Dynamics of cystatin С and some indicators of carbohydrate metabolism in patients with metabolic syndrome if their complex therapy is added with intravenous laser blood irradiation

The present article analyzes effects of laser light irradiation at cystatin C concentration and some indicators of carbohydrate metabolism: basal blood glucose level, glucose tolerance test, HOMA-IR insulin resistance index in patients with metabolic syndrome (MS). Material and methods. 154 patients with MS were examined and treated (mean age- 36.5 ± 8.6 years). All patients were randomly divided into two groups: control group (32 patients) and studied group (122 patients). Patients in the control group had conventional treatment for metabolic syndrome disease: hypolipidemic, hypoglycemic, antihypertensive therapy. Patients of the studied group in addition to medicamentious therapy had a course of intravenous laser blood irradiation (ILBI) by ILBI – 405 (VLOK-405) technique. Laser «Matrix – VLOK» (Matrix Ltd, Russia) had wavelength 0.405 mkm and output power at the basic fiber tip 1–1.5 mW. Laser session lasted for 15 minutes in continuous mode; therapy course consisted of 10 daily sessions except weekends. Cystatin C level in the serum was assessed with the solid-phase enzyme immunoassay (EIA) test using «HumanVendor HumanCystatin C ELISA» reagent kit (BioVendor Ltd, Czech Republic). Glucose concentration in capillary blood was determined with the glucose oxidase method on an empty stomach and in 1 and 2 hours after the per oral glucose tolerance test. Immunoreactive insulin (IRI) level in the serum was assessed using immunoassay on an empty stomach. In all tests, PerkinElmer Victor 2 enzyme immunoassay analyzer with wavelength 450 nm was used. Results. It has been shown that low-level laser therapy added to medicamentous therapy in MS cases normalizes cystatin C concentration and leads to better dynamics in carbohydrate metabolism.

metabolic syndrome, intravenous laser blood irradiation, cystatin C, carbohydrate metabolism, obesity

1. Aleksandrova O.M. Effects of laser radiation at microcirculation, platelet aggregation and rheological properties of blood. Proceedings of the VI scientific conference of young scientists in medicine. Vladikavkaz, 2007: 6–9. [In Russ.].

2. Almazov V.A., Blagosklonnaya Ya.V., Shlyakhto E.V., Krasilnikova E.I. Role of abdominal obesity in pathogenesis of insulin resistance syndrome. Terapevtichesky archive. 1999; 10: 18–22. [In Russ.].

3. Belyakov N.А., Mazurova V.I. Obesity. St-Petersburg, Publishing House SPbMAPO, 2003: 520. [In Russ.].

4. Burduli N.M. Gireeva E. Yu. Changes in the level of homocysteine, blood lipid spectrum, lipid peroxidation and endothelial function in patients with stable exertion angina under low-level laser therapy. Lasernaya Medicina. 2010; 14 (2): 26–30. [In Russ.].

5. Gaidishev I.P. Modeling Stochastic and Deterministic Systems: AtteStat Software User Guide. Kurgan, 2015: 483. [In Russ.].

6. Gelman V.Ya. Medicine Informatics (practicum). 2000: 480. [In Russ.].

7. Gerasevich V.A. Computer for a physician. Self-teacher book. 2nd edition. St-Peresburg. БХВ-Petersburg. 2004: 512. [In Russ.].

8. Nikitin A.V., Chernaya L.S. Laser therapy in the complex treatment of metabolic syndrome in patients with bronchial asthma. Vestnik novikh medicinskikh technologii. 2011: 18 (2): 308–310. [In Russ.].

9. Oganov R.G., Perova N.V., Metelskaya V.A. Combination of metabolic syndrome components is associated with a high risk of atherosclerotic diseases. Cardiovascular therapy and prevention. 2004; 1: 56–59. [In Russ.].

10. Platonov A.E. Statistical analysis in medicine and biology: tasks, terminology, logic, computer techniques. Moscow, 2000: 51. [In Russ.].

11. Brehm A., Krssak M., Schmid A.I. et al. Diabetes. 2006; 55: 136–140.

12. Grubb A., Björk J., Lindström V. et al. A cystatin C-based formula without anthropometric variables estimates glomerular filtration rate better than creatinine clearance using the Cockcroft-Gault formula. Scand J Clin Lab Invest. 2005; 65 (2): 153–162.

13. Hotamisligil G.S. Nature. 2006; 444 (7121), 860–867.

14. Koenig W., Twardella D., Brenner H. et al. Plasma concentrations of cystatin C in patients with coronary heart disease and risk for secondary cardiovascular events: more than simply a marker of glomerular filtration rate. Clin. Chem. 2005; 51 (2): 321–327.

15. Rawlings N.D., Barrett A.J. Evolution of proteins of the cystatin superfamily. Journal of Molecular Evolution. 1990; 30: 60–71.

16. Hall A. et al. Structural basis for the biological specificity of cystatin C. Journal of Biological Chemistry.1995; 270: 5115–5121.

17. Reaven G.M. Вanting Lecture: role of insulin resistance in human disease. Diabetes. 1988; 37: 1595–1607.

18. Safar M.E. Hypertension and arterial wall / M.E. Safar, G.M. London, S. Laurent. High Blood Pressure. 1993; 2: 32–39.

19. Shlipak M.G., Sarnak M.J., Katz R. et al. Cystatin C and the risk of death and cardiovascular events among elderly persons. N. Engl. J. Med. 2005; 352: 2049–2060.

20. World Health Organization (WHO): Global Database on Body Mass Index. URL: http://www.assessmentpsychology.com/icbmi.htm.

21. World Health Organization (WHO) Consultation. Definition and diagnosis of diabetes and intermediate hyperglycaemia. 2006. http:// www.who.int/diabetes/publications.