Mechanisms and pathogenesis of cardiovascular complications of cancers in relation to circadian rhythms

Background: Damage to circadian system of our body may be associated with disturbances in body rhythms which may predispose to carcinogenesis. Quantitative assessment and diagnosis of desynchronization of circadian rhythms may be performed for scientific purposes, as there are no simple methods for use in daily clinical practice. The aim of our work is to develop simple methods for the diagnosis of desynchronization in body rhythms. Subjects and Methods: This study included two groups; the first group included 51 age-and sex-matched subjects from among students and staff of the University for comparison. The second group comprised 24 patients with cancer: 7 patients had breast cancer and the rest had lung cancer. The identification of desynchronization of body rhythms was carried out using correlation-regression analysis. Results: In group 1, the regression coefficients are positive and statistically significant for all parameters, and the average value in the parameters for HR - SBP and HR - DBP significantly exceeds the average in group 2. The average value of the regression coefficient HR-SBP is 0.369 ± 0.194, P < 0.05; HR-DBP is 0.503 ± 0.22, P< 0.05, also significant. In group 2, all regression coefficients are positive in relation to DBP - SBP. However, in the pair HR - SBP, the part of negative regression coefficients is 12.5%, whereas in the pair HR - DBP it is 8%. In group 2, there is significant decrease in unidirectional characteristics of changes in relations between HR - SBP and HR - DBP. However, the appearance of negative regression coefficients indicates the coherence reduction and shows the emergence of diversity in the occurrence of combined physiological functions. The average value of the regression coefficient for HR-SBP is 0.242 ± 0.224 P < 0.05, and for HR-DBP it is 0.265 ± 0.339, P < 0.05.The substantial alterations identified in comparison of group 1 for all studied relations, apparently indicate various degrees of desynchronization in body rhythms against the background of severe somatic pathology in group 2 patients. Conclusions: The results revealed that identification and quantification of desynchronization is possible based on hemodynamic parameters by regression analysis. © Nova Science Publishers, Inc