Diminution of Heart Rate Variability in Bipolar Depression (original) (raw)
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A literature review of heart rate variability in depressive and bipolar disorders
The Australian and New Zealand journal of psychiatry, 2016
Autonomic nervous system dysfunction has the potential to adversely impact general medical health and is known to exist in a number of psychiatric disorders. It reflects alterations in the function of several regions of the central nervous system. Measurement of heart rate variability provides a non-invasive tool for studying autonomic function. While the literature relating to the technical process of heart rate variability and aspects of depressive disorders has been reviewed in the past, research relating to both depressive and bipolar disorders has not been comprehensively reviewed. This paper critically considers the published research in heart rate variability in both depressive and bipolar affective disorders. A literature search using Medline, EMBASE, PsycINFO, ProQuest Psychology and references included in published literature was conducted using the following keywords: 'heart rate variability and autonomic, combined with depression, depressive disorder, bipolar, mania ...
Journal of Affective Disorders, 2007
Depression is associated with greater cardiac morbidity and mortality. One of the contributory factors for this may be altered cardiac autonomic activity in depression. However, cardiac autonomic involvement in depression remains controversial because of methodological issues. In this study, alteration of cardiac autonomic functions was studied in drug-naive patients with major depression without co-morbidity. Heart rate variability, a sensitive measure of neurocardiac autonomic regulation was used in addition to conventional methods of measuring cardiac autonomic functions.We recruited 40 patients suffering from major depression, diagnosed based on DSM-IV-TR criteria. Their cardiac autonomic functions were measured using both conventional and heart rate variability measures. These were compared with those of age- and gender-matched healthy controls.Patients with major depression showed significantly lesser Valsalva ratio, maximum/minimum ratio and greater sympathovagal balance than healthy controls indicating decreased parasympathetic and increased sympathetic activity.Depression is associated with alteration of cardiac autonomic tone towards decreased parasympathetic activity and an increased sympathetic activity. It is possible that a common neurobiological dysfunction contributes to both depression and cardiac autonomic changes in the illness.
Heart Rate Variability Predicts Treatment Outcome in Major Depression
Journal of Psychiatry and Brain Science, 2017
Aims: Autonomic nervous system (ANS) dysregulation is associated with various symptoms of depressive disorder. The beat-to-beat pattern of heart rate (Heart Rate Variability) (HRV) provides a noninvasive portal to ANS function through the quantification of periodic heart rate patterns. In this study we quantified two components of HRV: Respiratory Sinus Arrhythmia (RSA), and Low Frequency HRV (LF-HRV). Both of these components have been extensively reported in studies of depression and have been at least partially associated with reduction in vagal nerve tone. We quantified RSA and LF-HRV in patients with Major Depressive Disorder (MDD) as measures of ANS regulation seeking to establish the utility of components of HRV as potential diagnostic and prognostic biomarkers for treatment outcome. Methods: Sixty-six MDD patients were enrolled. In two separate and consecutively run studies they received either Escitalopram or Quetiapine fumarate ER over 12 weeks. Forty-one patients completed the studies. RSA and LF-HRV were assessed at pretreatment and end of study. Thirty-six healthy subjects served as controls. RSA and LF-HRV were quantified using an algorithm that incorporates time and frequency domains to address the non-stationarity of the beat-to-beat heart rate pattern. Results: No significant differences in baseline RSA or LF-HRV were found between MDD and healthy controls. However, baseline RSA and LF-HRV were significantly higher in treatment responders (lnRSA = http://jpbs.qingres.com
Heart rate variability and treatment outcome in major depression: A pilot study
International Journal of Psychophysiology, 2014
Major depressive disorder Very low frequency Escitalopram Yoga Selective serotonin reuptake inhibitor Heart rate variability Variations in heart rate variability (HRV) have been associated with major depressive disorder (MDD), but the relationship of baseline HRV to treatment outcome in MDD is unclear. We conducted a pilot study to examine associations between resting baseline HRV and MDD treatment outcome. We retrospectively tested several parameters of HRV in an MDD treatment study with escitalopram (ESC, N = 26) to generate a model of how baseline HRV related to treatment outcome, and cross-validated the model in a separate trial of MDD treatment with Iyengar yoga (IY, N = 16). Lower relative power of very low frequency (rVLF) HRV at baseline predicted improvement in depressive symptoms when adjusted for age and gender (R 2 N .43 and p b 0.05 for both trials). Although vagal parasympathetic measures were correlated with antidepressant treatment outcome, their predictive power was not significant after adjusting for age and gender. In conclusion, baseline resting rVLF was associated with depression treatment outcome in two independent MDD treatment studies. These results should be interpreted with caution due to limited sample size, but a strength of this study is its validation of the rVLF predictor in an independent sample. rVLF merits prospective confirmation as a candidate biomarker.
When heart beats differently in depression: a review of HRV measures
arXiv (Cornell University), 2021
Background and Objective: The connection between depression and autonomous nervous system (ANS) is well documented in scientific literature. Heart rate variability (HRV) is a rich source of information for studying the dynamics of this relation. Disturbed heart dynamics in depression seriously increases mortality risk. Technical sciences help improve early detection and monitoring and offer more accurate management of treatment. Based on advances in computational power, information theory, complex systems dynamics, and nonlinear analysis applied to physiological complexity, we can now turn to novel biomarkers extracted from electrophysiological signals. This work is a cross-sectional analysis with methodological commentary of application of nonlinear measures of HRV related to depression. Methods: We systematically searched online for papers exploring the connection of depression and HRV, using both conventional and nonlinear analysis. We scrutinized chosen publications and methodologically analyzed and compared them. Results: Sixty-seven publications on the connection of HRV measures and depression meeting our inclusion criteria are selected. The effectiveness of the applied methods of electrocardiogram (ECG) analysis are compared and discussed in the light of detection and prevention of depression-related cardiac diseases. Conclusions: It is clear that aberrated ANS dynamics can be detected via ECG analysis, where nonlinear measures show to be more sensitive and accurate than standard time and spectral ones. With the portable ECG devices and cloud-based telehealth applications, monitoring of outpatients could be done anytime anywhere. We appeal for early screening for cardiovascular abnormalities in depressive patients to prevent possible deleterious events.
Cardiac autonomic dysfunction assessed by heart rate variability in major depression
International Journal of Medical Science and Public Health, 2017
Major depressive disorder (MDD) is reported to be associated with increased cardiovascular morbidity and mortality. [1] This has been hypothesized to be because of alterations in the autonomic nervous system among depressed persons. Such alterations are believed to reduce heart rate variability (HRV), a well-known prognostic risk factor for cardiovascular disease and mortality. [2]
Journal of Affective Disorders, 2004
Background: The link between depression and autonomic dysfunction has attracted more attention since epidemiological studies have revealed that depressed patients have an augmented risk of cardiovascular morbidity and mortality. Former studies of autonomic dysfunction in major depression have shown inconclusive results. Aims: To further elucidate the effect of depression and medication on autonomic function, 18 patients and 18 matched control subjects were comprehensively assessed once medicated and once non-medicated as well as after full clinical recovery. Methods: Cardiac autonomic function was evaluated by measuring heart rate variability (HRV) parameters, and central autonomic tone was investigated by obtaining parameters of the pupillary light reflex (PLR). Results: Acutely depressed patients who had not taken antidepressant medication for 8 weeks prior to the investigation differed significantly neither in heart rate parameters nor in parameters of the PLR from their controls. However, after 2 days of antidepressant treatment (SSRI and NaSSRI), parameters of heart rate analysis and PLR (except relative amplitude) changed significantly and remained significantly different after clinical recovery. Limitations: The study needs to be repeated using larger patient groups. Long-term studies are absolutely essential. Conclusion: The state of depression did not influence autonomic parameters significantly. In fact, treatment influenced autonomic function far more than the disease itself. Other branches of the autonomic nervous system (ANS), as well as new techniques should be applied to elucidate whether small changes in autonomic function exist. This might clarify whether disease or treatment might influence cardiac mortality in depression. D
Heartbeat Complexity Modulation in Bipolar Disorder during Daytime and Nighttime
Scientific Reports
This study reports on the complexity modulation of heartbeat dynamics in patients affected by bipolar disorder. In particular, a multiscale entropy analysis was applied to the R-R interval series, that were derived from electrocardiographic (ECG) signals for a group of nineteen subjects comprised of eight patients and eleven healthy control subjects. They were monitored using a textile-based sensorized t-shirt during the day and overnight for a total of 47 diurnal and 27 nocturnal recordings. Patients showed three different mood states: depression, hypomania and euthymia. Results show a clear loss of complexity during depressive and hypomanic states as compared to euthymic and healthy control states. In addition, we observed that a more significant complexity modulation among healthy and pathological mood states occurs during the night. These findings suggest that bipolar disorder is associated with an enhanced sleep-related dysregulation of the Autonomic Nervous System (ANS) activity, and that heartbeat complex dynamics may serve as a viable marker of pathological conditions in mental health. Bipolar disorder is recognized as a chronic illness with a lifetime prevalence of 1-3% and is considered one of the world's ten most disabling conditions 1,2. This disease is characterized by pathological mood changes, being a significant source of disquietude, suffering, and disability, often ending in suicide. Pathological mood states in bipolar disorder include depression, mania or hypomania, mixed state, and euthymia. More specifically, depressive states are characterized by sadness, anxiety, feelings of guilt, loss of interest in activities and suicidal thoughts in some cases. Mania is characterized by a pathologically-elevated mood, with extreme happiness and irritability 3 , whereas hypomania is a less severe form of mania. During a mixed state, patients experience both manic and depressive sympthoms at the same time. The euthymic state is characterized by a normal affective balance 2. Given the high cost of treatment and repercussions for patients, relatives and caregivers, bipolar disorder is perceived as a major social problem 4. Despite its prevalence and high cost of treatment 5 (also due to the high number of mis-diagnosis and additional indirect costs, e.g., those due to work loss 6), diagnosis of bipolar disorder is still ill-defined. Likewise, for the great majority of mental disorders, diagnosis relies on the clinician's expertise and background, supported only by scores gathered from psychometric scales and structured interviews 2. Furthermore, patients with mood disorders might experience a very heterogeneous pattern of symptoms related to the phenomenology, severity, number, and duration of the symptomatic episodes, as well as the time interval between them. The diagnosis of bipolar disorder is based on clinical observation of a patient's behavioral mood episodes, according to standardized criteria described in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) 7 and the tenth edition of the International Classification of Diseases (ICD-10) 8. These criteria differentiate the diagnosis according to the presence, sequence and history of critical mood episodes. According to DSM-V classification, the diagnosis of depressive episodes is made if the patient exhibits five out of nine possible symptoms. In line with this approach, a patient who has had only four symptoms of depressive episodes is considered remitted, although partially remitted. Similar cutoffs are applied for the diagnosis of other types