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Sammito S, Thielmann B, Böckelmann I. Update: factors influencing heart rate variability-a narrative review. Front Physiol 2024; 15:1430458. [PMID: 39165281 PMCID: PMC11333334 DOI: 10.3389/fphys.2024.1430458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Accepted: 07/22/2024] [Indexed: 08/22/2024] Open
Abstract
Objective Heart rate variability (HRV) is an important non-invasive marker for the assessment of an organism's autonomic physiological regulatory pathways. Lower HRV has been shown to correlate with increased mortality. HRV is influenced by various factors or diseases. The aim of this narrative review is to describe the current state of knowledge on factors influencing HRV and their significance for interpretation. Methods The narrative review only included reviews, meta-analyses, and cohort studies which were published until 2021. HRV confounders were grouped into four categories (non-influenceable physiological factors, diseases, influenceable lifestyle factors and external factors). Results The review found that HRV was decreased not only in non-influenceable physiological factors (e.g., age, gender, ethnicity) but also in connection with various number of acute and chronic diseases (e.g., psychiatric diseases, myocardial infarction, heart failure), influenceable lifestyle factors (e.g., alcohol abuse, overweight, physical activity), and external factors (e.g., heat, noise, shift work, harmful- and hazardous substances). Conclusion In order to improve the quality of HRV studies and to ensure accurate interpretation, it is recommended that confounders be taken into account in future diagnostic measurements or measurements in the workplace (e.g., as part of health promotion measures) in order to counteract data bias.
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Affiliation(s)
- Stefan Sammito
- German Air Force Centre of Aerospace Medicine, Cologne, Germany
- Occupational Medicine, Faculty of Medicine, Otto von Guericke University, Magdeburg, Germany
| | - Beatrice Thielmann
- Occupational Medicine, Faculty of Medicine, Otto von Guericke University, Magdeburg, Germany
| | - Irina Böckelmann
- Occupational Medicine, Faculty of Medicine, Otto von Guericke University, Magdeburg, Germany
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Anmella G, Corponi F, Li BM, Mas A, Garriga M, Sanabra M, Pacchiarotti I, Valentí M, Grande I, Benabarre A, Giménez-Palomo A, Agasi I, Bastidas A, Cavero M, Bioque M, García-Rizo C, Madero S, Arbelo N, Murru A, Amoretti S, Martínez-Aran A, Ruiz V, Rivas Y, Fico G, De Prisco M, Oliva V, Solanes A, Radua J, Samalin L, Young AH, Vergari A, Vieta E, Hidalgo-Mazzei D. Identifying digital biomarkers of illness activity and treatment response in bipolar disorder with a novel wearable device (TIMEBASE): protocol for a pragmatic observational clinical study. BJPsych Open 2024; 10:e137. [PMID: 39086306 DOI: 10.1192/bjo.2024.716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND Bipolar disorder is highly prevalent and consists of biphasic recurrent mood episodes of mania and depression, which translate into altered mood, sleep and activity alongside their physiological expressions. AIMS The IdenTifying dIgital bioMarkers of illnEss activity and treatment response in BipolAr diSordEr with a novel wearable device (TIMEBASE) project aims to identify digital biomarkers of illness activity and treatment response in bipolar disorder. METHOD We designed a longitudinal observational study including 84 individuals. Group A comprises people with acute episode of mania (n = 12), depression (n = 12 with bipolar disorder and n = 12 with major depressive disorder (MDD)) and bipolar disorder with mixed features (n = 12). Physiological data will be recorded during 48 h with a research-grade wearable (Empatica E4) across four consecutive time points (acute, response, remission and episode recovery). Group B comprises 12 people with euthymic bipolar disorder and 12 with MDD, and group C comprises 12 healthy controls who will be recorded cross-sectionally. Psychopathological symptoms, disease severity, functioning and physical activity will be assessed with standardised psychometric scales. Physiological data will include acceleration, temperature, blood volume pulse, heart rate and electrodermal activity. Machine learning models will be developed to link physiological data to illness activity and treatment response. Generalisation performance will be tested in data from unseen patients. RESULTS Recruitment is ongoing. CONCLUSIONS This project should contribute to understanding the pathophysiology of affective disorders. The potential digital biomarkers of illness activity and treatment response in bipolar disorder could be implemented in a real-world clinical setting for clinical monitoring and identification of prodromal symptoms. This would allow early intervention and prevention of affective relapses, as well as personalisation of treatment.
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Affiliation(s)
- Gerard Anmella
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | | | - Bryan M Li
- School of Informatics, University of Edinburgh, UK
| | - Ariadna Mas
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Marina Garriga
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Miriam Sanabra
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Isabella Pacchiarotti
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Marc Valentí
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Iria Grande
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Antoni Benabarre
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Anna Giménez-Palomo
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Isabel Agasi
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain
| | - Anna Bastidas
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Myriam Cavero
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Miquel Bioque
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; Institute of Neurosciences (UBNeuro), University of Barcelona, Spain; and Barcelona Clinic Schizophrenia Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Clemente García-Rizo
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; Institute of Neurosciences (UBNeuro), University of Barcelona, Spain; and Barcelona Clinic Schizophrenia Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Santiago Madero
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; Institute of Neurosciences (UBNeuro), University of Barcelona, Spain; and Barcelona Clinic Schizophrenia Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Néstor Arbelo
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; Institute of Neurosciences (UBNeuro), University of Barcelona, Spain; and Barcelona Clinic Schizophrenia Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Andrea Murru
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Silvia Amoretti
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Anabel Martínez-Aran
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Victoria Ruiz
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain
| | - Yudit Rivas
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain
| | - Giovanna Fico
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Michele De Prisco
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Vincenzo Oliva
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Aleix Solanes
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; Institute of Neurosciences (UBNeuro), University of Barcelona, Spain; and Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; Institute of Neurosciences (UBNeuro), University of Barcelona, Spain; Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Early Psychosis: Interventions & Clinical Detection (EPIC) Laboratory, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; and Center for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Sweden
| | - Ludovic Samalin
- Institut Pascal (UMR 6602), Department of Psychiatry, CHU Clermont-Ferrand, University of Clermont Auvergne, CNRS, Clermont Auvergne INP, France; and Association Française de Psychiatrie Biologique et Neuropsychopharmacologie (AFPBN), Saint Germain en Laye, France
| | - Allan H Young
- Centre for Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK
| | | | - Eduard Vieta
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
| | - Diego Hidalgo-Mazzei
- Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain
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3
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Pinto SM, Wright B, Annaswamy S, Nwana O, Nguyen M, Wilmoth K, Moralez G. Heart rate variability (HRV) after traumatic brain injury (TBI): a scoping review. Brain Inj 2024; 38:585-606. [PMID: 38590161 DOI: 10.1080/02699052.2024.2328310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 03/05/2024] [Indexed: 04/10/2024]
Abstract
BACKGROUND Heart rate variability (HRV), defined as the variability between successive heart beats, is a noninvasive measure of autonomic nervous system (ANS) function, which may be altered following traumatic brain injury (TBI). This scoping review summarizes the existing literature regarding changes in HRV after TBI as well as the association between measures of HRV and outcomes following TBI. METHODS A literature search for articles assessing 'heart rate variability' and 'brain injury' or 'concussion' was completed. Articles were included if HRV was measured in human subjects with TBI or concussion. Review articles, protocol papers, and studies including non-traumatic injuries were excluded. RESULTS Sixty-three articles were included in this review. Varied methods were used to measure HRV in the different studies. Forty articles included information about differences in HRV measures after TBI and/or longitudinal changes after TBI. Fifteen studies assessed HRV and symptoms following TBI, and 15 studies assessed HRV and either functional or cognitive outcomes after TBI. CONCLUSIONS HRV has been studied in the context of mortality, clinical symptoms, and medical, functional, or cognitive outcomes following TBI. Methods used to measure HRV have varied amongst the different studies, which may impact findings, standardized protocols are needed for future research.
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Affiliation(s)
- Shanti M Pinto
- Department of Physical Medicine and Rehabilitation, O'Donnell Brain Institute Clinical Neuroscience Scholar, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Brittany Wright
- Department of Physical Medicine and Rehabilitation, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Shreyas Annaswamy
- National Institute of Allergy and Infectious Diseases (NIAID), Bethesda, Maryland, USA
| | - Ola Nwana
- Department of Neurology, Houston Methodist Neuroscience Center Team at Willowbrook, Houston, Texas, USA
| | - Michael Nguyen
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, Houston, Texas, USA
- Brain Injury and Stroke Medicine, TIRR Memorial Hermann, Houston, Texas, USA
| | - Kristin Wilmoth
- Department of Physical Medicine and Rehabilitation, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Gilbert Moralez
- Department of Applied Clinical Research, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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Książek K, Masarczyk W, Głomb P, Romaszewski M, Stokłosa I, Ścisło P, Dębski P, Pudlo R, Buza K, Gorczyca P, Piegza M. Assessment of symptom severity in psychotic disorder patients based on heart rate variability and accelerometer mobility data. Comput Biol Med 2024; 176:108544. [PMID: 38723395 DOI: 10.1016/j.compbiomed.2024.108544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 04/22/2024] [Accepted: 04/28/2024] [Indexed: 05/31/2024]
Abstract
BACKGROUND Advancement in mental health care requires easily accessible, efficient diagnostic and treatment assessment tools. Viable biomarkers could enable objectification and automation of the diagnostic and treatment process, currently dependent on a psychiatric interview. Available wearable technology and computational methods make it possible to incorporate heart rate variability (HRV), an indicator of autonomic nervous system (ANS) activity, into potential diagnostic and treatment assessment frameworks as a biomarker of disease severity in mental disorders, including schizophrenia and bipolar disorder (BD). METHOD We used a commercially available electrocardiography (ECG) chest strap with a built-in accelerometer, i.e. Polar H10, to record R-R intervals and physical activity of 30 hospitalized schizophrenia or BD patients and 30 control participants through ca. 1.5-2 h time periods. We validated a novel approach to data acquisition based on a flexible, patient-friendly and cost-effective setting. We analyzed the relationship between HRV and the Positive and Negative Syndrome Scale (PANSS) test scores, as well as the HRV and mobility coefficient. We also proposed a method of rest period selection based on R-R intervals and mobility data. The source code for reproducing all experiments is available on GitHub, while the dataset is published on Zenodo. RESULTS Mean HRV values were lower in the patient compared to the control group and negatively correlated with the results of the PANSS general subcategory. For the control group, we also discovered the inversely proportional dependency between the mobility coefficient, based on accelerometer data, and HRV. This relationship was less pronounced for the treatment group. CONCLUSIONS HRV value itself, as well as the relationship between HRV and mobility, may be promising biomarkers in disease diagnostics. These findings can be used to develop a flexible monitoring system for symptom severity assessment.
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Affiliation(s)
- Kamil Książek
- Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, Gliwice, 44-100, Poland.
| | - Wilhelm Masarczyk
- Department of Psychiatry, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Pyskowicka 49, Tarnowskie Góry, 42-612, Poland
| | - Przemysław Głomb
- Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, Gliwice, 44-100, Poland
| | - Michał Romaszewski
- Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, Gliwice, 44-100, Poland
| | - Iga Stokłosa
- Department of Psychiatry, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Pyskowicka 49, Tarnowskie Góry, 42-612, Poland
| | - Piotr Ścisło
- Psychiatric Department of the Multidisciplinary Hospital, Tarnowskie Góry, 42-612, Poland
| | - Paweł Dębski
- Institute of Psychology, Humanitas University in Sosnowiec, Kilińskiego 43, Sosnowiec, 41-200, Poland
| | - Robert Pudlo
- Department of Psychoprophylaxis, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Pyskowicka 49, Tarnowskie Góry, 42-612, Poland
| | - Krisztián Buza
- Budapest Business University, Buzogány utca 10-12, Budapest, 1149, Hungary; BioIntelligence Group, Department of Mathematics-Informatics, Sapientia Hungarian University of Transylvania, Târgu Mureş, Romania
| | - Piotr Gorczyca
- Department of Psychiatry, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Pyskowicka 49, Tarnowskie Góry, 42-612, Poland
| | - Magdalena Piegza
- Department of Psychiatry, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Pyskowicka 49, Tarnowskie Góry, 42-612, Poland
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5
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Quirin M, Malekzad F, Jais M, Kehr H, Ennis M. Heart rate variability and psychological health: The key role of trait emotional awareness. Acta Psychol (Amst) 2024; 246:104252. [PMID: 38677024 DOI: 10.1016/j.actpsy.2024.104252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 03/19/2024] [Accepted: 04/08/2024] [Indexed: 04/29/2024] Open
Abstract
Studies have shown that Trait Emotional Awareness (TEA) - the ability to recognize one's emotions - and Heart Rate Variability (HRV) are both negatively associated with psychological disorders. Although these studies imply that TEA is related to HRV and may explain the association between HRV and psychological disorders, there is limited research investigating this implication. Such investigation is essential to illuminate the psychophysiological processes linked to psychological disorders. The present study aims to investigate a) the association between TEA and HRV, b) the association between HRV and psychological disorders, and c) whether TEA explains the association between HRV and psychological disorders. A sample of 41 German students completed self-report questionnaires as indicators of psychological disorders, including the Hospital Anxiety and Depression Scale (HADS; Snaith & Zigmond, 1983) for anxiousness and depressiveness, as well as the somatization scale of the Hopkins Symptom Checklist (HSCL; Derogatis et al., 1976) for physical complaints. HRV was measured at baseline (resting HRV) and during exposure to a fear-provoking movie clip (reactive HRV). As hypothesized, a) TEA showed a positive association with reactive HRV, b) HRV showed negative associations with anxiousness and physical complaints, and c) TEA explained the relationships between reactive HRV and anxiousness, as well as physical complaints. Contrary to our hypothesis, we did not find any association between HRV and depressiveness. We discussed the contribution of TEA to psychophysiological health, limited generalizability of the current study, and direct future research to explore the underlying mechanisms linking TEA to health.
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Affiliation(s)
- Markus Quirin
- Technical University of Munich, Germany; PFH Göttingen, Germany.
| | - Farhood Malekzad
- Technical University of Munich, Germany; PFH Göttingen, Germany.
| | | | - Hugo Kehr
- Technical University of Munich, Germany.
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6
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Galin S, Keren H. The Predictive Potential of Heart Rate Variability for Depression. Neuroscience 2024; 546:88-103. [PMID: 38513761 DOI: 10.1016/j.neuroscience.2024.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 02/29/2024] [Accepted: 03/16/2024] [Indexed: 03/23/2024]
Abstract
Heart rate variability (HRV),a measure of the fluctuations in the intervals between consecutive heartbeats, is an indicator of changes in the autonomic nervous system. A chronic reduction in HRV has been repeatedly linked to clinical depression. However, the chronological and mechanistic aspects of this relationship, between the neural, physiological, and psychopathological levels, remain unclear. In this review we present evidence by which changes in HRV might precede the onset of depression. We describe several pathways that can facilitate this relationship. First, we examine a theoretical model of the impact of autonomic imbalance on HRV and its role in contributing to mood dysregulation and depression. We then highlight brain regions that are regulating both HRV and emotion, suggesting these neural regions, and the Insula in particular, as potential mediators of this relationship. We also present additional possible mediating mechanisms involving the immune system and inflammation processes. Lastly, we support this model by showing evidence that modification of HRV with biofeedback leads to an improvement in some symptoms of depression. The possibility that changes in HRV precede the onset of depression is critical to put to the test, not only because it could provide insights into the mechanisms of the illness but also because it may offer a predictive anddiagnosticphysiological marker for depression. Importantly, it could also help to develop new effective clinical interventions for treating depression.
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Affiliation(s)
- Shir Galin
- Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel; Gonda Interdisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel
| | - Hanna Keren
- Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel; Gonda Interdisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel.
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Sammito S, Thielmann B, Klussmann A, Deußen A, Braumann KM, Böckelmann I. Guideline for the application of heart rate and heart rate variability in occupational medicine and occupational health science. J Occup Med Toxicol 2024; 19:15. [PMID: 38741189 DOI: 10.1186/s12995-024-00414-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 04/24/2024] [Indexed: 05/16/2024] Open
Abstract
This updated guideline replaces the "Guideline for the application of heart rate and heart rate variability in occupational medicine and occupational health science" first published in 2014. Based on the older version of the guideline, the authors have reviewed and evaluated the findings on the use of heart rate (HR) and heart rate variability (HRV) that have been published in the meantime and incorporated them into a new version of this guideline.This guideline was developed for application in clinical practice and research purposes in the fields of occupational medicine and occupational science to complement evaluation procedures with respect to exposure and risk assessment at the workplace by the use of objective physiological workload indicators. In addition, HRV is also suitable for assessing the state of health and for monitoring the progress of illnesses and preventive medical measures. It gives an overview of factors influencing the regulation of the HR and HRV at rest and during work. It further illustrates methods for measuring and analyzing these parameters under standardized laboratory and real workload conditions, areas of application as well as the quality control procedures to be followed during the recording and evaluation of HR and HRV.
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Affiliation(s)
- Stefan Sammito
- Department of Occupational Medicine, Medical Faculty, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
- German Air Force Centre of Aerospace Medicine, Experimental Aerospace Medicine Research, Flughafenstraße 1, Cologne, 51147, Germany.
| | - Beatrice Thielmann
- Department of Occupational Medicine, Medical Faculty, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Andre Klussmann
- Competence Centre Health (CCG), Department Health Sciences, University of Applied Sciences (HAW) Hamburg, Hamburg, Germany
| | - Andreas Deußen
- Department of Physiology, Medical Faculty, TU Dresden, Dresden, Germany
| | | | - Irina Böckelmann
- Department of Occupational Medicine, Medical Faculty, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
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8
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Kocsel N, Galambos A, Szőke J, Kökönyei G. The moderating effect of resting heart rate variability on the relationship between pain catastrophizing and depressed mood: an empirical study. Biol Futur 2024; 75:29-39. [PMID: 37934392 DOI: 10.1007/s42977-023-00190-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 10/15/2023] [Indexed: 11/08/2023]
Abstract
Previous research indicated that pain catastrophizing-a negative emotional and cognitive response toward actual or anticipated pain-could contribute to pain intensity and could be associated with depressive symptoms not just in chronic pain patients but in healthy population as well. Accumulated evidence suggests that resting heart rate variability (HRV) as a putative proxy of emotion regulation could moderate the association of self-reported pain catastrophizing and depressed mood. In the present cross-sectional study, we investigated these associations in a healthy young adult sample controlling for the effect of trait rumination. Seventy-two participants (58 females, mean age = 22.2 ± 1.79 years ranging from 19 to 28 years old) completed the Pain Catastrophizing Scale, the Zung Self-Rating Depression Scale and the Ruminative Response Scale. Resting HRV was measured by time domain metric of HRV, the root mean square of successive differences (RMSSD). The results showed that the relationship between pain catastrophizing and depressive symptoms is significantly moderated by resting HRV (indexed by lnRMSSD). Specifically, in participants with higher resting HRV there was no significant relationship between the two investigated variables, while in participants with relatively low or medium HRV pain catastrophizing and depressed mood showed significant positive association. The relationship remained significant after controlling for sex, age and trait rumination. These results might indicate that measuring pain catastrophizing and depressive symptoms is warranted in non-clinical samples as well and higher resting HRV could have a buffer or protective role against depressive symptoms.
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Affiliation(s)
- Natália Kocsel
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary.
| | - Attila Galambos
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Júlia Szőke
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Doctoral School of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Gyöngyi Kökönyei
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- NAP3.0-SE Neuropsychopharmacology Research Group, Hungarian Brain Research Program, Semmelweis University, Budapest, Hungary
- Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University, Budapest, Hungary
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Tomasi J, Zai CC, Pouget JG, Tiwari AK, Kennedy JL. Heart rate variability: Evaluating a potential biomarker of anxiety disorders. Psychophysiology 2024; 61:e14481. [PMID: 37990619 DOI: 10.1111/psyp.14481] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 08/19/2023] [Accepted: 10/20/2023] [Indexed: 11/23/2023]
Abstract
Establishing quantifiable biological markers associated with anxiety will increase the objectivity of phenotyping and enhance genetic research of anxiety disorders. Heart rate variability (HRV) is a physiological measure reflecting the dynamic relationship between the sympathetic and parasympathetic nervous systems, and is a promising target for further investigation. This review summarizes evidence evaluating HRV as a potential physiological biomarker of anxiety disorders by highlighting literature related to anxiety and HRV combined with investigations of endophenotypes, neuroimaging, treatment response, and genetics. Deficient HRV shows promise as an endophenotype of pathological anxiety and may serve as a noninvasive index of prefrontal cortical control over the amygdala, and potentially aid with treatment outcome prediction. We propose that the genetics of HRV can be used to enhance the understanding of the genetics of pathological anxiety for etiological investigations and treatment prediction. Given the anxiety-HRV link, strategies are offered to advance genetic analytical approaches, including the use of polygenic methods, wearable devices, and pharmacogenetic study designs. Overall, HRV shows promising support as a physiological biomarker of pathological anxiety, potentially in a transdiagnostic manner, with the heart-brain entwinement providing a novel approach to advance anxiety treatment development.
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Affiliation(s)
- Julia Tomasi
- Molecular Brain Science Department, Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Clement C Zai
- Molecular Brain Science Department, Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Jennie G Pouget
- Molecular Brain Science Department, Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Arun K Tiwari
- Molecular Brain Science Department, Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - James L Kennedy
- Molecular Brain Science Department, Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
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Li Z, Pulopulos M, Allaert J, De Smet S, De Wandel L, Kappen M, Puttevils L, Razza LB, Schoonjans E, Vanhollebeke G, Baeken C, De Raedt R, Vanderhasselt MA. Vagally-mediated HRV as a marker of trait rumination in healthy individuals? A large cross-sectional analysis. Psychophysiology 2024; 61:e14448. [PMID: 37779356 DOI: 10.1111/psyp.14448] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 08/29/2023] [Accepted: 08/29/2023] [Indexed: 10/03/2023]
Abstract
The tendency to ruminate (i.e., repetitive, self-referential, negative thoughts) is a maladaptive form of emotional regulation and represents a transdiagnostic vulnerability factor for stress-related psychopathology. Vagally-mediated heart rate variability (vmHRV) provides a non-invasive, surrogate measure of vagal modulation of the heart, and higher HRV is considered an indicator of susceptibility, or ability to respond to stress. Past research has suggested a link between trait rumination and vmHRV; however, inconsistent results exist in healthy individuals. In this study, we investigated the association between the tendency to ruminate, brooding, and reflection (using the Ruminative Response Scale) with vmHRV measured at baseline in a healthy population using a large cross-sectional dataset (N = 1189, 88% female; mean age = 21.55, ranging from 17 to 48 years old), which was obtained by combining samples of healthy individuals from different studies from our laboratory. The results showed no cross-sectional correlation between vmHRV and trait rumination (confirmed by Bayesian analysis), even after controlling for important confounders such as gender, age, and depressive symptoms. Also, a non-linear relationship was rejected. In summary, based on our results in a large sample of healthy individuals, vmHRV is not a marker of trait rumination (as measured by the Ruminative Response Scale).
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Affiliation(s)
- Zefeng Li
- Department of Head and Skin, Ghent Experimental Psychiatry Lab, Ghent University, Ghent, Belgium
| | - Matias Pulopulos
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Jens Allaert
- Department of Head and Skin, Ghent Experimental Psychiatry Lab, Ghent University, Ghent, Belgium
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Stefanie De Smet
- Department of Head and Skin, Ghent Experimental Psychiatry Lab, Ghent University, Ghent, Belgium
| | - Linde De Wandel
- Department of Head and Skin, Ghent Experimental Psychiatry Lab, Ghent University, Ghent, Belgium
| | - Mitchel Kappen
- Department of Head and Skin, Ghent Experimental Psychiatry Lab, Ghent University, Ghent, Belgium
| | - Louise Puttevils
- Department of Head and Skin, Ghent Experimental Psychiatry Lab, Ghent University, Ghent, Belgium
| | - Lais B Razza
- Department of Head and Skin, Ghent Experimental Psychiatry Lab, Ghent University, Ghent, Belgium
| | - Emmanuelle Schoonjans
- Department of Head and Skin, Ghent Experimental Psychiatry Lab, Ghent University, Ghent, Belgium
| | - Gert Vanhollebeke
- Department of Head and Skin, Ghent Experimental Psychiatry Lab, Ghent University, Ghent, Belgium
| | - Chris Baeken
- Department of Head and Skin, Ghent Experimental Psychiatry Lab, Ghent University, Ghent, Belgium
- Department of Psychiatry (UZ Brussel), Vrije Universiteit Brussel, Ixelles, Belgium
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Rudi De Raedt
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Marie-Anne Vanderhasselt
- Department of Head and Skin, Ghent Experimental Psychiatry Lab, Ghent University, Ghent, Belgium
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Anmella G, Mas A, Sanabra M, Valenzuela-Pascual C, Valentí M, Pacchiarotti I, Benabarre A, Grande I, De Prisco M, Oliva V, Fico G, Giménez-Palomo A, Bastidas A, Agasi I, Young AH, Garriga M, Corponi F, Li BM, de Looff P, Vieta E, Hidalgo-Mazzei D. Electrodermal activity in bipolar disorder: Differences between mood episodes and clinical remission using a wearable device in a real-world clinical setting. J Affect Disord 2024; 345:43-50. [PMID: 37865347 DOI: 10.1016/j.jad.2023.10.125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 10/16/2023] [Accepted: 10/18/2023] [Indexed: 10/23/2023]
Abstract
BACKGROUND Bipolar disorder (BD) lacks objective measures for illness activity and treatment response. Electrodermal activity (EDA) is a quantitative measure of autonomic function, which is altered in manic and depressive episodes. We aimed to explore differences in EDA (1) inter-individually: between patients with BD on acute mood episodes, euthymic states and healthy controls (HC), and (2) intra-individually: longitudinally within patients during acute mood episodes of BD and after clinical remission. METHODS A longitudinal observational study. EDA was recorded using a research-grade wearable in patients with BD during acute manic and depressive episodes and at clinical remission. Euthymic BD patients and HC were recorded during a single session. We compared EDA parameters derived from the tonic (mean EDA, mEDA) and phasic components (EDA peaks per minute, pmEDA, and EDA peaks mean amplitude, pmaEDA). Inter- and intra-individual comparisons were computed respectively with ANOVA and paired t-tests. RESULTS 49 patients with BD (15 manic, 9 depressed, and 25 euthymic), and 19 HC were included. Patients with bipolar depression showed significantly reduced mEDA (p = 0.003) and pmEDA (p = 0.001), which increased to levels similar to euthymia or HC after clinical remission (mEDA, p = 0.011; pmEDA, p < 0.001; pmaEDA, p < 0.001). Manic patients showed no differences compared to euthymic patients and HCs, but a significant reduction of tonic and phasic EDA parameters after clinical remission (mEDA, p = 0.035; pmEDA, p = 0.004). LIMITATIONS Limited sample size, high inter-individual variability of EDA parameters, limited comparability to previous studies and non-adjustment for medication. CONCLUSION EDA ecological monitoring might provide several opportunities for early detection of depressive symptoms, and might aid at assessing early response to treatments in mania and bipolar depression.
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Affiliation(s)
- Gerard Anmella
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain.
| | - Ariadna Mas
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Miriam Sanabra
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Clàudia Valenzuela-Pascual
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Marc Valentí
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Isabella Pacchiarotti
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Antoni Benabarre
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Iria Grande
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Michele De Prisco
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Vincenzo Oliva
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Giovanna Fico
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Anna Giménez-Palomo
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Anna Bastidas
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain
| | - Isabel Agasi
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain
| | - Allan H Young
- Centre for Affective Disorders (CfAD), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
| | - Marina Garriga
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | | | - Bryan M Li
- School of informatics, University of Edinburgh, UK
| | - Peter de Looff
- Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands; Fivoor, Science and Treatment Innovation, Expert centre "De Borg", Den Dolder, the Netherlands
| | - Eduard Vieta
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Diego Hidalgo-Mazzei
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.
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Lu L, Zhu T, Morelli D, Creagh A, Liu Z, Yang J, Liu F, Zhang YT, Clifton DA. Uncertainties in the Analysis of Heart Rate Variability: A Systematic Review. IEEE Rev Biomed Eng 2024; 17:180-196. [PMID: 37186539 DOI: 10.1109/rbme.2023.3271595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Heart rate variability (HRV) is an important metric with a variety of applications in clinical situations such as cardiovascular diseases, diabetes mellitus, and mental health. HRV data can be potentially obtained from electrocardiography and photoplethysmography signals, then computational techniques such as signal filtering and data segmentation are used to process the sampled data for calculating HRV measures. However, uncertainties arising from data acquisition, computational models, and physiological factors can lead to degraded signal quality and affect HRV analysis. Therefore, it is crucial to address these uncertainties and develop advanced models for HRV analysis. Although several reviews of HRV analysis exist, they primarily focus on clinical applications, trends in HRV methods, or specific aspects of uncertainties such as measurement noise. This paper provides a comprehensive review of uncertainties in HRV analysis, quantifies their impacts, and outlines potential solutions. To the best of our knowledge, this is the first study that presents a holistic review of uncertainties in HRV methods and quantifies their impacts on HRV measures from an engineer's perspective. This review is essential for developing robust and reliable models, and could serve as a valuable future reference in the field, particularly for dealing with uncertainties in HRV analysis.
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13
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Waddington JL. From operational diagnostic to dimensional-continuum concepts of psychotic and non-psychotic illness: Embracing catatonia across psychopathology and intrinsic movement disorder in neural network dysfunction. Schizophr Res 2024; 263:99-108. [PMID: 36244867 DOI: 10.1016/j.schres.2022.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 10/01/2022] [Accepted: 10/02/2022] [Indexed: 03/04/2023]
Abstract
Psychiatry is currently negotiating several challenges that are typified by (but are not unique to) schizophrenia: do periodic refinements in operational diagnostic algorithms (a) resolve intricacies and subtleties within and between psychotic and non-psychotic disorders that are authentic and impactful, or (b) constitute arbitrary and porous boundaries that should be complemented, or even replaced, by dimensional-continuum concepts of abnormality and dysfunction. Critically, these issues relate not only to apparent boundaries between diagnoses but also to those between 'health' and 'illness'. This article considers catatonia within evolving dimensional-continuum approaches to the description of impairment and dysfunction among psychotic and non-psychotic disorders. It begins by considering the definition and assessment of catatonia vis-à-vis other disorders, followed by its long-standing conjunction with schizophrenia, relationship with antipsychotic drug treatment, transdiagnostic perspectives and relationships, and pathobiological processes. These appear to involve dysfunction across elements in overlapping neural networks that result in a confluence of psychopathology and intrinsic hypo- and hyperkinetic motor dysfunction. It has been argued that while current diagnostic approaches can have utility in defining groups of cases that are closely related, contemporary evidence indicates categorical diagnoses to be arbitrary divisions of what is essentially a continuous landscape. Psychotic and non-psychotic diagnoses, including catatonia, may reflect arbitrary areas around points of intersection between orthogonal dimensions of psychopathology and intrinsic movement disorder in a poly-dimensional space that characterises this continuous landscape of mental health and dysfunction.
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Affiliation(s)
- John L Waddington
- School of Pharmacy and Biomolecular Sciences, RCSI University of Medicine and Health Sciences, Dublin, Ireland; Jiangsu Key Laboratory of Translational Research & Therapy for Neuropsychiatric Disorders and Department of Pharmacology, College of Pharmaceutical Sciences, Soochow University, Suzhou, China.
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14
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Xie F, Zhou L, Hu Q, Zeng L, Wei Y, Tang X, Gao Y, Hu Y, Xu L, Chen T, Liu H, Wang J, Lu Z, Chen Y, Zhang T. Cardiovascular variations in patients with major depressive disorder versus bipolar disorder. J Affect Disord 2023; 341:219-227. [PMID: 37657620 DOI: 10.1016/j.jad.2023.08.128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 08/14/2023] [Accepted: 08/29/2023] [Indexed: 09/03/2023]
Abstract
BACKGROUND Differentiating depression in major depressive disorder and bipolar disorder is challenging in clinical practice. Therefore, reliable biomarkers are urgently needed to differentiate between these diseases. This study's main objective was to assess whether cardiac autonomic function can distinguish patients with unipolar depression (UD), bipolar depression (BD), and bipolar mania (BM). METHODS We recruited 791 patients with mood disorders, including 191 with UD, 286 with BD, and 314 with BM, who had been drug free for at least 2 weeks. Cardiovascular status was measured using heart rate variability (HRV) and pulse wave velocity (PWV) indicators via finger photoplethysmography during a 5-min rest period. RESULTS Patients with BD showed lower HRV but higher heart rates than those with UD and BM. The PWV indicators were lower in the UD group than in the bipolar disorder group. The covariates of age, sex, and body mass index affected the cardiovascular characteristics. After adjusting for covariates, the HRV and PWV variations among the three groups remained significant. Comparisons between the UD and BD groups showed that the variable with the largest effect size was the frequency-domain indices of HRV, very low and high frequency, followed by heart rate. The area under the receiver operating characteristic curve (AUC) for each cardiovascular variable ranged from 0.661 to 0.714. The High-frequency index reached the highest AUC. LIMITATIONS Cross-sectional design and the magnitude of heterogeneity across participants with mood disorders limited our findings. CONCLUSION Patients with BD, but not BM, had a greater extent of cardiac imbalance than those with UD. Thus, HRV may serve as a psychophysiological biomarker for the differential diagnosis of UD and BD.
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Affiliation(s)
- Fei Xie
- School of Public Health, Fudan University, Shanghai, China; Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - LinLin Zhou
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - Qiang Hu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China; Department of Psychiatry, ZhenJiang Mental Health Center, Zhenjiang, China
| | - LingYun Zeng
- Department of Psychiatric Rehabilitation, Shenzhen Kangning Hospital, ShenZhen, China
| | - YanYan Wei
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - XiaoChen Tang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - YuQing Gao
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - YeGang Hu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - LiHua Xu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - Tao Chen
- Big Data Research Lab, University of Waterloo, Ontario, Canada; Labor and Worklife Program, Harvard University, MA, United States
| | - HaiChun Liu
- Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
| | - JiJun Wang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - Zheng Lu
- Department of Psychiatry, Tongji Hospital, Tongji University School of Medicine, 389 Xin Cun Road, Shanghai 200065, China.
| | - YingYao Chen
- School of Public Health, Fudan University, Shanghai, China.
| | - TianHong Zhang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China.
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15
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Biçer GY, Kurt A, Zor KR. Efficacy of automatic pupillometry as a screening technique to detect autonomic dysfunction in bipolar disorder. Clin Exp Optom 2023; 106:896-900. [PMID: 36436223 DOI: 10.1080/08164622.2022.2145182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 11/03/2022] [Indexed: 11/28/2022] Open
Abstract
CLINICAL RELEVANCE Autonomic nervous system abnormalities in the pathophysiology of bipolar disorder are controversial. Pupillary features may be affected as a result of autonomic nervous system abnormalities in bipolar disorder. Small changes in pupillary responses may not be noticeable on clinical examination. Automated pupillemetries can be helpful in demonstrating these changes reliably and quantitatively. BACKGROUND The aim of this study was to compare the static and dynamic pupillary responses of bipolar patients with healthy controls. In addition, pupillary response differences between mania, depression and remission stages were investigated. METHODS The bipolar patient group consisted of 39 eyes of 39 patients with 13 patients in each of the stages: mania, depression and remission. The control group consisted of 39 eyes of 39 healthy volunteers. After the ophthalmic examination, static and dynamic pupillometry measurements were made. The mean pupil dilatation speed was calculated according to dynamic measurements. Static pupillometry measurements including scotopic, mesopic and photopic pupil diameters; the first dynamic measurements at 0th second and pupillary dilatation speed were used for statistical analysis. RESULTS There was no difference static and the first dynamic pupillometry measurements between the bipolar and control groups (p > 0.05 for all parameters), but there was a significant difference in mean pupil dilatation speed (p = 0.041). No significant differences were found between the 3 groups for all static and the first dynamic pupillometry measurements and the mean pupil dilatation speed (p > 0.05). CONCLUSION Static and the first dynamic measurements of bipolar patients were not different from healthy controls. The mean pupil dilatation speed of bipolar patients was significantly lower, but this difference had a low effect size.
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Affiliation(s)
| | - Aydın Kurt
- Department of Psychiatry, Niğde Ömer Halisdemir Education and Research Hospital, Niğde, Turkey
| | - Kürşad Ramazan Zor
- Department of Ophthalmology, Niğde Ömer Halisdemir University, Niğde, Turkey
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Gullett N, Zajkowska Z, Walsh A, Harper R, Mondelli V. Heart rate variability (HRV) as a way to understand associations between the autonomic nervous system (ANS) and affective states: A critical review of the literature. Int J Psychophysiol 2023; 192:35-42. [PMID: 37543289 DOI: 10.1016/j.ijpsycho.2023.08.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 07/31/2023] [Accepted: 08/02/2023] [Indexed: 08/07/2023]
Abstract
Evidence suggests affective disorders such as depression and bipolar disorder are characterised by dysregulated autonomic nervous system (ANS) activity. These findings suggest ANS dysregulation may be involved in the pathogenesis of affective disorders. Different affective states are characterised by different ANS activity patterns (i.e., an increase or decrease in sympathetic or parasympathetic activity). To understand how ANS abnormalities are involved in the development of affective disorders, it is important to understand how affective states correlate with ANS activity before their onset. Using heart rate variability (HRV) as a tool to measure ANS activity, this review aimed to look at associations between affective states and HRV in non-clinical populations (i.e., in those without medical and psychiatric disorders). Searches on PubMed and Google Scholar were completed using the following search terms: heart rate variability, autonomic nervous system, sympathetic nervous system, parasympathetic nervous system, affective state, mood and emotion in all possible combinations. All but one of the studies examined (N = 13), demonstrated significant associations between affect and HRV. Findings suggest negative affect, encompassing both diffused longer-term experiences (i.e., mood) as well as more focused short-term experiences (i.e., emotions), may be associated with a reduction in parasympathetic activity as measured through HRV parameters known to quantify parasympathetic activity (e.g., high frequency (HF)-HRV). HRV measures typically linked to reduction in parasympathetic activity appear to be linked to negative affective states in non-clinical populations. However, given the complex and possibly non-linear relationship between HRV and parasympathetic activity, further studies need to clarify specificity of these findings. Future studies should investigate the potential utility of HRV measures as biomarkers for monitoring changes in affective states and for early detection of onset and relapse of depression in patients with affective disorders.
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Affiliation(s)
- Nancy Gullett
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, London, UK.
| | - Zuzanna Zajkowska
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, London, UK
| | - Annabel Walsh
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, London, UK
| | - Ross Harper
- Limbic, Kemp House, 160 City Road, London EC1V 2NX, UK
| | - Valeria Mondelli
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, London, UK; National Institute for Health Research Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust and King's College London, London, UK
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Stautland A, Jakobsen P, Fasmer OB, Osnes B, Torresen J, Nordgreen T, Oedegaard KJ. Reduced heart rate variability during mania in a repeated naturalistic observational study. Front Psychiatry 2023; 14:1250925. [PMID: 37743991 PMCID: PMC10513449 DOI: 10.3389/fpsyt.2023.1250925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 08/21/2023] [Indexed: 09/26/2023] Open
Abstract
Background Bipolar disorder (BD) is a chronic recurrent mood disorder associated with autonomic nervous system (ANS) dysfunction, indexed by heart rate variability (HRV). Changes in HRV between mood states are sparsely studied longitudinally. We aimed to compare HRV of hospitalized manic individuals with their own euthymic selves in a naturalistic observational study. Methods 34 individuals were included, of which 16 were lost to follow-up. Ultimately 15 patients provided reliable heart rate data in both a manic and euthymic state, using photoplethysmography (PPG) sensor wristbands overnight. We calculated HRV measures Root Mean Square of Successive Differences (RMSSD), High-frequency (HF: 0.15-0.40 Hz), Low-frequency (LF: 0.40-0.15 Hz), Very low-frequency (VLF: 0.0033-0.04 Hz), Total power and Sample Entropy in 5-min night-time resting samples. We compared HRV measures by mood state within individuals using paired t-tests and linear regression to control for age and sex. Results HRV was lower in the manic state when compared to the euthymic state for all HRV metrics (p ≤ 0.02), with large to medium effect sizes (g = 1.24 to 0.65). HRV changes were not significantly affected by age or sex. Conclusion This longitudinal study provides evidence of lower HRV in manic states compared to euthymia, indicating an association between ANS dysregulation and changes in bipolar mood state. This corroborates previous cross-sectional studies, although the association may be less clear or reversed in hypomanic states. Further investigation in larger longitudinal samples is warranted.
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Affiliation(s)
- Andrea Stautland
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Petter Jakobsen
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- NORMENT, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Ole Bernt Fasmer
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- NORMENT, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Berge Osnes
- Department of Clinical Psychology, University of Bergen, Bergen, Norway
| | - Jim Torresen
- Department of Informatics and RITMO, University of Oslo, Oslo, Norway
| | - Tine Nordgreen
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Ketil J. Oedegaard
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- NORMENT, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
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Miller ML, Sanzari CM, Timko CA, Hormes JM. Impact of virtual adjunctive cognitive remediation therapy on cognitive flexibility and treatment outcomes in comorbid anorexia nervosa and exercise dependence as quantified using novel biomarkers: A stage 1 registered report. Int J Eat Disord 2023; 56:1449-1460. [PMID: 37464977 DOI: 10.1002/eat.23942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 03/04/2023] [Accepted: 03/15/2023] [Indexed: 07/20/2023]
Abstract
OBJECTIVE Anorexia nervosa (AN) is associated with significant individual mental and physical suffering and public health burden and fewer than half of patients recover fully with current treatments. Comorbid exercise dependence (ExD) is common in AN and associated with significantly worse symptom severity and treatment outcomes. Research points to cognitive inflexibility as a prominent executive function inefficiency and transdiagnostic etiologic and maintaining mechanism linking AN and ExD. This study will evaluate the initial efficacy of adjunctive Cognitive Remediation Therapy (CRT), which has been shown to produce cognitive improvements in adults with AN, in targeting cognitive inflexibility in individuals with comorbid AN and ExD. As an exploratory aim, this study also addresses the current lack of quick and cost-effective assessments of cognitive flexibility by establishing the utility of two proposed biomarkers, heart rate variability and salivary oxytocin. METHOD We will conduct a single-group, within-subjects trial of an established CRT protocol delivered remotely as an adjunct to inpatient or intensive outpatient treatment as usual (TAU) to adult patients (n = 42) with comorbid AN and ExD. Assessments, including self-report, neuropsychological, and biomarker measurements, will occur at three time points. RESULTS We expect CRT to increase cognitive flexibility transdiagnostically and consequently, along with TAU, positively impact AN and ExD compulsivity and symptom severity, including weight gain. DISCUSSION Findings will inform the development of more effective integrative interventions for AN and ExD targeting shared mechanisms and facilitate the routine assessment of cognitive flexibility as a transdiagnostic risk and maintaining factor across psychopathologies in clinical and research settings. PUBLIC SIGNIFICANCE Patients with anorexia nervosa often engage in excessive exercise, leading to harmful outcomes, including increased suicidal behavior. This study examines the preliminary efficacy of an intervention that fosters flexible and holistic thinking in patients with problematic eating and exercise to, along with routine treatment, decrease harmful exercise symptoms. This study also examines new biological markers of the inflexible thinking style thought to be characteristic of anorexia nervosa and exercise dependence.
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Affiliation(s)
- McKenzie L Miller
- Department of Psychology, University at Albany, Albany, New York, USA
| | | | - C Alix Timko
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Philadelphia, USA
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, The Children's Hospital of Philadelphia, Philadelphia, Philadelphia, USA
| | - Julia M Hormes
- Department of Psychology, University at Albany, Albany, New York, USA
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Chen W, Zhong Q, Chen H, Chen S. Heart rate variability in children and adolescents with major depressive disorder: A systematic review and meta-analysis. J Affect Disord 2023; 335:204-215. [PMID: 37178829 DOI: 10.1016/j.jad.2023.05.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 04/23/2023] [Accepted: 05/06/2023] [Indexed: 05/15/2023]
Abstract
Although reduced heart rate variability (HRV) has been observed in adults with major depressive disorder (MDD), the correlation between HRV and MDD in children and adolescents remains uncertain and requires to be systematically reviewed. Our meta-analysis included ten articles comprising 410 MDD patients and 409 healthy controls. Adolescents with MDD showed significant reductions in most HRV measures, such as HF-HRV, RMSSD, and PNN50, and depressive symptom severity was statistically associated with RMSSD, HF-HRV, and LF/HF ratio. A large heterogeneity across studies was detected. Sensitivity analysis revealed that removal of a specific study would significantly decline the heterogeneity for measures of HF-HRV, LF-HRV, and SDNN, and meta-regression analysis found that sample size and year of publication substantially moderated the differences between depressed samples and controls in RMSSD. Compared with adults, depression-induced autonomic dysfunction was more detectable in children and adolescents with substantial effects. Moreover, excluded studies which reported both HRV and MDD or depression symptoms were summarized based on objectives. Findings indicate that it is promising for HRV to be an appropriate and objective candidate biomarker for clinically depressed children and adolescents.
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Affiliation(s)
- Wanlin Chen
- Department of Psychological and Behavioral Science, Zhejiang University, No.866 Yuhangtang Road, Hangzhou, Zhejiang 310058, China
| | - Qing Zhong
- Department of Psychological and Behavioral Science, Zhejiang University, No.866 Yuhangtang Road, Hangzhou, Zhejiang 310058, China
| | - Hang Chen
- College of Biomedical Engineering and Instrument Science, Zhejiang University, No.38 Zheda Road, Hangzhou, Zhejiang 310027, China
| | - Shulin Chen
- Department of Psychological and Behavioral Science, Zhejiang University, No.866 Yuhangtang Road, Hangzhou, Zhejiang 310058, China.
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20
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Anmella G, Corponi F, Li BM, Mas A, Sanabra M, Pacchiarotti I, Valentí M, Grande I, Benabarre A, Giménez-Palomo A, Garriga M, Agasi I, Bastidas A, Cavero M, Fernández-Plaza T, Arbelo N, Bioque M, García-Rizo C, Verdolini N, Madero S, Murru A, Amoretti S, Martínez-Aran A, Ruiz V, Fico G, De Prisco M, Oliva V, Solanes A, Radua J, Samalin L, Young AH, Vieta E, Vergari A, Hidalgo-Mazzei D. Exploring digital biomarkers of illness activity in mood episodes: hypotheses generating and model development study. JMIR Mhealth Uhealth 2023; 11:e45405. [PMID: 36939345 DOI: 10.2196/45405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 02/20/2023] [Accepted: 03/07/2023] [Indexed: 03/21/2023] Open
Abstract
BACKGROUND Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity alongside physiological alterations that wearables can capture. OBJECTIVE We explored whether physiological wearable data could predict: (aim 1) the severity of an acute affective episode at the intra-individual level, (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to the prior predictions, generalization across patients, and associations between affective symptoms and physiological data. METHODS We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded with a research-grade wearable (Empatica E4) across three consecutive timepoints (acute, response, and remission of episode). Euthymic patients and healthy controls (HC) were recorded during a single session (∼48 hours). Manic and depressive symptoms were assessed with standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), temperature (TEMP), blood volume pulse (BVP), heart rate (HR), and electrodermal activity (EDA). For data pre-processing, invalid physiological data were removed using a rule-based filter, channels were time-aligned at 1 second time units and then segmented window lengths of 32 seconds, since those parameters showed the best performances. We developed deep learning predictive models, assessed channels' individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales' items normalized mutual information (NMI). We present a novel fully automated method for analysis of physiological data from a research-grade wearable device, including a rule-based filter for invalid data and a viable supervised learning pipeline for time-series analyses. RESULTS 35 sessions (1,512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 HC (age 39.7±12.6; 31.6% female) were analyzed. (aim 1) The severity of mood episodes was predicted with moderate (62%-85%) accuracies. (aim 2) The polarity of episodes was predicted with moderate (70%) accuracy. The most relevant features for the former tasks were ACC, EDA, and HR. Kendall W showed fair agreement (0.383) in feature importance across classification tasks. Generalization of the former models were of overall low accuracy, with better results for the intra-individual models. "Increased motor activity" was associated with ACC (NMI>0.55), "aggressive behavior" with EDA (NMI=1.0), "insomnia" with ACC (NMI∼0.6), "motor inhibition" with ACC (NMI∼0.75), and "psychic anxiety" with EDA (NMI=0.52). CONCLUSIONS Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression respectively. These findings represent a promising pathway towards personalized psychiatry, in which physiological wearable data could allow early identification and intervention of mood episodes. CLINICALTRIAL
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Affiliation(s)
- Gerard Anmella
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Filippo Corponi
- School of informatics, University of Edinburgh, UK., Edinburgh, GB
| | - Bryan M Li
- School of informatics, University of Edinburgh, UK., Edinburgh, GB
| | - Ariadna Mas
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Miriam Sanabra
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Isabella Pacchiarotti
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Marc Valentí
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Iria Grande
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Antoni Benabarre
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Anna Giménez-Palomo
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Marina Garriga
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Isabel Agasi
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Anna Bastidas
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Myriam Cavero
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | | | - Néstor Arbelo
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Miquel Bioque
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Clemente García-Rizo
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Norma Verdolini
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Santiago Madero
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Andrea Murru
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Silvia Amoretti
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Anabel Martínez-Aran
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Victoria Ruiz
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Giovanna Fico
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Michele De Prisco
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Vincenzo Oliva
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Aleix Solanes
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) group, Barcelona, ES
| | - Joaquim Radua
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) group, Barcelona, ES
| | - Ludovic Samalin
- Department of Psychiatry, CHU Clermont-Ferrand, University of Clermont Auvergne, CNRS, Clermont Auvergne INP, Institut Pascal (UMR 6602), Clermont-Ferrand, France., Clermont-Ferrand, FR
| | - Allan H Young
- Centre for Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom., London, GB
| | - Eduard Vieta
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Antonio Vergari
- School of informatics, University of Edinburgh, UK., Edinburgh, GB
| | - Diego Hidalgo-Mazzei
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
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Breznoscakova D, Kovanicova M, Sedlakova E, Pallayova M. Autogenic Training in Mental Disorders: What Can We Expect? INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4344. [PMID: 36901353 PMCID: PMC10001593 DOI: 10.3390/ijerph20054344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/18/2023] [Accepted: 02/25/2023] [Indexed: 06/18/2023]
Abstract
Autogenic training (AT) is a well-established self-induced relaxation technique based on autosuggestion. From the past two decades, an increasing number of AT studies strongly suggests the practical usefulness of psychophysiological relaxation in the area of medicine. Despite this interest, to date, limited critical clinical reflection on the application and effects of AT in mental disorders exists. The present paper reviews psychophysiological, psychopathological, and clinical aspects of AT in persons with mental disorders with emphasis on implications for future research and practice. Based on a formal literature search, 29 reported studies (7 meta-analyses/systematic reviews) were identified that examined the effects and impact of AT on mental disorders. The main psychophysiological effects of AT include autonomic cardiorespiratory changes paralleled by central nervous system activity modifications and psychological outputs. Studies demonstrate consistent efficacy of AT in reducing anxiety and medium range positive effects for mild-to-moderate depression. The impact on bipolar disorders, psychotic disorders, and acute stress disorder remains unexplored. As an add-on intervention psychotherapy technique with beneficial outcome on psychophysiological functioning, AT represents a promising avenue towards expanding research findings of brain-body links beyond the current limits of the prevention and clinical management of number of mental disorders.
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Affiliation(s)
- Dagmar Breznoscakova
- Department of Social and Behavioural Medicine, Faculty of Medicine, Pavol Jozef Safarik University, Trieda SNP 1, 040 11 Kosice, Slovakia
- Center for Mental Functions, Crystal Comfort, LLC, M. R. Stefanika 2427, 093 01 Vranov nad Toplou, Slovakia
| | - Milana Kovanicova
- 2nd Department of Psychiatry, University Hospital of Louis Pasteur, Rastislavova 43, 041 90 Kosice, Slovakia
| | - Eva Sedlakova
- Department of Pathological Physiology, Faculty of Medicine, Pavol Jozef Safarik University, Trieda SNP 1, 040 11 Kosice, Slovakia
| | - Maria Pallayova
- Department of Human Physiology, Faculty of Medicine, Pavol Jozef Safarik University, Trieda SNP 1, 040 11 Kosice, Slovakia
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The Challenges of Studying Cognition and Autonomic Nervous System Dysregulation in Psychosis. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:131-132. [PMID: 36754482 DOI: 10.1016/j.bpsc.2022.12.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 12/21/2022] [Indexed: 02/09/2023]
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23
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Ettore E, Müller P, Hinze J, Benoit M, Giordana B, Postin D, Lecomte A, Lindsay H, Robert P, König A. Digital Phenotyping for Differential Diagnosis of Major Depressive Episode: Narrative Review. JMIR Ment Health 2023; 10:e37225. [PMID: 36689265 PMCID: PMC9903183 DOI: 10.2196/37225] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 09/02/2022] [Accepted: 09/30/2022] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Major depressive episode (MDE) is a common clinical syndrome. It can be found in different pathologies such as major depressive disorder (MDD), bipolar disorder (BD), posttraumatic stress disorder (PTSD), or even occur in the context of psychological trauma. However, only 1 syndrome is described in international classifications (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [DSM-5]/International Classification of Diseases 11th Revision [ICD-11]), which do not take into account the underlying pathology at the origin of the MDE. Clinical interviews are currently the best source of information to obtain the etiological diagnosis of MDE. Nevertheless, it does not allow an early diagnosis and there are no objective measures of extracted clinical information. To remedy this, the use of digital tools and their correlation with clinical symptomatology could be useful. OBJECTIVE We aimed to review the current application of digital tools for MDE diagnosis while highlighting shortcomings for further research. In addition, our work was focused on digital devices easy to use during clinical interview and mental health issues where depression is common. METHODS We conducted a narrative review of the use of digital tools during clinical interviews for MDE by searching papers published in PubMed/MEDLINE, Web of Science, and Google Scholar databases since February 2010. The search was conducted from June to September 2021. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) automated voice analysis, behavior analysis by (2) video and physiological measures, (3) heart rate variability (HRV), and (4) electrodermal activity (EDA). For this purpose, we were interested in 4 frequently found clinical conditions in which MDE can occur: (1) MDD, (2) BD, (3) PTSD, and (4) psychological trauma. RESULTS A total of 74 relevant papers on the subject were qualitatively analyzed and the information was synthesized. Thus, a digital phenotype of MDE seems to emerge consisting of modifications in speech features (namely, temporal, prosodic, spectral, source, and formants) and in speech content, modifications in nonverbal behavior (head, hand, body and eyes movement, facial expressivity, and gaze), and a decrease in physiological measurements (HRV and EDA). We not only found similarities but also differences when MDE occurs in MDD, BD, PTSD, or psychological trauma. However, comparative studies were rare in BD or PTSD conditions, which does not allow us to identify clear and distinct digital phenotypes. CONCLUSIONS Our search identified markers from several modalities that hold promise for helping with a more objective diagnosis of MDE. To validate their potential, further longitudinal and prospective studies are needed.
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Affiliation(s)
- Eric Ettore
- Department of Psychiatry and Memory Clinic, University Hospital of Nice, Nice, France
| | - Philipp Müller
- Research Department Cognitive Assistants, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Saarbrücken, Germany
| | - Jonas Hinze
- Department of Psychiatry and Psychotherapy, Saarland University Medical Center, Hombourg, Germany
| | - Michel Benoit
- Department of Psychiatry, Hopital Pasteur, University Hospital of Nice, Nice, France
| | - Bruno Giordana
- Department of Psychiatry, Hopital Pasteur, University Hospital of Nice, Nice, France
| | - Danilo Postin
- Department of Psychiatry, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Bad Zwischenahn, Germany
| | - Amandine Lecomte
- Research Department Sémagramme Team, Institut national de recherche en informatique et en automatique, Nancy, France
| | - Hali Lindsay
- Research Department Cognitive Assistants, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Saarbrücken, Germany
| | - Philippe Robert
- Research Department, Cognition-Behaviour-Technology Lab, University Côte d'Azur, Nice, France
| | - Alexandra König
- Research Department Stars Team, Institut national de recherche en informatique et en automatique, Sophia Antipolis - Valbonne, France
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Miller JG, Armstrong-Carter E, Balter L, Lorah J. A meta-analysis of mother-child synchrony in respiratory sinus arrhythmia and contextual risk. Dev Psychobiol 2023; 65:e22355. [PMID: 36567655 DOI: 10.1002/dev.22355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 10/08/2022] [Accepted: 11/02/2022] [Indexed: 12/23/2022]
Abstract
Biobehavioral frameworks of attachment posit that mother-child dyads engage in physiological synchrony that is uniquely formative for children's neurobiological, social, and emotional development. Much of the work on mother-child physiological synchrony has focused on respiratory sinus arrhythmia (RSA). However, the strength of the existing evidence for mother-child RSA synchrony during interaction is unclear. Using meta-analysis, we summarized results from 12 eligible studies comprising 14 samples and 1201 children ranging from infancy to adolescence (Mage = 5.68 years, SD = 4.13, range = 0.4-17 years) and their mothers. We found that there was a statistically significant, albeit modest, positive within-dyad association between mother and child fluctuations in RSA. There also was evidence for significant heterogeneity across studies. Less mother-child RSA synchrony was observed in high-risk samples characterized by clinical difficulties, history of maltreatment, or socioeconomic disadvantage. We did not find that mother-child RSA synchrony significantly differed by task context, mean child age, or by epoch length for computing RSA. Collectively, these findings suggest that mother-child dyads show correspondence in their fluctuations in RSA, and that RSA synchrony is disrupted in high-risk contexts. Future directions and implications for the study of parent-child physiological synchrony are discussed.
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Affiliation(s)
- Jonas G Miller
- Department of Psychology, Stanford University, Stanford, California, USA.,Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut, USA
| | | | - Leah Balter
- Graduate School of Education, Stanford University, Stanford, California, USA
| | - Julie Lorah
- Department of Education and Human Development, Clemson University, Clemson, South Carolina, USA
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Jarczok MN, Weimer K, Braun C, Williams DP, Thayer JF, Gündel HO, Balint EM. Heart rate variability in the prediction of mortality: A systematic review and meta-analysis of healthy and patient populations. Neurosci Biobehav Rev 2022; 143:104907. [DOI: 10.1016/j.neubiorev.2022.104907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 10/03/2022] [Accepted: 10/04/2022] [Indexed: 11/07/2022]
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The Dosage Effect of Laser Acupuncture at PC6 (Neiguan) on Heart Rate Variability: A Pilot Study. LIFE (BASEL, SWITZERLAND) 2022; 12:life12121951. [PMID: 36556316 PMCID: PMC9786668 DOI: 10.3390/life12121951] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 11/09/2022] [Accepted: 11/18/2022] [Indexed: 11/24/2022]
Abstract
Laser acupuncture (LA) has been more applicated in the clinical practice with good responses, but the dosage and parameter settings are still inconsistent with the arguments. This study is focused on the effect of LA on heart rate variability (HRV) with different energy density (ED). Based on the Arndt-Schulz law, we hypothesized that the effective range should fall within 0.01 to 10 J/cm2 of ED, and settings above 10 J/cm2 would perform opposite or inhibitory results. We recruited healthy adults in both sexes as subjects and choose bilateral PC6 (Neiguan) as the intervention points to observe the HRV indexes changes by an external wrist autonomic nerve system (ANS) watch on the left forearm. The data from the ANS watch, including heart rate, blood pressure, and ANS activity indexes, such as low frequency (LF), high frequency (HF), LF%, HF%, LF/HF ratio, and so on, were analyzed by the one-way ANOVA method to test the possible effect. In this study, every subject received all three different EDs of LA in a randomized order. After analyzing the data of 20 subjects, the index of HF% was upward and LF/HF ratio was downward when the ED was 7.96 J/cm2. Otherwise, the strongest ED 23.87 J/cm2 performed the opposite reaction. Appropriately, LA intervention could affect the ANS activities, with the tendency to increase the ratio of parasympathetic and decrease the ratio of sympathetic nerve system activities with statistically significant results, and different ED interventions are consistent with Arndt-Schulz law with opposite performance below and above 10 J/cm2.
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Understanding the Mechanisms of Sudden Cardiac Death in Bipolar Disorder: Functional Asymmetry in Brain-Heart Interactions as a Potential Culprit. Med Hypotheses 2022. [DOI: 10.1016/j.mehy.2022.110986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Dargél AA, Mosconi E, Volant S, Taieb D, Brenot P. Sexual dysfunction among males and females with bipolar disorder and healthy subjects: The burden of illness severity. Bipolar Disord 2022; 24:637-646. [PMID: 36000440 DOI: 10.1111/bdi.13249] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Sexual dysfunction has wide-ranging impacts on the person's functioning and quality of life, being associated with higher severity of psychiatric illnesses and poor therapeutic response. Given the paucity of data on this topic in bipolar disorder (BD), we investigated sexual functioning among males and females with BD and healthy controls (HCs) as well as whether illness severity markers and subthreshold mood symptoms were associated with sexual dysfunctions in BD patients. METHODS The study included 80 BD outpatients and 70 HCs. Sexual functioning was evaluated using the validated, gender-specific Changes in Sexual Functioning Questionnaire (CSFQ-14). RESULTS BD patients had a significantly poorer sexual functioning than HCs (p < 0.00001). The odds of sexual dysfunction doubled given a one-unit increase in the number of suicide attempts (adjusted OR = 2.01, 95% CI:1.23-3.55; p < 0.01) and increased by 60% for every additional hospitalization (p < 0.05). Greater illness duration was associated with arousal/orgasmic (p < 0.05) and overall sexual dysfunctions (p < 0.01). BD patients with more mixed or (hypo)manic episodes had a lower likelihood of libido loss and arousal/orgasmic disturbances (p < 0.01), respectively. Higher levels of subthreshold depressive symptoms increased by 20% the odds of sexual interest/frequency dysfunctions (p < 0.05), and up to 60% regarding orgasmic disturbances (p < 0.01). CONCLUSIONS Sexual functioning may be a useful proxy of illness severity as well as a relevant dimension to more deeply characterize BD patients. Further studies are warranted to replicate our findings, to evaluate temporal associations between sexual dysfunctions and illness severity across the BD mood and treatment spectrums and to explore neurobiological underpinnings of these associations.
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Affiliation(s)
- Aroldo A Dargél
- Institut Pasteur, Unité Perception et Mémoire, Paris, France.,Centre National de la Recherche Scientifique, Unité Mixte de Recherche, Paris, France
| | - Elise Mosconi
- Centre d'étude de la Sexologie et de la Sexualité Humaine, Université Paris 5-René Descartes, Paris, France
| | - Stevenn Volant
- Hub de Bioinformatique, Biostatistique et Biologie Intégrative, Institut Pasteur, Paris, France
| | - David Taieb
- Centre d'étude de la Sexologie et de la Sexualité Humaine, Université Paris 5-René Descartes, Paris, France
| | - Philippe Brenot
- Centre d'étude de la Sexologie et de la Sexualité Humaine, Université Paris 5-René Descartes, Paris, France
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Koga N, Komatsu Y, Shinozaki R, Ishida I, Shimizu Y, Ishimaru S, Kunugi H. Simultaneous monitoring of activity and heart rate variability in depressed patients: A pilot study using a wearable monitor for 3 consecutive days. Neuropsychopharmacol Rep 2022; 42:457-467. [PMID: 35906793 PMCID: PMC9773773 DOI: 10.1002/npr2.12285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 06/30/2022] [Accepted: 07/10/2022] [Indexed: 01/03/2023] Open
Abstract
INTRODUCTION Reduced activity and sleep-wake rhythm disturbances are essential features of depressive episodes. In addition, alterations in heart rate variability (HRV) have been implicated in depression. By using a wearable sensor that monitors 3-dimensional acceleration and HRV simultaneously, we examined the activity and HRV indices in depressive episode of mood disorders. METHODS Participants were 19 patients (13 major depressive disorder [MDD] and 6 bipolar depression; 11 females) and 18 controls (9 females) matched for age and ethnicity (all Japanese) who completed 3 consecutive days of all-day monitoring by a small and light device attached to the chest. RESULTS Activity magnitude was significantly reduced while lying/resting time was increased in depressed patients, compared with controls. When males and females were examined separately, male, but not female, patients showed significant reduction in activity. HRV indices such as R-R interval and high-frequency power (a parameter for the parasympathetic system) were significantly decreased in patients than in controls. Significant differences in activity and HRV indices were seen only in males. Sympathetic load during sleep significantly correlated with damped rest-activity rhythm in depressed patients. LIMITATIONS The number of participants was small, and the majority of the participants were taking psychotropic medications. CONCLUSIONS We obtained evidence for reduced activity, increased lying/resting time, and reduced HRV indices in male depressed patients. The simultaneous monitoring for activity and HRV suggested greater sympathetic load during sleep is associated with damped rest-activity rhythm (increased activity during sleep and decreased daytime activity), which might be a characteristic pathology of depression.
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Affiliation(s)
- Norie Koga
- Department of Mental Disorder Research, National Institute of NeuroscienceNational Center of Neurology and PsychiatryTokyoJapan
| | - Yoko Komatsu
- Comfort Engineering LaboratoryTOYOBO co., Ltd.ShigaJapan
| | | | - Ikki Ishida
- Department of Mental Disorder Research, National Institute of NeuroscienceNational Center of Neurology and PsychiatryTokyoJapan,Department of PsychiatryTeikyo University School of MedicineTokyoJapan
| | - Yusuke Shimizu
- Comfort Engineering LaboratoryTOYOBO co., Ltd.ShigaJapan
| | | | - Hiroshi Kunugi
- Department of Mental Disorder Research, National Institute of NeuroscienceNational Center of Neurology and PsychiatryTokyoJapan,Department of PsychiatryTeikyo University School of MedicineTokyoJapan
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Gilbert P, Basran JK, Raven J, Gilbert H, Petrocchi N, Cheli S, Rayner A, Hayes A, Lucre K, Minou P, Giles D, Byrne F, Newton E, McEwan K. Compassion Focused Group Therapy for People With a Diagnosis of Bipolar Affective Disorder: A Feasibility Study. Front Psychol 2022; 13:841932. [PMID: 35936292 PMCID: PMC9347420 DOI: 10.3389/fpsyg.2022.841932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 03/01/2022] [Indexed: 11/21/2022] Open
Abstract
Background Compassion focused therapy (CFT) is an evolutionary informed, biopsychosocial approach to mental health problems and therapy. It suggests that evolved motives (e.g., for caring, cooperating, competing) are major sources for the organisation of psychophysiological processes which underpin mental health problems. Hence, evolved motives can be targets for psychotherapy. People with certain types of depression are psychophysiologically orientated towards social competition and concerned with social status and social rank. These can give rise to down rank-focused forms of social comparison, sense of inferiority, worthlessness, lowered confidence, submissive behaviour, shame proneness and self-criticism. People with bipolar disorders also experience elevated aspects of competitiveness and up rank status evaluation. These shift processing to a sense of superiority, elevated confidence, energised behaviour, positive affect and social dominance. This is the first study to explore the feasibility of a 12 module CFT group, tailored to helping people with a diagnosis of bipolar disorder understand the impact of evolved competitive, status-regulating motivation on their mental states and the value of cultivating caring and compassion motives and their psychophysiological regulators. Methods Six participants with a history of bipolar disorder took part in a CFT group consisting of 12 modules (over 25 sessions) as co-collaborators to explore their personal experiences of CFT and potential processes of change. Assessment of change was measured via self-report, heart rate variability (HRV) and focus groups over three time points. Results Although changes in self-report scales between participants and across time were uneven, four of the six participants consistently showed improvements across the majority of self-report measures. Heart rate variability measures revealed significant improvement over the course of the therapy. Qualitative data from three focus groups revealed participants found CFT gave them helpful insight into: how evolution has given rise to a number of difficult problems for emotion regulation (called tricky brain) which is not one's fault; an evolutionary understanding of the nature of bipolar disorders; development of a compassionate mind and practices of compassion focused visualisations, styles of thinking and behaviours; addressing issues of self-criticism; and building a sense of a compassionate identity as a means of coping with life difficulties. These impacted their emotional regulation and social relationships. Conclusion Although small, the study provides evidence of feasibility, acceptability and engagement with CFT. Focus group analysis revealed that participants were able to switch from competitive focused to compassion focused processing with consequent improvements in mental states and social behaviour. Participants indicated a journey over time from 'intellectually' understanding the process of building a compassionate mind to experiencing a more embodied sense of compassion that had significant impacts on their orientation to (and working with) the psychophysiological processes of bipolar disorder.
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Affiliation(s)
- Paul Gilbert
- Centre for Compassion Research and Training, College of Health, Psychology and Social Care, University of Derby, Derby, United Kingdom
- The Compassionate Mind Foundation, Derby, United Kingdom
| | - Jaskaran K. Basran
- Centre for Compassion Research and Training, College of Health, Psychology and Social Care, University of Derby, Derby, United Kingdom
- The Compassionate Mind Foundation, Derby, United Kingdom
| | - Joanne Raven
- The Compassionate Mind Foundation, Derby, United Kingdom
| | - Hannah Gilbert
- The Compassionate Mind Foundation, Derby, United Kingdom
- Department of Psychology, University of Roehampton, London, United Kingdom
| | - Nicola Petrocchi
- Department of Economics and Social Sciences, John Cabot University, Rome, Italy
- Compassionate Mind ITALIA, Rome, Italy
| | - Simone Cheli
- School of Human Health Sciences, University of Florence, Florence, Italy
| | - Andrew Rayner
- The Compassionate Mind Foundation, Derby, United Kingdom
| | - Alison Hayes
- Birmingham and Solihull Mental Health NHS Foundation Trust, Birmingham, United Kingdom
| | - Kate Lucre
- Birmingham and Solihull Mental Health NHS Foundation Trust, Birmingham, United Kingdom
| | - Paschalina Minou
- Department of Philosophy, University College London, London, United Kingdom
- College of Health, Psychology and Social Care, University of Derby, Derby, United Kingdom
| | - David Giles
- Lattice Coaching and Training, Chesterfield, United Kingdom
| | - Frances Byrne
- Birmingham and Solihull Mental Health NHS Foundation Trust, Birmingham, United Kingdom
| | - Elizabeth Newton
- College of Health, Psychology and Social Care, University of Derby, Derby, United Kingdom
| | - Kirsten McEwan
- Birmingham and Solihull Mental Health NHS Foundation Trust, Birmingham, United Kingdom
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Cognitive Computing in Mental Healthcare: a Review of Methods and Technologies for Detection of Mental Disorders. Cognit Comput 2022. [DOI: 10.1007/s12559-022-10042-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Kirsch D, Preston A, Tretyak V, Le V, Weber W, Strakowski S, Lippard E. Neural functional connectivity changes to psychosocial stress in young adults with bipolar disorder and preliminary associations with clinical trajectories. Bipolar Disord 2022; 24:298-309. [PMID: 34532945 PMCID: PMC8926937 DOI: 10.1111/bdi.13127] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 07/06/2021] [Accepted: 09/12/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Stress-related mechanisms are implicated in the pathophysiology of bipolar disorder and may contribute to heterogeneity in illness course. Yet, there is a lack of study investigating the neural mechanisms underlying the stress response in this condition. This study investigated changes in amygdala activation and functional connectivity in response to acute psychosocial stress in young adults with bipolar disorder and explored relations with clinical phenotype and prospective mood symptoms. METHODS 42 young adults [19 with bipolar disorder, agemean ± SD =21.4 ± 2.2 years] completed a modified version of the Montreal Imaging Stress Task. Amygdala activation and functional connectivity with prefrontal cortex (PFC) regions of interest was calculated for control and stress conditions. Main effects of group, condition, and group by condition interaction on amygdala activation and connectivity were modeled. A subset of bipolar participants completed 1-year follow-up assessments. Relations between neural responses to stress with concurrent substance use and prospective mood symptoms were explored. RESULTS There were no between-group differences in amygdala activation or functional connectivity during the control condition. Increased right amygdala-right rostral PFC (rPFC) functional connectivity to stress was observed in bipolar disorder, compared to typically developing controls. In bipolar disorder, greater increase in right amygdala-right rPFC functional connectivity to stress was associated with less frequent cannabis use, and prospectively with shorter duration and lower severity of depression symptoms over follow-up. CONCLUSION Results from this preliminary study suggest differences in frontolimbic functional connectivity responses to stress in young adults with bipolar disorder and associations with cannabis use and prospective mood symptoms.
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Affiliation(s)
- D.E. Kirsch
- Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas, Austin, TX, USA,Waggoner Center for Alcohol and Addiction Research, University of Texas, Austin, TX, USA,Institute for Neuroscience, University of Texas, Austin, TX, USA
| | - A. Preston
- Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas, Austin, TX, USA
| | - V. Tretyak
- Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas, Austin, TX, USA,Waggoner Center for Alcohol and Addiction Research, University of Texas, Austin, TX, USA,Department of Psychology, University of Texas, Austin, TX, USA
| | - V. Le
- Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas, Austin, TX, USA
| | - W. Weber
- Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas, Austin, TX, USA
| | - S.M. Strakowski
- Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas, Austin, TX, USA,Waggoner Center for Alcohol and Addiction Research, University of Texas, Austin, TX, USA,Institute for Neuroscience, University of Texas, Austin, TX, USA,Department of Psychology, University of Texas, Austin, TX, USA
| | - E.T.C. Lippard
- Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas, Austin, TX, USA,Waggoner Center for Alcohol and Addiction Research, University of Texas, Austin, TX, USA,Institute for Neuroscience, University of Texas, Austin, TX, USA,Department of Psychology, University of Texas, Austin, TX, USA,Institute of Early Life Adversity Research, University of Texas, Austin, TX, USA
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Berger M, Seemüller F, Voggt A, Obermeier M, Kirchberg F, Löw A, Riedel M, von Schacky C, Severus E. Omega-3 fatty acids in bipolar patients with a low omega-3 index and reduced heart rate variability: the "BIPO-3" trial. Int J Bipolar Disord 2022; 10:9. [PMID: 35362878 PMCID: PMC8975918 DOI: 10.1186/s40345-022-00253-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 01/31/2022] [Indexed: 11/26/2022] Open
Abstract
Background Research suggests that a low omega-3 index may contribute to the low heart rate variability and the increased risk of cardiovascular morbidity and mortality in bipolar disorders. However, so far, no intervention trial with EPA and DHA has been conducted in bipolar patients attempting to increase their heart rate variability. Methods 119 patients with bipolar disorder according to DSM-IV were screened, with 55 euthymic bipolar patients—owing to inclusion criteria (e.g. low omega-3 index (< 6%), SDNN < 60 ms.)—being enrolled in a randomized, double-blind, 12-week parallel study design with omega-3 fatty acids (4 capsules of 530 mg EPA, 150 mg DHA) or corn oil as a placebo, in addition to usual treatment. Heart rate variability as well as the omega-3 index were measured at baseline and at the endpoint of the study. Results A total of 42 patients (omega-3: n = 23, corn oil: n = 19) successfully completed the study after 12 weeks. There was a significant increase in the omega-3 index (value at endpoint minus value at baseline) in the omega-3 group compared to the corn oil group (p < 0.0001). However, there was no significant difference in the change of the SDNN (value at endpoint minus value at baseline) between the treatment groups (p = 0.22). In addition, no correlation between changes in SDNN and change in the omega-3 index could be detected in the omega-3 group (correlation coefficient = 0.02, p = 0.94) or the corn oil group (correlation coefficient = − 0.11, p = 0.91). Similarly, no significant differences between corn oil and omega-3 group regarding the change of LF (p = 0.19), HF (p = 0.34) and LF/HF ratio (p = 0.84) could be demonstrated. Conclusions In our randomized, controlled intervention trial in euthymic bipolar patients with a low omega-3 index and reduced heart rate variability no significant effect of omega-3 fatty acids on SDNN or frequency-domain measures HF, LF and LF/HF ratio could be detected. Possible reasons include, among others, the effect of psychotropic medication present in our trial and/or the genetics of bipolar disorder itself. Further research is needed to test these hypotheses. Trial registration ClinicalTrials.gov, NCT00891826. Registered 01 May 2009–Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT00891826
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Affiliation(s)
| | - Florian Seemüller
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany.,Department of Psychiatry, Psychosomatic and Psychotherapy, Kbo-Lech-Mangfall-Clinic Garmisch-Partenkirchen, Garmisch-Partenkirchen, Germany
| | - Alessandra Voggt
- St. Joseph Krankenhaus, Klinik Für Seelische Gesundheit Im Kindes- Und Jugendalter, Berlin, Germany
| | | | - Franca Kirchberg
- Division of Metabolic and Nutritional Medicine, Dr. Von Hauner Children's Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Anja Löw
- Department of Internal Medicine I - Cardiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Michael Riedel
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany.,Marion Von Tessin Memory-Zentrum gGmbH, Munich, Germany
| | - Clemens von Schacky
- Department of Preventive Cardiology, Ludwig- Maximilians-Universität München, Munich, Germany.,Omegametrix, GmbH, Planegg, Germany
| | - Emanuel Severus
- Department of Psychiatry and Psychotherapy, TU Dresden, Dresden, Germany.
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Associations between Heart Rate Variability and Brain Activity during a Working Memory Task: A Preliminary Electroencephalogram Study on Depression and Anxiety Disorder. Brain Sci 2022; 12:brainsci12020172. [PMID: 35203935 PMCID: PMC8870686 DOI: 10.3390/brainsci12020172] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/24/2022] [Accepted: 01/25/2022] [Indexed: 01/02/2023] Open
Abstract
Heart rate variability (HRV) has been suggested to reflect executive function and related neural activity. Executive dysfunction has been suggested to play an important role in the pathophysiology of emotional disorders. The purpose of this study was to investigate whether HRV showed a significant correlation with electroencephalogram (EEG) during a working memory performance in patients with depressive or anxiety disorder. A retrospective analysis was conducted with data from 61 patients with depressive disorder (43 women and 18 men) and 59 patients with anxiety disorder (35 women and 24 men). HRV was measured in the resting state, and EEG was recorded in the resting state and during the execution of a working memory task. It was performed in patients with depressive and anxiety disorder, and the paired sample t-test between resting state and task performance, as well as the partial correlation analysis between HRV and EEG, was conducted. Both depressed and anxious patients showed weaker beta relative power during the working memory task compared to the rest period. The resting-state EEG did not correlate with HRV parameters in both groups. In depressed patients, HRV showed a positive correlation with delta power during the task and a negative correlation with beta relative power during the task. In patients with anxiety disorder, HRV showed a significant positive correlation with theta power of the right frontal region during the task. Our results suggest that HRV would be related to executive-function-related neural activity in patients with depressive or anxiety disorder. Future studies with more subjects, including healthy controls, are needed to verify the correlation between HRV and EEG and to come up with a more comprehensive picture of neurobiological changes in emotional disorders.
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Mutz J, Young AH, Lewis CM. Age-related changes in physiology in individuals with bipolar disorder. J Affect Disord 2022; 296:157-168. [PMID: 34601303 DOI: 10.1016/j.jad.2021.09.027] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 08/02/2021] [Accepted: 09/12/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND Individuals with bipolar disorder have a reduced life expectancy and may experience accelerated biological ageing. In individuals with bipolar disorder and healthy controls, we examined differences in age-related changes in physiology. METHODS UK Biobank recruited more than 500,000 participants, aged 37-73, between 2006 and 2010. Generalised additive models were used to examine associations between age and grip strength, cardiovascular function, body composition, lung function and heel bone mineral density. RESULTS The main dataset included 271,118 adults (mean age = 56.04 years; 49.60% females). We found statistically significant differences between cases and controls for grip strength, blood pressure, pulse rate and body composition, with standardised mean differences of up to -0.24 (95% CI -0.28 to -0.19). Evidence of differences in lung function, heel bone mineral density or arterial stiffness was limited. Case-control differences were most evident for age-related changes in cardiovascular function (both sexes) and body composition (females). Differences did not uniformly narrow or widen with age and differed by sex. For example, the difference in systolic blood pressure between male cases and controls was -1.3 mmHg at age 50 and widened to -4.7 mmHg at age 65. Diastolic blood pressure in female cases was 1.2 mmHg higher at age 40 and -1.2 mmHg lower at age 65. LIMITATIONS Analyses did not distinguish between bipolar disorder subtypes. Results may not generalise to other age groups. CONCLUSIONS Differences between bipolar disorder cases and controls were most evident for cardiovascular and body composition measures. Targeted screening for cardiovascular and metabolic health in middle age is warranted to potentially mitigate excess mortality.
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Affiliation(s)
- Julian Mutz
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
| | - Allan H Young
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, Monks Orchard Road, Beckenham, Kent, UK
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Department of Medical and Molecular Genetics, Faculty of Life Sciences & Medicine, King's College London, London, UK
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Heart rate variability is associated with disease severity in psychosis spectrum disorders. Prog Neuropsychopharmacol Biol Psychiatry 2021; 111:110108. [PMID: 32946948 DOI: 10.1016/j.pnpbp.2020.110108] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 09/09/2020] [Accepted: 09/11/2020] [Indexed: 12/19/2022]
Abstract
While a growing literature links cardiac autonomic dysregulation to a variety of psychiatric disorders, the relationship between cardiac autonomic functioning and specific symptoms in schizophrenia (SZ) and bipolar disorder (BD) remains elusive. Thus, we investigated heart rate variability (HRV), a proxy for vagal activity, as a biological marker for symptom severity in patients with SZ and BD. HRV was calculated in 35 patients with SZ and 52 patients with BD, as well as in 149 healthy controls. In the patient groups, symptom severity and function were measured by the Positive and Negative Syndrome Scale (PANSS) and the Global Assessment of Functioning (GAF) scale. Results showed that HRV was significantly lower in both clinical groups compared to the healthy controls, with no significant HRV differences between patient groups. PANSS general psychopathology scores, GAF symptom scores, and GAF function scores showed statistically significant associations with HRV across groups. These results suggest that disease severity is associated with autonomic dysfunction and that HRV may provide a potential biomarker of disease severity in SZ and BD.
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Li Y, Wang J, Li X, Jing W, Omorodion I, Liu L. Association Between Heart Rate Variability and Parkinson's Disease: A Meta-analysis. Curr Pharm Des 2021; 27:2056-2067. [PMID: 32888281 DOI: 10.2174/1871527319666200905122222] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 07/25/2020] [Indexed: 11/22/2022]
Abstract
AIM A systematic review which aims to assess the evidence regarding the function of the autonomic heart rate regulation system among Parkinson's disease (PD) patients. The main objective of the study is to compare heart rate variability (HRV) between those with and without PD from published studies. The subgroup analyses aimed to investigate the impact of treatment and disease duration on heart rate variability (HRV), assessed by measuring sympathetic and parasympathetic activity via low-frequency (LF) and high-frequency (HF) power spectrum scores, in patients with Parkinson's disease (PD). METHODS PubMed, Cochrane Library, Embase and Web of Science were searched using the keywords "Parkinson's disease" and "heart rate variability". Studies that reported at least one HRV variable were included. The quality of the included studies was evaluated, and the relevant information was extracted. A meta-analysis was carried out with Stata software. We followed the PRISMA guidelines for all stages of the meta-analysis. PROSPERO registration number: CRD42021242766. RESULTS Thirteen references (16 studies) were included in our analysis. The LF values (g -0.27; 95% confidence interval (CI) -0.53 to -0.01) of the patients with PD were lower than the controls. No significant differences in HF values (g -0.11; 95% CI -0.28 to 0.06) were observed between groups. Subgroup analyses of HRV outcomes in patients stratified by treatment status and disease duration were performed. For LF, patients with a disease duration of less than 5 years presented lower HF (g -0.25; 95% CI -0.44 to -0.06) values than controls. Regarding HF, patients receiving treatment presented lower HF (g -0.22; 95% CI -0.40 to 0.05) values than controls, and patients with a disease duration greater than 5 years also presented lower HF (g -0.29; 95% CI -0.56 to -0.03) values than controls. DISCUSSION We have confirmed and elaborated on the hypothesis of sympathovagal imbalance in PD. Knowledge of the effect of sympathovagal balance on HRV may inform the design of therapeutic regimens for PD. However, between-study heterogeneity and methodological issues limit the generalizability of the evidence; thus, future studies employing strict methodologies are warranted. CONCLUSION Our meta-analysis found that PD is associated with reduced HRV values, which indicates that both sympathetic and vagal activities are decreased. Patients in the early stage of PD have sympathetic autonomic nerve dysfunction, with only minor damage to sympathetic activity.
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Affiliation(s)
- Yuan Li
- Department of Neurology of Shanxi Bethune Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China
| | | | - Xinyi Li
- Department of Neurology of Shanxi Bethune Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China
| | - Wei Jing
- Department of Neurology of Shanxi Bethune Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China
| | - Itohan Omorodion
- University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - Lei Liu
- University of Virginia School of Medicine, Charlottesville, Virginia, United States
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Weiner L, Guidi A, Doignon-Camus N, Giersch A, Bertschy G, Vanello N. Vocal features obtained through automated methods in verbal fluency tasks can aid the identification of mixed episodes in bipolar disorder. Transl Psychiatry 2021; 11:415. [PMID: 34341338 PMCID: PMC8329226 DOI: 10.1038/s41398-021-01535-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 07/05/2021] [Accepted: 07/26/2021] [Indexed: 02/07/2023] Open
Abstract
There is a lack of consensus on the diagnostic thresholds that could improve the detection accuracy of bipolar mixed episodes in clinical settings. Some studies have shown that voice features could be reliable biomarkers of manic and depressive episodes compared to euthymic states, but none thus far have investigated whether they could aid the distinction between mixed and non-mixed acute bipolar episodes. Here we investigated whether vocal features acquired via verbal fluency tasks could accurately classify mixed states in bipolar disorder using machine learning methods. Fifty-six patients with bipolar disorder were recruited during an acute episode (19 hypomanic, 8 mixed hypomanic, 17 with mixed depression, 12 with depression). Nine different trials belonging to four conditions of verbal fluency tasks-letter, semantic, free word generation, and associational fluency-were administered. Spectral and prosodic features in three conditions were selected for the classification algorithm. Using the leave-one-subject-out (LOSO) strategy to train the classifier, we calculated the accuracy rate, the F1 score, and the Matthews correlation coefficient (MCC). For depression versus mixed depression, the accuracy and F1 scores were high, i.e., respectively 0.83 and 0.86, and the MCC was of 0.64. For hypomania versus mixed hypomania, accuracy and F1 scores were also high, i.e., 0.86 and 0.75, respectively, and the MCC was of 0.57. Given the high rates of correctly classified subjects, vocal features quickly acquired via verbal fluency tasks seem to be reliable biomarkers that could be easily implemented in clinical settings to improve diagnostic accuracy.
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Affiliation(s)
- Luisa Weiner
- INSERM 1114, Strasbourg, France. .,University Hospital of Strasbourg, Strasbourg, France. .,Laboratoire de Psychologie des Cognitions, Université de Strasbourg, Strasbourg, France.
| | - Andrea Guidi
- grid.5395.a0000 0004 1757 3729Dipartimento di Ingegneria dell’Informazione, University of Pisa, Via G. Caruso 16, 56122 Pisa, Italy ,grid.5395.a0000 0004 1757 3729Research Center “E. Piaggio”, University of Pisa, Largo L, Lazzarino 1, 56122 Pisa, Italy
| | | | - Anne Giersch
- grid.7429.80000000121866389INSERM 1114, Strasbourg, France
| | - Gilles Bertschy
- grid.7429.80000000121866389INSERM 1114, Strasbourg, France ,grid.412220.70000 0001 2177 138XUniversity Hospital of Strasbourg, Strasbourg, France ,grid.11843.3f0000 0001 2157 9291Fédération de Médecine Translationnelle de Strasbourg, Université de Strasbourg, Strasbourg, France
| | - Nicola Vanello
- grid.5395.a0000 0004 1757 3729Dipartimento di Ingegneria dell’Informazione, University of Pisa, Via G. Caruso 16, 56122 Pisa, Italy ,grid.5395.a0000 0004 1757 3729Research Center “E. Piaggio”, University of Pisa, Largo L, Lazzarino 1, 56122 Pisa, Italy
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Zenker M, Venz J, Koenig J, Voss C, Beesdo-Baum K, Pieper L. Evidence for the association between physiological and emotional states in adolescents and young adults without psychopathology under ecologically valid conditions. Psychophysiology 2021; 58:e13902. [PMID: 34286859 DOI: 10.1111/psyp.13902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 06/20/2021] [Accepted: 06/29/2021] [Indexed: 11/29/2022]
Abstract
Well-powered studies on the physiological concomitants underlying affect and its regulation during emerging adulthood are warranted to provide novel insight into mental health. The association between autonomic nervous system activity and emotional states occurring under natural conditions in daily life was investigated in individuals (N = 549, age 14-21, females 45.6%) without any lifetime mental disorder from an epidemiological cohort study in Germany. Using ecological momentary assessment, mood and optimism/pessimism were assessed over 4 days simultaneously with continuous heart rate monitoring. Lower vagal activity was found in mood states accompanied by high arousal (wakefulness, mania) and greater vagal activity in mood states with low arousal (calmness, pessimism). Findings illustrate important associations between autonomic nervous system activity and mood in youth under ecologically valid conditions. Vagal activity presents a prominent pathway by which mood may influence physiological function or vice versa. In contrast to commonly performed laboratory assessments, the ambulatory assessment in participants' daily life allows an application of the results to the field.
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Affiliation(s)
- Monique Zenker
- Behavioral Epidemiology, Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - John Venz
- Behavioral Epidemiology, Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany.,Center for Clinical Epidemiology and Longitudinal Studies (CELOS), Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Julian Koenig
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Medical Faculty, University of Cologne, Cologne, Germany.,Clinic and Polyclinic for Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Cologne, Cologne, Germany
| | - Catharina Voss
- Behavioral Epidemiology, Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Katja Beesdo-Baum
- Behavioral Epidemiology, Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany.,Center for Clinical Epidemiology and Longitudinal Studies (CELOS), Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Lars Pieper
- Behavioral Epidemiology, Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany.,Center for Clinical Epidemiology and Longitudinal Studies (CELOS), Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany
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Wu G, Liu H, Wu S, Liu G, Liang C. Can Heart Rate Variability (HRV) Be Used as a Biomarker of Thermal Comfort for Mine Workers? INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18147615. [PMID: 34300066 PMCID: PMC8306794 DOI: 10.3390/ijerph18147615] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Revised: 07/10/2021] [Accepted: 07/14/2021] [Indexed: 11/16/2022]
Abstract
This study aimed to determine whether heart rate variability (HRV) can express the thermal comfort of mine workers. Eight subjects ran on a treadmill (5.5 km/h) to simulate heavy labor in three kinds of mining environments (22 °C/90%, 26 °C/90%, 30 °C/90%), respectively. Based on the measured electrocardiogram (ECG) data, the HRV of the subjects was calculated. The results showed that the HRV indices changed obviously under different temperature environments. In the neutral and hot environment, except for the LF, TP and LF/HF, there were significant differences in each index. However, there was no significant difference between the cold and neutral environments. The R-R intervals, the very low-frequency power (VLF), pNN20 and SampEN had strong negative correlation with the thermal sensation of people from sitting to work (ρ < −0.700). These indices may be used as thermal comfort predictive biomarkers of mine workers.
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Affiliation(s)
- Guoshan Wu
- School of Resource & Environment and Safety Engineering, Hunan University of Science and Technology, Xiangtan 411201, China; (S.W.); (G.L.)
- School of Energy and Building Environment Engineering, Guilin University of Aerospace Technology, Guilin 541004, China
- Correspondence: (G.W.); (H.L.); Tel.: +86-731-58290280 (G.W.)
| | - Heqing Liu
- School of Resource & Environment and Safety Engineering, Hunan University of Science and Technology, Xiangtan 411201, China; (S.W.); (G.L.)
- Correspondence: (G.W.); (H.L.); Tel.: +86-731-58290280 (G.W.)
| | - Shixian Wu
- School of Resource & Environment and Safety Engineering, Hunan University of Science and Technology, Xiangtan 411201, China; (S.W.); (G.L.)
- School of Energy and Building Environment Engineering, Guilin University of Aerospace Technology, Guilin 541004, China
| | - Guanglei Liu
- School of Resource & Environment and Safety Engineering, Hunan University of Science and Technology, Xiangtan 411201, China; (S.W.); (G.L.)
| | - Caihang Liang
- School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, China;
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Ortiz A, Bradler K, Moorti P, MacLean S, Husain MI, Sanches M, Goldstein BI, Alda M, Mulsant BH. Reduced heart rate variability is associated with higher illness burden in bipolar disorder. J Psychosom Res 2021; 145:110478. [PMID: 33820643 DOI: 10.1016/j.jpsychores.2021.110478] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/16/2021] [Accepted: 03/27/2021] [Indexed: 01/17/2023]
Abstract
BACKGROUND Bipolar disorder (BD) is associated with premature death and ischemic heart disease is the main cause of excess mortality. Heart rate variability (HRV) predicts mortality in patients with or without cardiovascular disease. While several studies have analyzed the association between HRV and BD, none has analyzed the association of HRV with illness burden in BD. METHODS 53 participants with BD I and II used a wearable device to assess the association between HRV and factors characterizing illness burden, including illness duration, number and type of previous episode(s), duration of the most severe episode, history of suicide attempts or psychotic symptoms during episodes, and co-morbid psychiatric disorders. We ran unadjusted models and models controlling statistically for age, sex, pharmacotherapy, baseline functional cardiovascular capacity, BMI, years of education, and marital status. We also explored the association between HRV and an overall illness burden index (IBI) integrating all these factors using a weighted geometric mean. RESULTS Adjusted and unadjusted models had similar results. Longer illness duration, higher number of depressive episodes, longer duration of most severe manic/hypomanic episode, co-morbid anxiety disorders, and family history of suicide were associated with reduced HRV, as was bipolar depression severity in the participants experiencing a depressive episode. Finally, a higher IBI score was associated with lower HRV. CONCLUSIONS High illness burden is associated with reduced HRV in BD. While the IBI needs to be validated in a larger sample, it may provide an overall measure that captures illness burden in BD.
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Affiliation(s)
- Abigail Ortiz
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada.
| | | | - Pooja Moorti
- Institute for Mental Health Research, The Royal Ottawa Hospital, Ottawa, ON, Canada
| | - Stephane MacLean
- Institute for Mental Health Research, The Royal Ottawa Hospital, Ottawa, ON, Canada
| | - M Ishrat Husain
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Marcos Sanches
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Benjamin I Goldstein
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada; National Institute of Mental Health, Klecany, Czech Republic
| | - Benoit H Mulsant
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada
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Analysis of Gender Differences in HRV of Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Mobile-Health Technology. SENSORS 2021; 21:s21113746. [PMID: 34071326 PMCID: PMC8197911 DOI: 10.3390/s21113746] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 05/20/2021] [Accepted: 05/22/2021] [Indexed: 01/09/2023]
Abstract
In a previous study using mobile-health technology (mHealth), we reported a robust association between chronic fatigue symptoms and heart rate variability (HRV) in female patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). This study explores HRV analysis as an objective, non-invasive and easy-to-apply marker of ME/CFS using mHealth technology, and evaluates differential gender effects on HRV and ME/CFS core symptoms. In our methodology, participants included 77 ME/CFS patients (32 men and 45 women) and 44 age-matched healthy controls (19 men and 25 women), all self-reporting subjective scores for fatigue, sleep quality, anxiety, and depression, and neurovegetative symptoms of autonomic dysfunction. The inter-beat cardiac intervals are continuously monitored/recorded over three 5-min periods, and HRV is analyzed using a custom-made application (iOS) on a mobile device connected via Bluetooth to a wearable cardiac chest band. Male ME/CFS patients show increased scores compared with control men in all symptoms and scores of fatigue, and autonomic dysfunction, as with women in the first study. No differences in any HRV parameter appear between male ME/CFS patients and controls, in contrast to our findings in women. However, we have found negative correlations of ME/CFS symptomatology with cardiac variability (SDNN, RMSSD, pNN50, LF) in men. We have also found a significant relationship between fatigue symptomatology and HRV parameters in ME/CFS patients, but not in healthy control men. Gender effects appear in HF, LF/HF, and HFnu HRV parameters. A MANOVA analysis shows differential gender effects depending on the experimental condition in autonomic dysfunction symptoms and HF and HFnu HRV parameters. A decreased HRV pattern in ME/CFS women compared to ME/CFS men may reflect a sex-related cardiac autonomic dysfunction in ME/CFS illness that could be used as a predictive marker of disease progression. In conclusion, we show that HRV analysis using mHealth technology is an objective, non-invasive tool that can be useful for clinical prediction of fatigue severity, especially in women with ME/CFS.
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Teixeira E, Fonseca H, Diniz-Sousa F, Veras L, Boppre G, Oliveira J, Pinto D, Alves AJ, Barbosa A, Mendes R, Marques-Aleixo I. Wearable Devices for Physical Activity and Healthcare Monitoring in Elderly People: A Critical Review. Geriatrics (Basel) 2021; 6:38. [PMID: 33917104 PMCID: PMC8167657 DOI: 10.3390/geriatrics6020038] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 03/25/2021] [Accepted: 04/02/2021] [Indexed: 01/22/2023] Open
Abstract
The availability of wearable devices (WDs) to collect biometric information and their use during activities of daily living is significantly increasing in the general population. These small electronic devices, which record fitness and health-related outcomes, have been broadly utilized in industries such as medicine, healthcare, and fitness. Since they are simple to use and progressively cheaper, they have also been used for numerous research purposes. However, despite their increasing popularity, most of these WDs do not accurately measure the proclaimed outcomes. In fact, research is equivocal about whether they are valid and reliable methods to specifically evaluate physical activity and health-related outcomes in older adults, since they are mostly designed and produced considering younger subjects' physical and mental characteristics. Additionally, their constant evolution through continuous upgrades and redesigned versions, suggests the need for constant up-to-date reviews and research. Accordingly, this article aims to scrutinize the state-of-the-art scientific evidence about the usefulness of WDs, specifically on older adults, to monitor physical activity and health-related outcomes. This critical review not only aims to inform older consumers but also aid researchers in study design when selecting physical activity and healthcare monitoring devices for elderly people.
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Affiliation(s)
- Eduardo Teixeira
- Research Centre in Physical Activity, Health, and Leisure (CIAFEL), Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
- Faculty of Psychology, Education and Sports, Lusófona University of Porto, 4000-098 Porto, Portugal
- Escola Superior Desporto e Lazer, Instituto Politécnico de Viana do Castelo, 4900-347 Viana do Castelo, Portugal
- Laboratory for Integrative and Translational Research in Population Health (ITR), 4050-600 Porto, Portugal
| | - Hélder Fonseca
- Research Centre in Physical Activity, Health, and Leisure (CIAFEL), Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
- Laboratory for Integrative and Translational Research in Population Health (ITR), 4050-600 Porto, Portugal
| | - Florêncio Diniz-Sousa
- Research Centre in Physical Activity, Health, and Leisure (CIAFEL), Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
- Laboratory for Integrative and Translational Research in Population Health (ITR), 4050-600 Porto, Portugal
| | - Lucas Veras
- Research Centre in Physical Activity, Health, and Leisure (CIAFEL), Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
- Laboratory for Integrative and Translational Research in Population Health (ITR), 4050-600 Porto, Portugal
| | - Giorjines Boppre
- Research Centre in Physical Activity, Health, and Leisure (CIAFEL), Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
- Laboratory for Integrative and Translational Research in Population Health (ITR), 4050-600 Porto, Portugal
| | - José Oliveira
- Research Centre in Physical Activity, Health, and Leisure (CIAFEL), Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
- Laboratory for Integrative and Translational Research in Population Health (ITR), 4050-600 Porto, Portugal
| | - Diogo Pinto
- Research Center in Sports Sciences, Health Sciences and Human Development (CIDESD), University Institute of Maia, 4475-690 Maia, Portugal
| | - Alberto Jorge Alves
- Research Center in Sports Sciences, Health Sciences and Human Development (CIDESD), University Institute of Maia, 4475-690 Maia, Portugal
| | - Ana Barbosa
- Laboratory for Integrative and Translational Research in Population Health (ITR), 4050-600 Porto, Portugal
- EPIUnit-Instituto de Saúde Pública, Universidade do Porto, 4050-091 Porto, Portugal
| | - Romeu Mendes
- Laboratory for Integrative and Translational Research in Population Health (ITR), 4050-600 Porto, Portugal
- EPIUnit-Instituto de Saúde Pública, Universidade do Porto, 4050-091 Porto, Portugal
- Northern Region Health Administration, 4000-477 Porto, Portugal
| | - Inês Marques-Aleixo
- Research Centre in Physical Activity, Health, and Leisure (CIAFEL), Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
- Faculty of Psychology, Education and Sports, Lusófona University of Porto, 4000-098 Porto, Portugal
- Laboratory for Integrative and Translational Research in Population Health (ITR), 4050-600 Porto, Portugal
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Lemogne C, Blacher J, Airagnes G, Hoertel N, Czernichow S, Danchin N, Meneton P, Limosin F, Fiedorowicz JG. Management of Cardiovascular Health in People with Severe Mental Disorders. Curr Cardiol Rep 2021; 23:7. [PMID: 33409804 DOI: 10.1007/s11886-020-01436-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/18/2020] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW To review evidence regarding the association between bipolar disorder and schizophrenia, henceforth referred to as severe mental disorders (SMD), and cardiovascular morbidity and mortality, its mechanisms, and the interventions to reduce this burden. RECENT FINDINGS Much of the loss in life expectancy in people with SMD remains driven by cardiovascular mortality. Antipsychotics and mood stabilizers are associated with negative cardio-metabolic outcomes, but large inter-individual differences are observed, and not treating SMD might be associated with even greater cardiovascular mortality. Classical modifiable cardiovascular risk factors remained inadequately screened and, once identified, too seldom treated in people with SMD. After a myocardial infarction, aggressive tertiary prevention may be as effective in people with SMD as in the general population but is less prescribed. Reduced healthcare quality and increased prevalence of cardiovascular risk factors may not fully explain the excess cardiovascular mortality associated with SMDs, which themselves should be considered risk factors in risk calculators. Hazardous health behaviors, the cardio-metabolic adverse effects of medications, and a reduced access to quality healthcare remain priority targets for intervention.
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Affiliation(s)
- Cédric Lemogne
- Université de Paris, AP-HP, Hôpital Hôtel-Dieu, DMU Psychiatrie et Addictologie, Service de Psychiatrie de l'adulte, INSERM, Institut de Psychiatrie et Neurosciences de Paris (IPNP), UMR_S1266, Paris, France.
| | - Jacques Blacher
- Université de Paris, AP-HP, Hôpital Hôtel-Dieu, Centre de Diagnostic et de Thérapeutique, Paris, France
| | - Guillaume Airagnes
- Université de Paris, AP-HP, Hôpital européen Georges-Pompidou, DMU Psychiatrie et Addictologie, Centre Ambulatoire d'Addictologie, INSERM, UMS 011 Cohortes Epidémiologiques en Population, Paris, France
| | - Nicolas Hoertel
- Université de Paris, AP-HP, Hôpital Corentin-Celton, DMU Psychiatrie et Addictologie, Service de Psychiatrie de l'adulte et du sujet âgé, INSERM, Institut de Psychiatrie et Neurosciences de Paris (IPNP), UMR_S1266, Issy-les-Moulineaux, France
| | - Sébastien Czernichow
- Université de Paris, AP-HP, Hôpital européen Georges-Pompidou, Service de Nutrition, Paris, France
| | - Nicolas Danchin
- Université de Paris, AP-HP, Hôpital européen Georges-Pompidou, Service de Cardiologie, Paris, France
| | - Pierre Meneton
- INSERM U1142 LIMICS, UMRS 1142, Sorbonne Universities, UPMC University of Paris 06, University of Paris 13, Paris, France
| | - Frédéric Limosin
- Université de Paris, AP-HP, Hôpital Corentin-Celton, DMU Psychiatrie et Addictologie, Service de Psychiatrie de l'adulte et du sujet âgé, INSERM, Institut de Psychiatrie et Neurosciences de Paris (IPNP), UMR_S1266, Issy-les-Moulineaux, France
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45
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Biometric Data as Real-Time Measure of Physiological Reactions to Environmental Stimuli in the Built Environment. ENERGIES 2021. [DOI: 10.3390/en14010232] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
The physiological and cognitive effects of environmental stimuli from the built environment on humans have been studied for more than a century, over short time frames in terms of comfort, and over long-time frames in terms of health and wellbeing. The strong interdependence of objective and subjective factors in these fields of study has traditionally involved the necessity to rely on a number of qualitative sources of information, as self-report variables, which however, raise criticisms concerning their reliability and precision. Recent advancements in sensing technology and data processing methodologies have strongly contributed towards a renewed interest in biometric data as a potential high-precision tool to study the physiological effects of selected stimuli on humans using more objective and real-time measures. Within this context, this review reports on a broader spectrum of available and advanced biosensing techniques used in the fields of building engineering, human physiology, neurology, and psychology. The interaction and interdependence between (i) indoor environmental parameters and (ii) biosignals identifying human physiological response to the environmental stressors are systematically explored. Online databases ScienceDirect, Scopus, MDPI and ResearchGate were scanned to gather all relevant publications in the last 20 years, identifying and listing tools and methods of biometric data collection, assessing the potentials and drawbacks of the most relevant techniques. The review aims to support the introduction of biomedical signals as a tool for understanding the physiological aspects of indoor comfort in the view of achieving an improved balance between human resilience and building resilience, addressing human indoor health as well as energetic and environmental building performance.
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Moshe I, Terhorst Y, Opoku Asare K, Sander LB, Ferreira D, Baumeister H, Mohr DC, Pulkki-Råback L. Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data. Front Psychiatry 2021; 12:625247. [PMID: 33584388 PMCID: PMC7876288 DOI: 10.3389/fpsyt.2021.625247] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 01/07/2021] [Indexed: 11/16/2022] Open
Abstract
Background: Depression and anxiety are leading causes of disability worldwide but often remain undetected and untreated. Smartphone and wearable devices may offer a unique source of data to detect moment by moment changes in risk factors associated with mental disorders that overcome many of the limitations of traditional screening methods. Objective: The current study aimed to explore the extent to which data from smartphone and wearable devices could predict symptoms of depression and anxiety. Methods: A total of N = 60 adults (ages 24-68) who owned an Apple iPhone and Oura Ring were recruited online over a 2-week period. At the beginning of the study, participants installed the Delphi data acquisition app on their smartphone. The app continuously monitored participants' location (using GPS) and smartphone usage behavior (total usage time and frequency of use). The Oura Ring provided measures related to activity (step count and metabolic equivalent for task), sleep (total sleep time, sleep onset latency, wake after sleep onset and time in bed) and heart rate variability (HRV). In addition, participants were prompted to report their daily mood (valence and arousal). Participants completed self-reported assessments of depression, anxiety and stress (DASS-21) at baseline, midpoint and the end of the study. Results: Multilevel models demonstrated a significant negative association between the variability of locations visited and symptoms of depression (beta = -0.21, p = 0.037) and significant positive associations between total sleep time and depression (beta = 0.24, p = 0.023), time in bed and depression (beta = 0.26, p = 0.020), wake after sleep onset and anxiety (beta = 0.23, p = 0.035) and HRV and anxiety (beta = 0.26, p = 0.035). A combined model of smartphone and wearable features and self-reported mood provided the strongest prediction of depression. Conclusion: The current findings demonstrate that wearable devices may provide valuable sources of data in predicting symptoms of depression and anxiety, most notably data related to common measures of sleep.
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Affiliation(s)
- Isaac Moshe
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Yannik Terhorst
- Department of Research Methods, Ulm University, Ulm, Germany.,Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, Ulm University, Ulm, Germany
| | | | - Lasse Bosse Sander
- Department of Rehabilitation Psychology and Psychotherapy, Institute of Psychology, University of Freiburg, Freiburg, Germany
| | - Denzil Ferreira
- Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
| | - Harald Baumeister
- Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, Ulm University, Ulm, Germany
| | - David C Mohr
- Department of Preventive Medicine, Center for Behavioral Intervention Technologies, Northwestern University, Chicago, IL, United States
| | - Laura Pulkki-Råback
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
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Lee D, Baek JH, Cho YJ, Hong KS. Association of Resting Heart Rate and Heart Rate Variability With Proximal Suicidal Risk in Patients With Diverse Psychiatric Diagnoses. Front Psychiatry 2021; 12:652340. [PMID: 33995148 PMCID: PMC8121144 DOI: 10.3389/fpsyt.2021.652340] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 04/06/2021] [Indexed: 11/23/2022] Open
Abstract
Objectively measurable biomarkers have not been applied for suicide risk prediction. Resting heart rate (HR) and heart rate variability (HRV) showed potential as trans-diagnostic markers associated with suicide. This study aimed to investigate the associations of resting HR and HRV on proximal suicide risk in patients with diverse psychiatric diagnoses. This chart review study used the medical records of psychiatric patients who visited the outpatient clinic at an academic tertiary hospital. A total of 1,461 patients with diverse psychiatric diagnoses was included in the analysis. Proximal suicide risk was measured using the Mini-International Neuropsychiatric Interview (MINI) suicidal score. Linear regression analyses with the MINI suicidal score as a dependent variable and binary logistic regression analyses with moderate-to-high suicide risk (MINI suicidal risk score ≥6) as a dependent variable were conducted to explore the effects of resting HR and HRV parameters on acute suicide risk after adjusting for age, sex, presence of major depressive disorder (MDD) and bipolar disorder (BD), severity of depression and anxiety severity. We found that 55 (34.6%) patients in the MDD group, 40 (41.7%) in the BD group and 36 (3.9%) in the others group reported moderate-to-high suicide risk. Linear regression analysis revealed that both resting HR and root-mean-square of successive difference (RMSSD) had significant associations with the MINI suicidal score (P = 0.037 with HR, P = 0.003 with RMSSD). In logistic regression, only RMSSD showed a significant association with moderate-to-high suicide risk (P = 0.098 with HR, P = 0.019 with RMSSD), which remained significant in subgroup analysis with patients who reported any suicide-related symptom (MINI suicidal score >0; n = 472; P = 0.017 with HR, P = 0.012 with RMSSD). Our study findings suggest the potential for resting HR and RMSSD as biomarkers for proximal suicide risk prediction. Further research with longitudinal evaluation is needed to confirm our study findings.
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Affiliation(s)
- Dongbin Lee
- Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Ji Hyun Baek
- Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Yun Ji Cho
- Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Kyung Sue Hong
- Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
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Heiss S, Vaschillo B, Vaschillo EG, Timko CA, Hormes JM. Heart rate variability as a biobehavioral marker of diverse psychopathologies: A review and argument for an "ideal range". Neurosci Biobehav Rev 2020; 121:144-155. [PMID: 33309905 DOI: 10.1016/j.neubiorev.2020.12.004] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 12/02/2020] [Indexed: 01/21/2023]
Abstract
Heart rate variability (HRV), a measure of the variability in intervals between subsequent heart beats, is now widely considered an index of emotion regulatory capacity and the ability to adapt flexibly to changing environmental demands. Abnormalities in HRV are implicated in a host of psychopathologies, making it a potentially powerful transdiagnostic biobehavioral change mechanism in treatment interventions. While most mental illnesses are associated with low HRV, eating disorders have been linked to elevated HRV. We examined 62 research articles on HRV in psychopathology to test the hypothesis that there is an "ideal range" of HRV that predicts optimal functioning. Relationships between symptom severity and parameters that quantify HRV were examined graphically. More extreme time-domain HRV measures, both high and low, were associated with psychopathology, whereas healthy controls displayed mid-range values. Findings preliminarily support the hypothesis that there is an "ideal range" of HRV that could be targeted in biofeedback interventions.
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Affiliation(s)
- Sydney Heiss
- Department of Psychology, University at Albany, State University of New York, USA.
| | - Bronya Vaschillo
- Department of Kinesiology and Health, Rutgers, The State University of New Jersey, USA
| | - Evgeny G Vaschillo
- Department of Kinesiology and Health, Rutgers, The State University of New Jersey, USA
| | - C Alix Timko
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, The Children's Hospital of Philadelphia, USA
| | - Julia M Hormes
- Department of Psychology, University at Albany, State University of New York, USA
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Gregório ML, Wazen GLL, Kemp AH, Milan-Mattos JC, Porta A, Catai AM, de Godoy MF. Non-linear analysis of the heart rate variability in characterization of manic and euthymic phases of bipolar disorder. J Affect Disord 2020; 275:136-144. [PMID: 32658816 DOI: 10.1016/j.jad.2020.07.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 06/18/2020] [Accepted: 07/05/2020] [Indexed: 01/25/2023]
Abstract
BACKGROUND - Bipolar Disorder (BD) has been associated with autonomic nervous system (ANS) dysregulation, with a consequent increase in mortality. Recent work highlights the non-linear analysis of ANS function. Our objective was to compare ANS modulation using recurrence plots (RP) and symbolic analysis (SA) in manic and euthymic phases of BD to controls. METHODS - Eighteen male patients (33.1 ± 12.0 years) were assessed during mania and at discharge in the euthymic phase compared and to a healthy group matched by age (33.9 ± 10.8 years). Electrocardiographic series (1000 RR intervals, at rest, in supine position) were captured using Polar Advantage RS800CX equipment and Heart Rate Variability (HRV) was analysed using RP and SA. Statistical analysis was performed using ANOVA with Tukey's post-test. The threshold for statistical significance was set at P < 0.05 and Cohen's d effect size was also quantified considering d > 0.8 as an important effect. The study was registered into the Clinical Trials Registration (ClinicalTrials.gov: NCT01272518). RESULTS Manic group presented significantly higher linearity before treatment (P<0.05) compared to controls considering RP variables. Cohen's d values had a large effect size ranging from 0.888 to 1.227. In the manic phase, SA showed predominance of the sympathetic component (OV%) with reduction of the parasympathetic component (2LV% and 2UV%) with reversion post treatment including higher Shannon Entropy (SE) indicating higher complexity. LIMITATIONS - short follow-up (1 month) and small number of patients. CONCLUSIONS - Non-linear analyzes may be used as supplementary tools for understanding autonomic function in BD during mania and after drug treatment.
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Affiliation(s)
- Michele Lima Gregório
- Transdisciplinary Nucleus for the Study of Chaos and Complexity, NUTECC, São José do Rio Preto Medical School, FAMERP, Avenida Brigadeiro Faria Lima, 54-16 CEP, 15090-000 São José do Rio Preto, SP, Brazil.
| | - Guilherme Luiz Lopes Wazen
- Department of Psychiatry, São José do Rio Preto Medical School, FAMERP, Avenida Brigadeiro Faria Lima, 54-16 CEP, 15090-000 São José do Rio Preto, SP, Brazil
| | - Andrew Haddon Kemp
- Department of Psychology, College of Human and Health Sciences, Swansea University, Singleton Park, Wales SA2 8PP, United Kingdom
| | - Juliana Cristina Milan-Mattos
- Cardiovascular Physical Therapy Laboratory, Department of Physical Therapy, Federal University of São Carlos, São Paulo, Brazil
| | - Alberto Porta
- Department of Biomedical Sciences for Health, University of Milan, Milan, Italy; Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, Milan, Italy.
| | - Aparecida Maria Catai
- Cardiovascular Physical Therapy Laboratory, Department of Physical Therapy, Federal University of São Carlos, São Paulo, Brazil.
| | - Moacir Fernandes de Godoy
- Transdisciplinary Nucleus for the Study of Chaos and Complexity, NUTECC, São José do Rio Preto Medical School, FAMERP, Avenida Brigadeiro Faria Lima, 54-16 CEP, 15090-000 São José do Rio Preto, SP, Brazil; Department of Cardiology and Cardiovascular Surgery, São José do Rio Preto Medical School, FAMERP, Avenida Brigadeiro Faria Lima, 5416 CEP, 15090-000 São José do Rio Preto, SP, Brazil
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50
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Simonyan MA, Posnenkova OM, Kiselev AR. Capabilities of photoplethysmography as a method for screening of cardiovascular system pathology. CARDIO-IT 2020. [DOI: 10.15275/cardioit.2020.0102] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Currently, vegetative dysfunction considered to be one of principal mechanisms in the pathogenesis of cardiovascular pathology, which causes a cascade of events leading to changes in the properties and a structure of vascular wall. This review article contains literature from various databases (Russian science citation index, PubMed, Google Shcolar, Scopus). It presents the methods for assessing vegetative imbalance. In particular, the method of photoplethysmography (PPGV) is considered for recording periodic fluctuations at various frequencies in the distal vascular bed which characterize physiological processes (cardiac activity, respiratory influences, neurogenic, myogenic and endothelial activity). In addition, other diagnostic capabilities of PPGV such as heart rate (HR) assessment, determining the properties of vascular wall and the level of blood saturation are elucidated. This paper demonstrates a wide range of PPGV applications. The simplicity of PPGV reproduction and its cost-effectiveness make it feasible both in routine clinical practice for the purposes of screening for cardiovascular pathology, and for individual health monitoring incorporated in smart devices.
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