**Forecasting of the Possible Outcome of Prosthetics of the Aortal Valve on Preoperational Anatomo-Functional Hemodynamics and According to Heart Indicators**

F. F. Turaev1, A. M. Karaskov2 and S. I. Zheleznev2 *1V.Vakhidov Republican Specialized Center for Surgery, Tashkent, 2E.N.Meshalkin Novosibirsk State Research Institute of Circulation Pathology, Novosibirsk, 1Uzbekistan 2Russia* 

#### **1. Introduction**

Prosthetics of the aortal valve is recommended as a standard surgical procedure for the majority of patients with defects of the aortal valve, who need surgical treatment [1]. Being the most simple technically possible to make nowadays, prosthetics of the aortal valve makes 13 % from all operations in case of acquired valve defects [2,3]. The 5-year survival rate without operation makes 50-80 % whereas surgical treatment leads to recovery and survival rate increase even at a serious clinical course of aortal defect [4,5,6]. At present stage of cardiosurgery development there are some methods of estimation of risk of operation [7,8,9]. However indicators under which it would be possible to estimate the forecast of AV prosthetics in the postoperative period are quite poor [10,11]. Available scales of risk estimation sometimes limit an exact prediction of risk or overrate the risk at patients who undergo valve surgery with or without coronary shunting [12,13,14,15]. The estimation of preoperative indicators which characterize the postoperative forecast can be useful for preoperative stratification of risk.

The aim of the research was to estimate the influence of initial anatomic-functional and hemodynamic indicators when forecasting the nearest results at patients after prosthetics of the aortal valve.

#### **2. Material and methods**

To estimate the influence of initial anatomic-functional indicators on the results of AV prosthetics 394 patients who underwent isolated AV prosthetics in 2001-2007 have been examined. Out of 394 people there are 311men and 83women at the age of 10 – 78, middle age is 36,9 ± 1,3 years. In Functional ClassI on New York Heart Association there were 14 (3,6 %) patients, in class II - 42 (10,7 %), in class III - 296 (75,0 %), in class IV - 42 (10,7%). Patients have been divided according to hemodynamic implication of defect into two

Forecasting of the Possible Outcome of Prosthetics of the Aortal Valve on

**3. Results** 

prognosis efficacy (see Table 1).

Fig. 1. Share of influence of factors on the forecast

Preoperational Anatomo-Functional Hemodynamics and According to Heart Indicators 141

As a result of the performed analysis the variables put into factor groups (F) affecting the surgery prognosis were determined: F1 – blood supply disturbance (HF, NYHA FC), F2 – physical parameters (gender, age\*, weight\*, height\*, body surface area\*, Ketle index\*, CTI\*), F3 – hemodynamic parameters (SBP\*, DBP\*, MBP\*, BSV, HR\*, BMV\*, TPR\*, SPR, HI\*, LV stroke work\*), F4 – heart parameters (EDD\*, ESD\*, EDV\*, ESV\*, SV\*, EF\*, FS\*, RF\*, SVE\*, RV\*, LA\*, RA\*, PA\*), F5 – myocardial parameters (IVS\*, LVPW\*, LVMM\*, sPLVWT and dPLVWT\*, 2HD\*), F6 –valve morphology (calcification degree on AV, regurgitation degree on AV, MV, and TV), F7- – valve parameters (FA and ascending aorta diameter\*, AV gradients\*, AO\* surface, MO\* surface, MV gradients\*, Emv, Amv, E/A mv). Indexed parameters, reverse values and second degree were considered in «\*» variables, it has been leading to increase in

During research it has been defined, that for patients with isolated АV prosthetics greater influence on the operation forecast was made by factors heart characteristics, the central hemodynamics, indicators of valves, anthopometrical data and myocardium indicators (Fig. 1)

№ Variable Unit defenition Variable nomenclature **I Blood supply disturbance (F 1)**  1 HF I, IIА, IIB, III Heart failure 2 FC I , II, III, IV Functional class **II Physical parameters (F 2)**  1 Gender 1 - man, 2 – woman Patient gender 2 Age\* years Age 3 Weighr\* kg Weight 4 Height\* cm Height

groups: I group patients with an aortal stenosis and combined aortal defect with prevalence of stenosis (АS) - 165 (41,9 %) patients and II group with aortal insufficiency and combined aortal defect with prevalence of insufficiency (AI) - 229 (58,1 %) patients. The reasons of aortal defect (AD) were: rheumatic disease in 74,8 % of cases, an infectious endocarditis (IE) - 16,3 %, congenital defect АV - 8,5 %, an atherosclerotic degeneration and a calcification - 0,4 %. All patients took chest X-ray, ECG, EchoCG, laboratory examination. Patients condition at baseline was a landmark to determine all totality of defect pathogenetic disorders, and evaluation of the factors affecting the separate components of complete clinical picture creation permitted to consider specially the causes, conditions and consequences of systemic positions.

Calculations were performed with the help of «STATISTICA for Windows», v.6.0 and original programs developed in "Excel - 2000" in "Visual Basic for Application" integrated computer language. Group data was divided into numeral and classification ones; additional tables for deviations (abs. and %) of variables from baseline levels were calculated. Difference of significance was evaluated by χ2criterion and 2x2 tables – by adjusted Fisher test. Distribution parameters were evaluated by formulas as follows:

$$\mathbf{M} = \frac{1}{N} \sum\_{i=1}^{n} \mathbf{X} \mathbf{i}; \qquad \mathbf{S} = \sqrt{\frac{1}{N-1}} \sum\_{i=1}^{n} (\mathbf{X} \mathbf{i} - \mathbf{M}) 2 \mathbf{i}; \qquad \mathbf{m} = \mathbf{M} \frac{S}{\sqrt{N}}.$$

Consistency of numerical data with normal distribution law was assessed with help of Kolmogorov test. If the numerical data did not correspond to normal distribution law, nonparametric statistical methods were used - Wilcoxon rank test. Power and direction of correlation between the signs were determined by Pearson correlation coefficient **(r)** and by Spearmanrank correlation, if distribution of the baseline data was deviant. The values of these tests range from -1 to +1. The extreme values are observed in signs associated with linear functional relation. The significance of selected correlation coefficient is assessed by statistics value: r\* *n* − 2 / 1 2 − *r* =ta,f(1). The expression (1) permits to determine *a*, possibility of correlation coefficient difference from zero depending on *r* and sample size *n*. This, in turn, allows comparing the correlation of the same signs in the different sample sizes by possibility. Correlation power was assessed by a value of the correlation coefficient: strong, if r ≥0.7, moderate, if r = 0.3-0.7, weak, ifr<0.3. The differences between compared values were significant if p<0.5, it is consistent with criteria accepted in medical and biological researches.

Prognosis model is based on the regression analysis. Regression analysis was directed to the test of significance of one (dependent) variable Y from set of other ones, so called independent variables Xj = {X1, X2, … Xp}. The values of the prognostic parameter are defined according to the result of determination of the risk factors based on analysis of the clinical materials. The purpose of linear regression analysis in this study was to predict the values of the resulted variable Y according to the known values of physical parameters, EchoCG parameters and various additional features related to surgery specificity. The index of favorable surgery outcome was calculated as an arithmetic mean of risk factors.

As a result of these calculations, the model was developed. Based on this model the program was created in "Excel–2000»-« The Program of forecasting of probability of a favorable outcome of surgical treatment of aortal valve defects » (CERTIFICATE SPD RUzbDGU 01377) which helps to calculate a percentage of favorable surgery outcome and dynamics of LV ejection fraction after surgery with prognostic significance of 75-90%.
