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Growth differentiation factor 15 as a predictor of cardiorenal syndrome development

Session Poster session 2 Sunday 08:30 - 18:00

Speaker Associate Professor Irina Vishnevskaya

Event : Heart Failure 2015

  • Topic : cardiovascular disease in special populations
  • Sub-topic : Renal Failure and Cardiovascular Disease
  • Session type : Poster Session

Authors : IR Vyshnevska (Kharkiv,UA), MP Kopytsya (Kharkiv,UA), OV Petyunina (Kharkiv,UA), NV Tytarenko (Kharkiv,UA), YV Hilova (Kharkiv,UA), OI Lytvyn (Kharkiv,UA)

IR Vyshnevska1 , MP Kopytsya1 , OV Petyunina1 , NV Tytarenko1 , YV Hilova1 , OI Lytvyn1 , 1Government institution' L.T. Malaya Therapy National institute of the National academy of medical sci - Kharkiv - Ukraine ,

European Journal of Heart Failure Abstracts Supplement ( 2015 ) 17 ( Supplement 1 ), 189

Development of cardiorenal syndrome (CRS) significantly worsens the prognosis of patients with acute coronary syndrome (ACS). Stress-induced marker growth differentiation factor 15 (GDF 15), a member of the transforming growth factor-β cytokine superfamily is being actively studied.

Purpose: to determine prognostic significance of GDF 15 and other biochemical markers in prognosis of development of CRS in patients with ACS. Methods: 70 patients with different forms of ACS were included in the study, they were admitted to hospital from 2012 to 2013: 77% men and 23% women, mean age was 61, 8 ± 1, 3 years. Among them, 54% patients with Q-wave myocardial infarction (Q-wave MI), 20% - with non-Q-wave myocardial infarction (non-Q-wave MI), 26% - unstable angina (UA). All patients underwent a baseline investigation which includes: standard electrocardiography, echocardiography, angiography, determination of marker of myocardial necrosis - cardiac troponin T, marker of inflammation - C-reactive protein (C-RP)  GRACE score has been used for risk stratification. The glomerular filtration rate (GFR) was estimated by MDRD. In addition, the level of GDF 15 was determined during the first day of hospitalization via ELISA test.  

Results: The effect of 60 variables of clinical, instrumental and laboratorial status were assessed on formation of CRS in patients with different level of GFR. We calculated the GFR, the average was 57,4 ± 3,5 ml/min. In patients with Q-wave MI the average of GFR was 58,2 ± 3,7 ml/min, with non-Q-wave MI - 49,7 ± 3,5 ml/min, UA - 60,0 ± 3,2 ml/min. There was significant difference between level of GFR in patients with non-Q-wave MI and UA (p ≥ 0.02). For identification of the main risk factors for CRS, we have used logistic regression (LR): CRP (area under curve (AUC) 0.817; p < 0.0057; 95% confidence interval (CI): 0.592 - 1), GDF 15 (AUC 0.754; p < 0.017; 95% CI: 0.546-0.962) were main risk factors for predicting development of CRS. We have developed a prognostic model for predicting CRS formation (AUC 0.839; p < 0.0007). This model with 88% of sensitivity and 76% of specificity can predict development of CRS in patients with different level of GFR after ACS. 

Conclusions: The prognostic multifactor model was the best for predicting the risk formation of CRS and can be used in clinical practice to improve risk stratification in patients with ACS to prevent formation of CRS.

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