Characterization of cardiac autonomic dysfunction in acute Schizophrenia: a cluster analysis of heart rate variability parameters

Abstract Underlying biological mechanisms leading to the dramatically increased cardiac mortality in patients with schizophrenia (SCZ) are largely unknown. Cardiac autonomic dysfunction (CADF), which has been extensively described in patients with SCZ, represents an important physiological link to c...

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Main Authors: Alexander Refisch, Andy Schumann, Yubraj Gupta, Steffen Schulz, Andreas Voss, Berend Malchow, Karl-Jürgen Bär
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Schizophrenia
Online Access:https://doi.org/10.1038/s41537-025-00589-y
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author Alexander Refisch
Andy Schumann
Yubraj Gupta
Steffen Schulz
Andreas Voss
Berend Malchow
Karl-Jürgen Bär
author_facet Alexander Refisch
Andy Schumann
Yubraj Gupta
Steffen Schulz
Andreas Voss
Berend Malchow
Karl-Jürgen Bär
author_sort Alexander Refisch
collection DOAJ
description Abstract Underlying biological mechanisms leading to the dramatically increased cardiac mortality in patients with schizophrenia (SCZ) are largely unknown. Cardiac autonomic dysfunction (CADF), which has been extensively described in patients with SCZ, represents an important physiological link to cardiovascular disease (CVD). This study investigated the prevalence of CADF in patients with SCZ using HRV across multiple domains (time and frequency, nonlinear dynamics, complexity measures, symbolic dynamics, and segmented Poincaré plot analysis). HRV-based clustering classified 119 SCZ patients as having or not having CADF based on deviations from 119 age- and sex-matched healthy controls. Our findings showed that approximately half of the patients had normal cardiac autonomic function, while the other half had significant abnormalities. The severity of CADF correlated with age, body mass indes (BMI), disease duration, and symptom severity. About half of SCZ patients have significant CADF, which increases their risk for cardiac events. These findings highlight the potential of HRV-based biomarkers in improving CVD risk prediction and stratification in SCZ. Future research should explore integrating HRV analysis with other biomarkers to enhance early detection and intervention strategies.
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spelling doaj-art-3fd7abc964ac47859149e932381faf3f2025-08-20T02:59:57ZengNature PortfolioSchizophrenia2754-69932025-03-0111111010.1038/s41537-025-00589-yCharacterization of cardiac autonomic dysfunction in acute Schizophrenia: a cluster analysis of heart rate variability parametersAlexander Refisch0Andy Schumann1Yubraj Gupta2Steffen Schulz3Andreas Voss4Berend Malchow5Karl-Jürgen Bär6Department of Psychiatry and Psychotherapy, Jena University HospitalLab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University HospitalLab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University HospitalCharité Competence Center for Traditional and Integrative Medicine (CCCTIM), Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of HealthInstitute of Biomedical Engineering and Informatics (BMTI), Technische Universität IlmenauDepartment of Psychiatry and Psychotherapy, University Hospital GöttingenLab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University HospitalAbstract Underlying biological mechanisms leading to the dramatically increased cardiac mortality in patients with schizophrenia (SCZ) are largely unknown. Cardiac autonomic dysfunction (CADF), which has been extensively described in patients with SCZ, represents an important physiological link to cardiovascular disease (CVD). This study investigated the prevalence of CADF in patients with SCZ using HRV across multiple domains (time and frequency, nonlinear dynamics, complexity measures, symbolic dynamics, and segmented Poincaré plot analysis). HRV-based clustering classified 119 SCZ patients as having or not having CADF based on deviations from 119 age- and sex-matched healthy controls. Our findings showed that approximately half of the patients had normal cardiac autonomic function, while the other half had significant abnormalities. The severity of CADF correlated with age, body mass indes (BMI), disease duration, and symptom severity. About half of SCZ patients have significant CADF, which increases their risk for cardiac events. These findings highlight the potential of HRV-based biomarkers in improving CVD risk prediction and stratification in SCZ. Future research should explore integrating HRV analysis with other biomarkers to enhance early detection and intervention strategies.https://doi.org/10.1038/s41537-025-00589-y
spellingShingle Alexander Refisch
Andy Schumann
Yubraj Gupta
Steffen Schulz
Andreas Voss
Berend Malchow
Karl-Jürgen Bär
Characterization of cardiac autonomic dysfunction in acute Schizophrenia: a cluster analysis of heart rate variability parameters
Schizophrenia
title Characterization of cardiac autonomic dysfunction in acute Schizophrenia: a cluster analysis of heart rate variability parameters
title_full Characterization of cardiac autonomic dysfunction in acute Schizophrenia: a cluster analysis of heart rate variability parameters
title_fullStr Characterization of cardiac autonomic dysfunction in acute Schizophrenia: a cluster analysis of heart rate variability parameters
title_full_unstemmed Characterization of cardiac autonomic dysfunction in acute Schizophrenia: a cluster analysis of heart rate variability parameters
title_short Characterization of cardiac autonomic dysfunction in acute Schizophrenia: a cluster analysis of heart rate variability parameters
title_sort characterization of cardiac autonomic dysfunction in acute schizophrenia a cluster analysis of heart rate variability parameters
url https://doi.org/10.1038/s41537-025-00589-y
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