Non-linear complexity measures of heart rate variability in acute schizophrenia
Introduction
Mortality in patients with schizophrenia is at least two times higher than in reference populations (Black and Fisher, 1992, Brown et al., 2000). Apart from suicide (Meltzer, 1998) cardiovascular causes account for the majority of these events (Brown et al., 2000, Enger et al., 2004). The latter have been associated with unhealthy lifestyle, adverse effects caused by antipsychotics and higher incidence of diabetes as well as metabolic syndrome (Ruschena et al., 1998, Glassman and Bigger, 2001, Grundy et al., 2004), which resulted in the recommendation to routinely monitor physical health in these patients (Marder et al., 2004). The impact of antipsychotic medication has been studied in the greatest extent due to these substances’ ability to significantly prolong QTc intervals (Titier et al., 2005). However, even unmedicated patients with schizophrenia face an increased incidence of sudden cardiac death (Ray et al., 2001, Jindal et al., 2005). As we and others already assumed previously, one possible underlying cause might be autonomic dysfunction during acute psychosis as reflected by altered heart rate variability and autonomic function parameters. These include reduced time and frequency measures of heart rate variability (HRV) (Valkonen-Korhonen et al., 2003, Bar et al., 2005, Mujica-Parodi et al., 2005), reduced baroreflex sensitivity (Bar et al., 2007a) and reduced QT variability (Bar et al., 2007c) in short-term recordings. Besides linear HRV parameters describing the variance of beat-to-beat intervals, non-linear complexity parameters have been developed to describe the regularity of heart rate time series. The application of these novel analyses has led to a higher sensitivity for detecting autonomic dysfunction (Baumert et al., 2004b, Hoyer et al., 2006) and patients at risk for sudden death (Voss et al., 1996) in different diseases. To date, there is limited information about complexity measures of HRV in schizophrenia. Reduced complexity was found in 24 h recordings in unmedicated patients (Boettger et al., 2006) and in clozapine-treated patients when applying the sample entropy parameter, which negatively correlated with the degree of positive psychotic symptoms (Kim et al., 2004).
Even less data exist on complexity measures obtained from short-term recordings, owing to the fact that the calculation of such parameters requires a significant amount of raw data. Here, we aimed to fill this gap employing novel non-linear complexity measures that have been shown to reveal reliable results even in short recording times in patients suffering from different cardiovascular diseases. These are compression entropy Hc (Baumert et al., 2004b), probability of high or low variability sequences (phvar and plvar, respectively) (Voss et al., 1996), fractal dimension (Katz, 1988) and approximate entropy (Pincus, 1991). These were applied to electrocardiographic data obtained from 20 unmedicated patients with acute schizophrenia and 20 matched controls.
Section snippets
Participants
Twenty patients suffering from paranoid schizophrenia and 20 healthy controls matched with respect to age, sex, weight, smoking habits and education (see Table 1) were included in this study. Patients were examined unmedicated in the acute stage on the day of admission to the hospital and were only included in the study, when they had not taken antipsychotic medication for at least 8 weeks prior to the study. Control subjects were recruited from hospital staff and medical students. Neither
Multivariate statistic
Using multivariate ANOVA to compare schizophrenic patients with matched controls, we found a significant main effect for the between-subjects factor GROUP (patients with schizophrenia versus healthy controls) [F(4, 35) = 5.33, p = 0.002].
Univariate statistics
Follow-up univariate ANOVAs showed significant main effects for lnHc [F(1, 41) = 13.33, p < 0.0001] (Fig. 2a), lnphvar10 [F(1, 41) = 13.46, p < 0.001] (Fig. 2b), lnApEn [F(1, 41) = 10.13, p < 0.003] (Fig. 2c) and lnFD [F(1, 41) = 22.49, p < 0.001] (Fig. 2d), indicating that all
Discussion
In this study, we present further evidence for reduced complexity in beat-to-beat interval (BBI) time series obtained from short-term electrocardiographic recordings in patients with acute schizophrenia. Recently, we were able to show a similar reduction of complexity in patients with schizophrenia (Boettger et al., 2006). However, these measures needed to be calculated from 24 h Holter ECG recordings. Here, we assessed complexity from short BBI time series.
High complexity of biosignals reflects
Acknowledgement
We are grateful to Dr. R. Vollandt (IMSID, Institute for Medical Statistics, University of Jena, Germany) for his advice on statistics.
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These authors contributed equally to this work.