AIHM Hungary Chapter Event ~ Risk Assessment in Coronary Heart Disease: Study Discussion

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Description of Event: Coronary heart disease is a common health problem and a single leading cause of death and disability globally. The disease burden is increasing rapidly leading to a public health concern. over the past decades; significant improvement in the medical center occurred after the genetic revolution, but no significant reduction from CHD has been made, although there is advanced diagnostic technology and therapeutic management.

The preventive interventions for CHD are available for the high-risk group, but identifying these groups has remained. Risk assessment plays a pivotal role in predicting cardiovascular diseases (mainly coronary heart disease, and stroke), and helping the clinicians for targeting the intervention also might improve patient outcomes and cost-effectiveness. Several questions of interest about are there any consensus about the best model for CHD, which biomarker should incorporate besides the traditional risk factor, does the genetic information improved the model’s performance.

Our study aims to apply a systematic review method to provide an overview of the published modeling studies for predicting CHD in the general populations, also we are, therefore, concerned about the optimal models developed for CHD attempting to help the clinicians and patients by comparing the model’s performance.

We performed the search in five databases includes; Pubmed, Cochrane, Embase, Web of Science, and Scopus applying the human filter only on 24 September 2019.

The search strategy identified 7187 potential articles while 74 are eligible included in the review. Framingham and SCORE are the most popular models for CHD. The common set of predictors is age, gender, systolic blood pressure, total cholesterol, smoking, diabetes, and single nucleotides polymorphism reported in the genetics modeling studies.

The conclusion of this study is no generalizability of the models identified. most of the models are developmental only without validation. validation of the existing models is needed to ensure the generalizability and increase the transparency of the study. genetic modeling studies may improve the model’s performance, help to identify the targeted group and guide the clinician for effective intervention.

About the Speaker: Nayla Mohamed Gomaa Nasr is a Sudanese lecturer at Bahri University in Khartoum (Sudan), she graduated from Khartoum University (honored degree in public and environmental health), she attended Airlangga University in Indonesia from 2003 to 2016, where she got her master’s degree in epidemiology (honored degree) in public health (scholarship). Currently, she is a doctoral candidate at Debrecen University (faculty of medicine _department of public health and epidemiology) in Hungary (scholarship).

In 2009, Nayla was volunteered to work in the public health department at Khartoum University, she has established a small laboratory of hematology in her faculty. Nayla is focusing on medical entomology, parasitology and is also concerned about port inspection and quarantine for diseases control, and non-communicable diseases as well. In 2016-2018 Nayla worked as a quality manager, laboratory control, and in the exam centers.