Impact of public health initiatives on acute coronary syndrome fatality rates in Portugal

The HEARTS partner forum-supporting implementation of HEARTS to treat and control hypertension

Cardiovascular diseases (CVD), principally ischemic heart disease (IHD) and stroke, are the leading causes of death (18. 6 million deaths annually) and disability (393 million disability-adjusted life-years lost annually), worldwide. High blood pressure is the most important preventable risk factor for CVD and deaths, worldwide (10.8 million deaths annually). In 2016, the World Health Organization (WHO) and the United States Centers for Disease Control (CDC) launched the Global Hearts initiative to support governments in their quest to prevent and control CVD. HEARTS is the core technical package of the initiative and takes a public health approach to treating hypertension and other CVD risk factors at the primary health care level. The HEARTS Partner Forum, led by WHO, brings together the following 11 partner organizations: American Heart Association (AHA), Center for Chronic Disease Control (CCDC), International Society of Hypertension (ISH), International Society of Nephrology (ISN), Pan American Health Organization (PAHO), Resolve to Save Lives (RTSL), US CDC, World Hypertension League (WHL), World Heart Federation (WHF) and World Stroke Organization (WSO). The partners support countries in their implementation of the HEARTS technical package in various ways, including providing technical expertise, catalytic funding, capacity building and evidence generation and dissemination. HEARTS has demonstrated the feasibility and acceptability of a public health approach, with more than seven million people already on treatment for hypertension using a simple, algorithmic HEARTS approach. Additionally, HEARTS has demonstrated the feasibility of using hypertension as a pathfinder to universal health coverage and should be a key intervention of all basic benefit packages. The partner forum continues to find ways to expand support and reinvigorate enthusiasm and attention on preventing CVD. Proposed future HEARTS Partner Forum activities are related to more concrete information sharing between partners and among countries, expanded areas of partner synergy, support for implementation, capacity building, and advocacy with country ministries of health, professional societies, academy and civil societies organizations. Advancing toward the shared goals of the HEARTS partners will require a more formal, structured approach to the forum and include goals, targets and published reports. In this way, the HEARTS Partner Forum will mirror successful global partnerships on communicable diseases and assist countries in reducing CVD mortality and achieving global sustainable development goals (SDGs).

An interpretable machine learning approach to estimate the influence of inflammation biomarkers on cardiovascular risk assessment

BACKGROUND AND OBJECTIVE

Cardiovascular disease has a huge impact on health care services, originating unsustainable costs at clinical, social, and economic levels. In this context, patients' risk stratification tools are central to support clinical decisions contributing to the implementation of effective preventive health care. Although useful, these tools present some limitations, in particular, some lack of performance as well as the impossibility to consider new risk factors potentially important in the prognosis of severe cardiac events. Moreover, the actual use of these tools in the daily practice requires the physicians' trust. The main goal of this work addresses these two issues: (i) evaluate the importance of inflammation biomarkers when combined with a risk assessment tool; (ii) incorporation of personalization and interpretability as key elements of that assessment.

METHODS

Firstly, machine learning based models were created to assess the potential of the inflammation biomarkers applied in secondary prevention, namely in the prediction of the six month risk of death/myocardial infarction. Then, an approach based on three main phases was created: (i) set of interpretable rules supported by clinical evidence; (ii) selection based on a machine learning classifier able to identify for a given patient the most suitable subset of rules; (iii) an ensemble scheme combining the previous subset of rules in the estimation of the patient cardiovascular risk. All the results were statistically validated (t-test, Wilcoxon-signed rank test) according to a previous verification of data normality (Shapiro-Wilk).

RESULTS

The proposed methodology was applied to a real acute coronary syndrome patients dataset (N = 1544) from the Cardiology Unit of Coimbra Hospital and Universitary centre. The first assessment was based on the GRACE tool and a Random Forest classifier, the incorporation of inflammation biomarkers achieved SE=0.83; SP=0.84 whereas the original GRACE risk factors reached SE=0.75; SP=0.85. In the second phase, the proposed approach with inflammation biomarkers achieved SE=0.763 and SP=0.778.

CONCLUSIONS

This approach confirms the potential of combining inflammation markers with the GRACE score, increasing SE and SP, when compared with the original GRACE. Additionally, it assures interpretability and personalization, which are critical issues to allow its application in the daily clinical practice.