Department of Cardiology, Hospital Universitario de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Facultad de Medicina, Universidad de Salamanca, and CIBERCV, Salamanca, Spain.
Miguel Armijo Primary Care Centre, Salamanca, Spain.
BMJ Open. 2019 Feb 13;9(2):e024605. doi: 10.1136/bmjopen-2018-024605.
This study aims to obtain data on the prevalence and incidence of structural heart disease in a population setting and, to analyse and present those data on the application of spatial and machine learning methods that, although known to geography and statistics, need to become used for healthcare research and for political commitment to obtain resources and support effective public health programme implementation.
We will perform a cross-sectional survey of randomly selected residents of Salamanca (Spain). 2400 individuals stratified by age and sex and by place of residence (rural and urban) will be studied. The variables to analyse will be obtained from the clinical history, different surveys including social status, Mediterranean diet, functional capacity, ECG, echocardiogram, VASERA and biochemical as well as genetic analysis.
The study has been approved by the ethical committee of the healthcare community. All study participants will sign an informed consent for participation in the study. The results of this study will allow the understanding of the relationship between the different influencing factors and their relative importance weights in the development of structural heart disease. For the first time, a detailed cardiovascular map showing the spatial distribution and a predictive machine learning system of different structural heart diseases and associated risk factors will be created and will be used as a regional policy to establish effective public health programmes to fight heart disease. At least 10 publications in the first-quartile scientific journals are planned.
NCT03429452.
本研究旨在获取人群中心脏结构性疾病的患病率和发病率数据，并应用空间和机器学习方法对这些数据进行分析和呈现。尽管这些方法在地理学和统计学中已经为人所知，但它们需要应用于医疗保健研究中，以争取政治承诺，为有效公共卫生计划的实施获取资源和支持。
我们将对萨拉曼卡（西班牙）的随机居民进行横断面调查。将研究 2400 名按年龄和性别以及居住地（农村和城市）分层的个体。分析的变量将从临床病史、包括社会地位、地中海饮食、功能能力、心电图、超声心动图、VASERA 和生化以及遗传分析在内的不同调查中获得。
该研究已获得医疗保健社区伦理委员会的批准。所有研究参与者将签署参与研究的知情同意书。这项研究的结果将有助于理解不同影响因素之间的关系及其在结构性心脏病发展中的相对重要性权重。这将首次创建一个详细的心血管地图，显示不同结构性心脏病和相关风险因素的空间分布，并创建一个预测性机器学习系统，将其作为区域政策，以制定有效的公共卫生计划来防治心脏病。计划至少在第一四分位科学期刊上发表 10 篇论文。
NCT03429452。
