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.
| Original language | English |
|---|---|
| Article number | 182 |
| Number of pages | 8 |
| Journal | Translational Psychiatry |
| Volume | 13 |
| DOIs | |
| Publication status | Published - 30 May 2023 |
Bibliographical note
Funding Information:We would like to thank GM Bloem, D Sloohof, G Arts, and E van den Kieboom for their work on (pre-)processing the physiological data. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (ERC-CoG-2015; No. 681466 to M Wichers). The Cortrium monitors were kindly provided by the iLab of the Department of Psychiatry of the University Medical Center Groningen (UMCG, http://www.ilab-psychiatry.nl ).
Keywords
- Humans
- Depression/drug therapy
- Antidepressive Agents/therapeutic use
- Electrocardiography
- Recurrence
Access to Document
- George_etal_TP_Predicting_Recurrence_of_VOR
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.