Predictors of Kidney Damage in Patients with Metabolic Syndrome
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Supplementary Files

Correlation between hydrogen sulfid and microalbuminuria
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Keywords

metabolic syndrome
kidney damage
hydrogen sulfide
microalbuminuria

How to Cite

Kutsyk, D., & Sklyarov, E. (2017). Predictors of Kidney Damage in Patients with Metabolic Syndrome. Galician Medical Journal, 24(2). https://doi.org/10.21802/gmj.2017.2.15

Abstract

Metabolic syndrome is an epidemic of XXI century. Each of the components of metabolic syndrome (arterial hypertension, hyperglycemia or dyslipidemia) can be a risk factor for chronic kidney disease. However, it remains unknown what plays a key role in the progression of the disease.

The objective of the research was to identify early detectors of kidney damage in patients with metabolic syndrome.

Materials and methods. The study involved 70 patients with metabolic syndrome. In addition to standard examination methods, markers of endothelial disfunction (hydrogen sulfide and nitrogen monooxide) were measured in venous blood samples and the urine was tested for microalbuminuria. All the patients were divided into 3 groups according to the degree of albuminuria: normoalbuminuria, microalbuminuria and macroalbuminuria. To compare the indices between the groups, the Student’s t-test was used; to determine the relationship between the individual values, the Pearson correlation coefficient (r) was applied.

Results. The indicator of systolic blood pressure was higher in patients with microalbuminuria compared to those with normoalbuminuria (163.4±14.4 mmHg, versus 153.0±17.7 mmHg; p<0.01). Hydrogen sulfide level was higher in patients with normoalbuminuria (66.8±7.2 µmol). There was a moderate positive correlation between systolic blood pressure and microalbuminuria (r=0.3804; p<0.01) and a moderate negative correlation between hydrogen sulfide and microalbuminuria (r=0.3404; p<0.01).

Conclusions. We revealed a decrease in hydrogen sulfide level to 57.4±7.9 µmol in patients with metabolic syndrome. This may be an early predictor of kidney damage.

 

https://doi.org/10.21802/gmj.2017.2.15
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