Acute coronary syndrome predictors depending on lipid metabolism indices

Authors

  • Валерія Василівна Ватага Shupik National Medical Academy of Postgraduate Education Dorogozhytska str., 9, Kyiv, Ukraine, 04112, Ukraine https://orcid.org/0000-0002-6168-9003

DOI:

https://doi.org/10.15587/2519-4798.2017.91269

Keywords:

acute coronary syndrome, dyslipidemia, cardiovascular diseases risk factors, coronary heart disease

Abstract

Aim. Determination of acute coronary syndrome (ACS) frequency in patients without dyslipidemia (DLP) and the analysis of the profile features of cardiovascular diseases risk factors (CVD RF) among these patients comparing to the patients having lipid metabolism disorders.

Materials and methods. Retrospective analysis of 91 medical card of patients having ACS (the average age 60,8±9,9 years) with the further estimation of the traditional CVD RF prevalence. According to the results of lipid blood spectrum, the patients were divided in 2 groups: the patients without DLP were in the first group, and the patients with lipid metabolism disorders were in the second group.

Results. ACS in patients without DLP appeared in 38.5% of cases. Reliable differences between the frequency of various forms of ACS, obesity and age among the patients of the both groups were found. Hypertension (AH) and stress were found more often among the traditional CVD RF regardless of DLP.

Conclusion. The ACS patients without DLP have greater depth of myocardial damage comparing to the patients with lipid metabolism disorders. The traditional CVD RF can not explain the ACS in patients without DLP. The further research in the area of the search of more (non-traditional) CVD RF in patients without DLP is relevant

Author Biography

Валерія Василівна Ватага, Shupik National Medical Academy of Postgraduate Education Dorogozhytska str., 9, Kyiv, Ukraine, 04112

Assistant

The Department of Family Medicine

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Published

2017-01-31

How to Cite

Ватага, В. В. (2017). Acute coronary syndrome predictors depending on lipid metabolism indices. ScienceRise: Medical Science, (1 (9), 31–34. https://doi.org/10.15587/2519-4798.2017.91269

Issue

No. 1 (9) (2017)

Section

Medical Science

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Copyright (c) 2017 Валерія Василівна Ватага

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