DEVELOPMENT OF LOGISTIC REGRESSION EQUATIONS FOR FRAILTY ASSESSING IN PATIENTS WITH ACUTE CORONARY SYNDROME

DOI: https://doi.org/10.29296/25877305-2021-04-14
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Issue: 
4
Year: 
2021

S. Kim(1, 2); A. Pushkin(1)–3, Candidate of Medical Sciences; Professor S. Rukavishnikova(1)–3,
Biol. Dr.; V. Yakovlev(4), MD; A. Narkevich(5), Candidate of Medical Sciences (1)City Multi-field Hospital
№2, Saint-Petersburg (2)Saint Petersburg Institute of Bioregulation and Gerontology (3)I.P. Pavlov First
Saint Petersburg State Medical University (4)S.M. Kirov Military Medical Academy, Saint-Petersburg (5)Prof.
V.F. Voino-Yasenetsky Krasnoyarsk State Medical University

Age is a reliable predictor of poor outcomes in acute coronary syndrome (ACS). In this particular meaning, the main risk factor in elderly patients – senile asthenia syndrome (SAS) or «frailty», is acquiring. The aim of this study is to develop a mathematical logistic regression model for other patients with acute coronary syndrome and to assess its quality in comparison with research tools commonly used for the comprehensive geriatric assessment of patients with ACS. Material and methods. To construct mathematical models of logistic regression, data on 300 patients with ACS were used. 50 (16.7%) patients were diagnosed with myocardial infarction with ST segment elevation, 126 (42.0%) patients had myocardial infarction without ST segment elevation, and 124 (41.3%) patients had unstable angina pectoris. Frailty was assessed using two scales: the Green frailty rating scale and the Fried frailty rating scale. In the course of the study, mathematical models of logistic regression were constructed using the «Enter» methods and step-by-step direct and reverse methods. Results. Indicators of sensitivity, specificity and accuracy in assessing the frailty of patients with ACS when using a model built using the reverse stepwise method, have maximum values and are respectively 86.3 (80.1; 90.7%), 90.8 (84.9; 94.5%) and 88.4 (86.0; 89.7%). With a decrease in the number of parameters measured in a patient from 7 to 4, the indices of sensitivity, specificity and accuracy are lower and amount to 81.3 (74.5; 86.5%), 87.2 (80.7; 91.8%), 84.1 (81.5; 85.7%). Conclusion. In the course of the study, three mathematical models of logistic regression were built, which allow assessing the fragility of patients with ACS, which can be used in an emergency, at the prehospital stage and after discharge from the hospital.
Keywords: 
cardiology
acute coronary syndrome
frailty
senile asthenia syndrome
rating scales
logistic regression

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