IRCCS Istituti Clinici Scientifici Maugeri Spa SB, Italy.
Centro Cardiologico Monzino IRCCS, Italy.
Eur J Prev Cardiol. 2020 Dec;27(2_suppl):12-18. doi: 10.1177/2047487320962990.
Heart failure is a serious condition with high prevalence (about 2% in the adult population in developed countries, and more than 8% in patients older than 75 years). About 3-5% of hospital admissions are linked with heart failure incidents. The guidelines of the European Society of Cardiology for the diagnosis and treatment of acute and chronic heart failure have identified individual markers in patients with heart failure, including demographic data, aetiology, comorbidities, clinical, radiological, haemodynamic, echocardiographic and biochemical parameters. Several scoring systems have been proposed to identify adverse events, such as destabilizations, re-hospitalizations and mortality. This article reviews scoring systems for heart failure prognostication, with particular mention of those models with exercise tolerance objective definition. Although most of the models include readily available clinical information, quite a few of them comprise circulating levels of natriuretic peptides and a more objective evaluation of exercise tolerance. A literature review was also conducted to (a) identify heart failure risk-prediction models, (b) assess statistical approach, and (c) identify common variables.
心力衰竭是一种患病率较高的严重疾病（在发达国家的成年人群中约为 2%，在 75 岁以上的患者中超过 8%）。约 3-5%的住院治疗与心力衰竭事件有关。欧洲心脏病学会关于急性和慢性心力衰竭的诊断和治疗指南确定了心力衰竭患者的个体标志物，包括人口统计学数据、病因、合并症、临床、影像学、血液动力学、超声心动图和生化参数。已经提出了几种评分系统来识别不良事件，如不稳定、再住院和死亡。本文回顾了心力衰竭预后评分系统，特别提到了那些具有运动耐量客观定义的模型。尽管大多数模型都包含易于获得的临床信息，但其中相当一部分模型包含利钠肽的循环水平和对运动耐量的更客观评估。还进行了文献回顾，以（a）确定心力衰竭风险预测模型，（b）评估统计方法，和（c）确定常见变量。
