A novel complex model of hemodialysis adequacy: predictive value and relationship with malnutrition-inflammation score

Target dialysis dose to ensure the best patient outcome is still a matter of debate. Traditional models have a number of limitations and do not comprehensively reflect all factors involved. In this study we present a new complex model of dialysis adequacy, the hemodialysis adequacy score (HAS), and evaluate its prognostic value, as well as its relationship with the malnutrition-inflammation score (MIS). The components of HAS included paradigms of the 6 major factors known to influence the outcome of hemodialysis (HD) patients: the modified Karnofsky index (KI), the Charlson comorbidity index (CCI), Kt/V and URR measures of dialysis dose, body mass index (BMI) and serum albumin level, serum levels of hemoglobin and ferritin, intact parathyroid hormone (iPTH) and calcium-phosphorus solubility product. The score was evaluated in a 24-month prospective study on 147 HD patients. Odds ratio analysis showed that hospitalized patients had twice the chance to have HAS >13 compared to those who were not hospitalized during the study period (OR=2.152, CI 95% (1.0024-4.619). Mortality rate was significantly higher in patients with a HAS >13 at the 12-month follow-up (χ2=16.416, p 13 had significantly higher probability of death (log-rank Cox-Mantel=17.920, df=1, p <0.00023). The HAS directly and significantly correlated with the MIS at all measurements (p <0.0001). Results confirmed that the HAS is a useful tool to assess dialysis adequacy with a good prognostic value. The cutoff level for the HAS at 13 points was associated with an unfavorable outcome. DOI: 10.2298/ABS160229088V Received: February 29, 2016; Revised: March 12, 2016; Accepted: March, 13, 2016; Published online: October 10, 2016 How to cite this article: Vlatkovic V, Trbojevic-Stankovic J, Nesic D, Stojimirovic B. A novel complex model of hemodialysis adequacy: predictive value and relationship with malnutrition-inflammation score. Arch Biol Sci. 2017;69(1):129-37.