Analyses of Heart Rate, Respiration and Cardiorespiratory Coupling in Patients with Schizophrenia

Abstract

Schizophrenia is a severe mental disorder associated with a significantly increased cardiovascular mortality rate. However, the underlying mechanisms leading to this cardiovascular disease (CVD) are not fully known. Therefore, the objective of this study was to characterize the cardiorespiratory influence by investigating heart rate, respiration and the causal strength and direction of cardiorespiratory coupling (CRC), based mainly on entropy measures. We investigated 23 non-medicated patients with schizophrenia (SZ), comparing them to 23 age-and gender-matched healthy controls (CO). A significantly reduced complexity was found for the heart rate and a significantly increased complexity in respiration and CRC in SZ patients when compared to corresponding measurements from CO (p < 0.001). CRC analyses revealed a clear coupling, with a driver-responder relationship from respiration to heart rate in SZ patients. Moreover, a slight driver-responder relationship from heart rate to respiration could be recognized. These findings lead to the assumption that SZ should be considered to be a high-risk group for CVD. We hypothesize that the varying cardiorespiratory regulation contributes to the increased risk for cardiac mortality. Therefore, regular monitoring of the cardiorespiratory status of SZ is suggested to identify autonomic regulation impairment at an early stage-to develop timely and effective treatment and intervention strategies. OPEN ACCESSEntropy 2015, 17 484

Wavelet Entropy Automatically Detects Episodes of Atrial Fibrillation from Single-Lead Electrocardiograms

“…Indeed, numerous entropy-based metrics have recently provided a significant ability to reveal useful information from diseases that still represent a clinical challenge, such as Alzheimer's [1], schizophrenia [2], myocardial infarction [3] or atrial fibrillation (AF) [4], among others. The information provided by these metrics is mainly related to underlying mechanisms that cannot be quantified directly by clinicians in an exploratory examination, thus providing a significant knowledge increase of those diseases, as well as improving their diagnosis and treatment [5,6].…”

Complex and Nonlinear Analysis of Heart Rate Variability in the Assessment of Fetal and Neonatal Wellbeing

“…However, a limitation of all univariate nonlinear methods is that they are not able to quantify the direct interrelationships such as the nonlinear influence of respiration on heart rate. Therefore, they have limited power to reveal the underlying physiological mechanisms responsible for changes in cardiorespiratory complexity [76].…”

“…We investigated [76,101,102] non-medicated 23 patients with schizophrenia (SZ; 12 male; 30.4˙10.3 years) and 23 healthy subjects (CO, 13 male; 30.3˙9.5 years) matched regarding to age and sex (Table 2.1) to quantify heart rate-and respiratory variability (HRV, RESPV) and their dynamics as well as the cardiorespiratory coupling (CRC).…”

“…HRJSD based on the classical JSD [4] analyzing dynamic processes by means of symbols. HRJSD has been successful applied to investigate cardiovascular, cardiorespiratory and centralautonomic couplings [5,14,76,77].…”

“…Quantification of HRV, RESPV and CRC was done by applying several complexity approaches as symbolic dynamics (SD), compression entropy (H C ), sample entropy (SampEn), Poincaré plot analysis (PPA), Higuchi fractal dimension (HD), high resolution joint symbolic dynamics (HRJSD), cross conditional entropy (CCE), cross multiscale entropy (CMSE) and normalized short time partial directed coherence (NSTPDC) [71,76,103].…”