Three-dimensional return map: a new tool for quantification of heart rate variability

Abstract

Background: Several methods are used to study heart rate variability, but they have limitations, which might be overcome by the use of a three-dimensional return map. Objectives: To evaluate the performance of three-dimensional return map-derived indices to detect (1) sympathetic and parasympathetic modulation to the sinus node and (2) autonomic dysfunction in diabetic patients. Methods: Six healthy subjects underwent partial and total pharmacological autonomic blockade in a protocol that incorporated vagal and sympathetic predominance. Twenty-two patients with type 2 diabetes mellitus and 12 normal controls participated in the subsequent validation experiment. Three-dimensional return maps were constructed by plotting RR n intervals versus the difference between adjacent RR intervals [(RR n+1 )−(RR n )] versus the number of counts, and four derived indices ( P 1, P 2, P 3, MN) were created for quantification. Results: Both indices P 1 and MN were significantly increased after sympathetic blockade with propranolol, while all indices except P 1 were modified after parasympathetic blockade ( P<0.05). During the validation experiments, P 1 and MN detected differences between normal controls, and diabetic patients with and without autonomic neuropathy. The overall accuracy of most three-dimensional indices to detect autonomic dysfunction, estimated by the area under the ROC curve, was significantly better than traditional time domain indices. Three-dimensional return map-derived indices also showed adequate reproducibility on two different recording days (intra-class correlation coefficients of 0.69 to 0.82; P<0.001). Conclusions: Three-dimensional return map-derived indices are reproducible, quantify parasympathetic as well as sympathetic modulation to the sinus node, and are capable of detecting autonomic dysfunction in diabetic patients.