Use of the Dominant Component Analysis for Improvement of Preventive Measures in Patients with Cardiovascular Risks
Использование метода главных компонент для совершенствования профилактической работы с факторами риска сердечно-сосудистых заболеваний release_ei4tniwdpba7thnov35jorcyse

by I.V. Kovrigina, Scientific and Research Institute — Regional Clinical Hospital No.1 named after Professor S.V. Ochapovsky of Krasnodar Territorial Ministry of Health, E.V. Bolotova, A.V. Kontsevaya, Krasnodar, Russian Federation, Kuban State Medical University of the Ministry of Health of the Russian Federation; Krasnodar, Russian Federation, National Medical Research Centre of Preventive Medicine of the Ministry of Health of the Russian Federation; Moscow, Russian Federation

Published in Doctor Ru by NP Rusmedical Group.

2021   Volume 20, p7-14

Abstract

Study Objective: To improve efficiency of cardiovascular disease (CVD) prevention in patients with health category IIIa in Krasnodar Territorial Outpatient Clinic using a factorial analysis (dominant component analysis) of stage 1 health assessment results for 2015 and 2018. Materials and Methods. The study includes subjects who underwent stage 1 health assessment: 2015 — 2,461 people, 2018 — 2,772 people. Patients with health category IIIa were assessed for modifiable risk factors (RF) of CVDs using the dominant component analysis. Study Results. In 2015, health category IIIа was assigned to 29.9% of patients; female patients accounted for 68.5% (median age: 62 years), males accounted for 31.5% (median age: 60 years). In 2018, health category IIIа was recorded for 41.5% of patients; female patients accounted for 64.3% (median age: 63 years), males accounted for 35.7% (median age: 62 years). Factorial analysis demonstrated that male patients have the following composition of modifiable CVD RFs: factor 1 — improper diet (ID) and physical inactivity (PIA); factor 2 — hypercholesterolemia (HCS), tobacco smoking and alcohol abuse (TSAA); factor 3 — arterial hypertension (AH) and ID; factor 4 — AH. Women demonstrated different compositions of CVD RFs: factor 1 — ID and PIA; factor 2 — AH and HCS; factor 3 — BMI > 25 kg/m2 and hyperglycemia; factor 4 — TSAA. Conclusion. Gender differences together with modifiable CVD RFs in patients with risk category IIIa revealed with the help of the dominant component analysis allow correcting RFs taking into account combinations, most contributing to unfavourable cardiovascular events. Keywords: health assessment, risk factor, circulatory diseases, prevention, outpatient clinic, factorial analysis.
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