Congestive heart failure (CHF) is a signi cant healthcare problem, and is associated with high levels of morbidity and mortality. The majority of patients have poor quality of life in spite of the modern evidence-based treatment. Malnutrition is more common in patients with HF, especially at the severe stage of HF, and is associated with the risk of complications and mortality. Consequently, evaluation of malnutrition in patients with HF, monitoring of patients in this regard, and identifying the right assessment tools are the basis for developing of an effective nutritional strategy that can have a signi cant impact on the treatment and management of such patients.

Our aim was to study the prevalence of di erent markers of malnutrition, their association with nutrient indices, and their correlation with CHF in Georgian population.

The total of 96 patients relevant to the research objective (43 female and 53 male with average age 69.85) were enrolled in the study. Nutritional screening was performed using the GNRI, which was calculated as follows: GNRI=14.89× serum albumin (g/dL) +41.7*body weight÷ideal body weight. Ideal body weight=22*square of height in meters and PNI was calculated as follows: PNI=10* serum albumin (g/dL) +0.005*total lymphocyte (count per mm3) and The Controlling Nutritional Status (CONUT) score was calculated by serum albumin score plus total cholesterol score and total lymphocyte score. Peripheral venous blood was test- ed for acute phase reactant (hsCRP, Interleukin-6, brinogen, acid glycoprotein) and for protein-energy malnutrition (prealbumin, al- bumin, lymphocytes, lipid pro le and transferrin).

By examining the correlation between the CONUT, GNRI and PNI indices, a signi cant negative correlation was found between CONUT and PNI. We quantitatively compared results obtained us- ing CONUT, GNRI and PNI scale risk groups, as the primary pic- ture suggested it in our study group (ambulatory, quite compensated CHF). CONUT and PNI represent best option.

Prealbumin, lipid pro le data, transferrin decreases with in- creasing risk for CONUT and PNI, with Interleukin-6 increasing on both calculators. Changes in other data are not correlated.