Predicting recurrence of depression using cardiac complexity in individuals tapering antidepressants

Abstract

It is currently unknown whether the complexity and variability of cardiac dynamics predicts future depression and whether within-subject change herein precedes the recurrence of depression. We tested this in an innovative repeated single-subject study in individuals who had a history of depression and were tapering their antidepressants. In 50 individuals, electrocardiogram (ECG) derived Interbeat-interval (IBI) time-series data were collected for 5 min every morning and evening, for 4 months. Usable data were obtained from 14 participants who experienced a transition (i.e., a clinically significant increase in depressive symptoms) and 14 who did not. The mean, standard deviation, Higuchi dimension and multiscale entropy, calculated from IBIs, were examined for time trends. These quantifiers were also averaged over a baseline period and compared between the groups. No consistent trends were observed in any quantifier before increases in depressive symptoms within individuals. The entropy baseline levels significantly differed between the two groups (morning: P value < 0.001, Cohen's d = -2.185; evening: P value < 0.001, Cohen's d = -1.797) and predicted the recurrence of depressive symptoms, in the current sample. Moreover, higher mean IBIs and Higuchi dimensions were observed in individuals who experienced transitions. While we found little evidence to support the existence of within- individual warning signals in IBI time-series data preceding an upcoming depressive transition, our results indicate that individuals who taper antidepressants and showed lower entropy of cardiac dynamics exhibited a higher chance of recurrence of depression. Hence, entropy could be a potential digital phenotype for assessing the risk of recurrence of depression in the short term while tapering antidepressants.

Fig. 1. Flowchart describing the patient inclusion for the present study.

At the end of various inclusion and exlusion criteria, 14 individuals with a transition and 14 individuals without were analyzed in the present study.

Fig. 2. Violin plots showing the differences in the distributions of the person-averaged quantifiers between individuals who experienced a transition and those who did not.

The panels show a mean, b standard deviation, c Higuchi dimension, and d Multiscale entropy. The distribution for individuals who experienced a transition are in orange and those who did not are in green. The circles represent the quantifier values for each individual, scattered randomly along the x-axis. The quantifiers were averaged over the baseline periods.

Fig. 3. Scatter plot showing the entropy values for the morning and evening for each individual.

Red crosses represent individuals who experienced a transition, and the blue squares represent individuals who did not. The error bars represent the standard error.