Бюллетень сибирской медицины (Apr 2020)

Decision rule for stratification of patients with chronic heart failure of functional class II and III

  • E. V. Samoilova,
  • M. A. Fatova,
  • D. R. Mindzaev,
  • I. V. Zhitareva,
  • C. N. Nasonova,
  • I. V. Zhirov,
  • C. N. Tereschenko,
  • A. A. Korotaeva

DOI
https://doi.org/10.20538/1682-0363-2020-1-101-107
Journal volume & issue
Vol. 19, no. 1
pp. 101 – 107

Abstract

Read online

The aim of the study was focused on the development of a decision rule for classifying patients as functional class (FC) II or III of chronic heart failure (CHF) by discriminant analysis with inflammatory markers.Materials and methods. The study included CHF patients (n = 61) of both sexes. According to symptom severity, they were assigned to FC II (n = 20) and III (n = 41). In addition to conventional clinical and biochemical parameters to evaluate a patient’s state, parameters characterizing inflammation (IL-6, soluble IL-6 receptor, sgp130) were used. Statistically significant differences were revealed with the use of Mann – Whitney U test, Student’s t-test, Pearson’s χ2 test and Fisher’s exact test. Discriminant analysis was employed to formulate the decision rule. Receiver Operating Characteristic (ROC) analysis was used to evaluate the quality of the developed diagnostic test. The results were considered statistically significant at p < 0.05.Results. Discriminant analysis included significantly different variables (age, brain natriuretic peptide, sgp130, CHF etiology, ischemic heart disease) and additional clinically important variables (diastolic and systolic arterial blood pressure (BP), IL-6). The decision rule for assigning patients to different CHF FC was developed. The optimum cut-off value was found with the use of the ROC curve with a sensitivity of 75.6% and specificity of 85%.Conclusion. The decision rule for assigning CHF patients to FC II or III was developed using discriminant analysis. In addition to conventional clinical parameters, the model included the ones reflecting inflammatory processes (IL-6 and sgp130). ROC analysis revealed high quality of the model.

Keywords