Twenty-Four-Hour Heart Rate Is a Trait but Not State Marker for Depression in a Pilot Randomized Controlled Trial With a Single Infusion of Ketamine

Abstract

Background: Abnormalities of heart rate (HR) and its variability are characteristic of major depressive disorder (MDD). However, circadian rhythm is rarely taken into account when statistically exploring state or trait markers for depression.Methods: A 4-day electrocardiogram was recorded for 16 treatment-resistant patients with MDD and 16 age- and sex-matched controls before, and for the patient group only, after a single treatment with the rapid-acting antidepressant ketamine or placebo (clinical trial registration available on https://www.clinicaltrialsregister.eu/ with EUDRACT number 2016-001715-21). Circadian rhythm differences of HR and the root mean square of successive differences (RMSSD) were compared between groups and were explored for classification purposes. Baseline HR/RMSSD were tested as predictors for treatment response, and physiological measures were assessed as state markers.Results: Patients showed higher HR and lower RMSSD alongside marked reductions in HR amplitude and RMSSD variation throughout the day. Excellent classification accuracy was achieved using HR during the night, particularly between 2 and 3 a.m. (90.6%). A positive association between baseline HR and treatment response (r = 0.55, p = 0.046) pointed toward better treatment outcome in patients with higher HR. Heart rate also decreased significantly following treatment but was not associated with improved mood after a single infusion of ketamine.Limitations: Our study had a limited sample size, and patients were treated with concomitant antidepressant medication.Conclusion: Patients with depression show a markedly reduced amplitude for HR and dysregulated RMSSD fluctuation. Higher HR and lower RMSSD in depression remain intact throughout a 24-h day, with the highest classification accuracy during the night. Baseline HR levels show potential for treatment response prediction but did not show potential as state markers in this study.Clinical trial registration: EUDRACT number 2016-001715-21.

The cumulative effect of chronic stress and depressive symptoms affects heart rate in a working population

“…The mean HR(V) and activity levels were calculated in windows of 5 min with 4 min of overlap, analog to Schiweck et al ( 4 ) and Smets et al ( 36 ), following the minimum window length required to calculate HRV features. The activity level of the participants was calculated as the standard deviation of the magnitude of acceleration (Std Acc) as derived from the accelerometer of the ECG patch.…”

“…Patients with Major Depressive Disorder (MDD) show higher baseline levels of heart rate (HR) and altered heart rate variability (HRV) [e.g., lower Standard Deviation of Normal-to-Normal Intervals (SDNN), Root Mean Square of Successive Differences (RMSSD), low-frequency and high frequency (HF) HRV] (1-3). These baseline differences are paired with blunted reactivity during exposure to acute and repeated psychological stress (2)(3)(4)(5). Furthermore, differences of HR and HRV at baseline extend to abnormalities of HR circadian rhythm in severe depression (6,7).…”

“…A circadian rhythm is an oscillation of a process over 24 h. HR, for example, rises strongly in the morning, reaches a peak before noon, decreases again and reaches another peak in the afternoon, after which it keeps on lowering during the night until the next morning ( 8 ). Abnormalities within this rhythm may be used to discriminate between cases and controls ( 4 , 9 ). Indeed, it is well known that patients with MDD show altered circadian rhythms and diurnal mood variation ( 10 ).…”

Exhausted Heart Rate Responses to Repeated Psychological Stress in Women With Major Depressive Disorder

“…The choice to use the timeslot between 12.00 and 18.30 was based on our pilot study on diurnal variations in HR in patients with MDD and healthy controls, where a prominent increase in basal HR occurred during the morning, whereas the most significant decrease occurred later in the evening. The period-between 12.00 and 18.30 yielded a plateau ideal for behavioral analyses ( 48 ). Participants were in a seated position in a room with a controlled temperature of 22°C.…”

Will digital technology address the challenges of drug development in psychiatry?

“…Many studies have reported that it was possible to dis­tinguish between patients with mental disorders and healthy volunteers 4 , or detect early sign of relapse 5 with a relatively high degree of accuracy from these data, but there is still large room for improvement. Even when a pathological feature can be identified, it is often unclear whether it is a state or a trait marker 6 .…”