Tomsk National Research Medical Center of the Russian Academy of Sciences
Tomsk, 634012, Russia
NCT Number: NCT04489355
The study focuses on the development of a new personalized approach to diagnostics and surgical treatment of patients with ischemic cardiomyopathy. The algorithm for selection of patients for certain type of cardiac surgery will be developed. The models for prediction of the risks and outcomes of cardiac surgery will be elaborated to reduce the rate of complications in the early and long-term postoperative period in patients with ischemic cardiomyopathy. Imaging modalities, methods for assessement of structural and functional state of the myocardium, biochemistry testing, immunohistochemical examination, and myocardial biopsy studies will be used to achieve these goals.
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Notify Me18 year–70 year
All sexes
Observational
Tomsk, 634012, Russia
The aim of the study is to develop a new personalized approach to diagnostics and surgical treatment of patients with ischemic cardiomyopathy.
Research Objectives:
Methods:
Structured collection of patient data will be performed in a database formed on the platform of the Microsoft Excel 2010 software (Microsoft Corp., USA). Statistical processing of the results will be carried out using the SPSS 23.0 for Windows software package (IBM Corp., Armonk, NY, USA). The normality of the law of distribution of quantitative indicators will be checked using the Shapiro-Wilks criterion. Normally distributed parameters will be presented as mean value (M) and standard deviation (StD) in the form M ± StD; not normally distributed parameters will be presented as median (Me) and the 1st and 3rd interquantile intervals (Q25 - Q75) in the form of Me [Q25; Q75]. Qualitative data will be described by the frequency of occurrence or its percentage. To find statistical dependences, to determine their strength and direction, the Pearson correlation coefficient (r) (for normally distributed parameters) and Spearman correlation coefficient (for for not normally distributed parameters and for qualitative indicators in the ordinal scale) will be calculated. Using logistic regression, significant predictors will be identified for the values of reverse remodeling in the long term after surgical treatment. When conducting a multivariate analysis of interconnections, first, by means of a univariate analysis, the main parameters that influence the studied value will be identified, then, based on the search for intergroup correlations, the signs that have a moderate or strong relationship will be eliminated, and multivariate modeling of the relationships will be performed.
Survival analysis will be performed using the Kaplan-Meier method. All statistics will be considered significant at p <0.05.
During the work, the methods of statistical analysis can be revised and (or) supplemented.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: 12 months
Number of participants with a decrease in left ventricular end-systolic volume by 15% or more.
Time frame: 12 months
Cardiac death, %
Time frame: 12 months
Number of participants with increased exercise tolerance according to spiroergometry by 15% or more.
Tomsk National Research Medical Center of the Russian Academy of Sciences
Other
Assessment of Risks and Outcomes of Surgical Intervention in Patients With Ischemic Cardiomyopathy in the Early and Long-term Postoperative Period, Selection of Optimal Surgical and Surgical Treatment
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