stages of heart failure A to D) based on American College of Cardiology/American Heart Association guidelines with standard clinical and CMR imaging data.BackgroundHeart failure is a major cause of morbidity and mortality, resulting in millions of deaths and hospitalizations annually.MethodsThe study population consisted of 1,169 consecutive patients between September 2017 and February 2019 who underwent CMR for clinical reasons, and 61 healthy volunteers. In addition, clinical follow-up was performed in Stages A and B patients after 1.9 ± 0.4 years. Wall motion score and late gadolinium enhancement score indexes, left ventricular (LV) ejection fraction, and global circumferential and longitudinal strain based on fast-SENC acquisitions, were calculated in all subjects. The percentage of myocardial segments with strain ≤?17% (% normal myocardium) was determined in all subjects.ResultsLV ejection fraction, global circumferential and longitudinal strain, and % normal myocardium significantly decreased with increasing heart failure stages (p < 0.001 for all by analysis of variance). By multivariable analysis, % normal myocardium remained an independent predictor of heart failure stages, exhibiting closer association than LV ejection fraction (r_partial = 0.76 vs. r_partial = 0.30; p < 0.001). Importantly, 149 of 399 (37%) with Stage A were reclassified to Stage B, that is, as having subclinical LV dysfunction based on % normal myocardium <80%. Such patients exhibited significantly higher rates of all-cause mortality and hospital stay due to heart failure during follow-up, compared with patients with % normal myocardium ≥80% (chi-square = 6.9; p = 0.03).ConclusionsThe % normal myocardium, determined by fast-SENC, enables improved identification of asymptomatic patients with subclinical LV dysfunction compared with LV ejection fraction and risk stratification of patients with so far asymptomatic heart failure. The identification of such presumably healthy patients at high risk for heart failure-related outcomes may bear important medical implications.