Application of HRV-CD for estimation of life expectancy in various clinical disorders

Background: Low heart rate variability (HRV) was found in various medical conditions including heart failure and acute myocardial infarction. Decreased HRV in these conditions predicted poor prognosis. Methods: HRV was estimated in 133 unselected inpatients with relevant clinical bedside conditions by non-linear analysis derived from chaos theory, which calculates the correlation dimension (CD) of the cardiac electrophysiologic system (HRV-CD). Results: Mean HRV-CD in the entire group was 3.75 ± 0.45. Heart failure, coronary artery disease, cardiac arrhythmia, low serum potassium, renal dysfunction, and diabetes mellitus were significantly associated with reduced HRV-CD compared to their counterparts [3.6 vs. 3.9 (P < .001), 3.65 vs. 3.87 (P = .005), 3.58 vs. 3.8 (P = .01), 3.38 vs. 3.81 (P = .02), 3.59 vs. 3.8 (P = .04), and 3.66 vs. 3.82 (P = .04), respectively]. Stepwise logistic regression showed heart failure to be the condition most significantly associated with low HRV-CD (odds ratio 4.2, 95% confidence interval 1.90-9.28, P < .001). In the entire group, decreased HRV-CD (≤ 3.75 vs. > 3.75) was associated with lower survival (P = .01). Mortality of diabetic patients with HRV-CD ≤ 3.75 exceeded the mortality in patients with HRV-CD > 3.75 (P = .02). Heart failure, renal dysfunction or age over 70 combined with HRV-CD ≤ 3.75 also appeared to be associated with augmented mortality. Conclusions: Diminished HRV-CD is associated with heart failure, coronary artery disease, cardiac arrhythmia, renal dysfunction, diabetes mellitus and low serum potassium. Among the latter, heart failure is most significantly associated with decreased HRV-CD. Decreased HRV-CD values, especially in diabetics, are also associated with lower survival.