Centro Cardiologico Monzino, IRCCS, Italy.
Cardiology Division, Cardiac Arrhythmia Centre and Cardiomyopathies Unit, San Camillo-Forlanini Hospital, Italy.
Eur J Prev Cardiol. 2020 Dec;27(2_suppl):5-11. doi: 10.1177/2047487320959010.
The high morbidity and poor survival rates associated with chronic heart failure still represent a big challenge, despite improvements in treatments and the development of new therapeutic opportunities. The prediction of outcome in heart failure is gradually moving towards a multiparametric approach in order to obtain more accurate models and to tailor the prognostic evaluation to the individual characteristics of a single subject. The Metabolic Exercise test data combined with Cardiac and Kidney Indexes (MECKI) score was developed 10 years ago from 2715 patients and subsequently validated in a different population. The score allows an accurate evaluation of the risk of heart failure patients using only six variables that include the evaluation of the exercise capacity (peak oxygen uptake and ventilation/CO production slope), blood samples (haemoglobin, Na, Modification of Diet in Renal Disease) and echocardiography (left ventricular ejection fraction). Over the following years, the MECKI score was tested taking into account therapies and specific markers of heart failure, and it proved to be a simple, useful tool for risk stratification and for therapeutic strategies in heart failure patients. The close connection between the centres involved and the continuous updating of the data allow the participating sites to propose substudies on specific subpopulations based on a common dataset and to put together and develop new ideas and perspectives.
尽管治疗方法有所改善，新的治疗机会也有所增加，但慢性心力衰竭相关的高发病率和低生存率仍然是一个巨大的挑战。心力衰竭预后的预测正逐渐朝着多参数方法发展，以便获得更准确的模型，并根据单个患者的个体特征调整预后评估。代谢运动测试数据与心脏和肾脏指数（MECKI）评分是 10 年前从 2715 名患者中开发出来的，并随后在不同人群中进行了验证。该评分仅使用包括运动能力评估（峰值摄氧量和通气/CO 产量斜率）、血液样本（血红蛋白、Na、肾脏病饮食改良）和超声心动图（左心室射血分数）在内的六个变量，即可对心力衰竭患者的风险进行准确评估。在随后的几年中，考虑到治疗方法和心力衰竭的特定标志物，对 MECKI 评分进行了测试，结果证明它是心力衰竭患者进行风险分层和治疗策略的一种简单、有用的工具。参与中心之间的密切联系和数据的不断更新，使得参与站点能够根据共同的数据集提出针对特定亚人群的子研究，并汇集和发展新的思路和观点。
