Development of Minimally Invasive Cardiac Surgery Technologies as a Direction That Affects the Reduction of Mortality from Cardiovascular Diseases (on the Example of the Nizhny Novgorod Region)

Abstract

Background.Cardiovascular diseases (CVD) are the leading cause of death in the population. It is necessary to assess the priority areas of investment and development of medical technologies that can effectively influence the reduction of mortality.
 Aims to study the impact of minimally invasive surgical interventions on population mortality.
 Materials and methods.During the period from 2009 to 2019 was conducted analysis and assessment of the effect of the number of percutaneous coronary interventions (PCI) performed in the Nizhny Novgorod region, on mortality, including mortality from CVD, ischemic heart disease (IHD) and acute myocardial infarction (AMI) To study the relationship between these indicators were calculated the Spearman rank correlation coefficient. The prediction was performed using the multiple regression method. To evaluate the initial and predicted data (regression model), we used the cook and Mahalanobis distance indicators.
 Results.Over 11 years, the region has seen a significant increase in the number of PCI-from 220 to 6048 (27.5 times). During the same time, the total death rate in the region decreased from 17.42 to 14.60 per 1000 population (by 16.2%), fromСМВby 30.7%. A strong negative correlation was found between the number of PCI and mortality from CVD (r = 0.892), from CHD (r = 0.856), and from AMI (r = 0.904). A regression model of the result was developed, taking into account mortality rates and the number of PCI. The cook and Mahalanobis distance indicators indicate a change in the development vector of data variance since 2014, which may be due to changes in the infrastructure and volumes of cardiological and cardiac surgery care.
 Conclusion.The results of the analysis indicate the high feasibility of further development of cardiac surgery in the region. The resulting regression model can be used in planning the volume of medical care, taking into account the achievement of target demographic indicators and available health resources.