SEARCH

SEARCH BY CITATION

Keywords:

  • autonomic nervous system activity;
  • global assessment of functioning;
  • heart rate variability;
  • power spectral analysis;
  • schizophrenia

Abstract

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONCLUSIONS
  7. ACKNOWLEDGMENTS
  8. REFERENCES

Aims:  Schizophrenia patients have a mortality rate two to three-fold higher than that of the general population. Despite the disorder's widespread recognition, how and to what extent autonomic nervous system (ANS) activity contributes to schizophrenia remains inconclusive. The aim of the present study, therefore, was to determine the extent of ANS activity depression with respect to healthy, well-matched control subjects and the severity of psychiatric disorders as determined using the Global Assessment of Functioning (GAF) scale among schizophrenia patients with special reference to antipsychotic dose.

Methods:  This study included 71 schizophrenia patients and 72 healthy controls. ANS activity was assessed by means of heart rate variability power spectral analysis.

Results:  ANS-related spectral parameters were three–four-fold lower in the patients compared to the control group (P < 0.01). Furthermore, when the patients without cardiovascular complications were classified according to GAF score, overall ANS (P = 0.033) and parasympathetic nervous system (PNS) activity (P = 0.025) were significantly reduced in the low-GAF as compared to the high-GAF group. Partial correlation analyses demonstrated that ANS activity was significantly correlated with GAF score while statistically eliminating the effects of age, gender, body mass index, antipsychotic dose, and lipid profiles of the patient population.

Conclusion:  The significantly lower ANS activity in the low-GAF group suggests that such autonomic functional depression could be associated with the severity of schizophrenia. The present data further imply that schizophrenia patients with more depressed overall ANS and PNS activity might encounter increasing risks for cardiovascular events such as sudden death.

SCHIZOPHRENIA, A CHRONIC psychiatric disorder, creates numerous challenges, not only in terms of its clinical management, but also in the psychosocial consequences for the patient. The clinical picture, depending on the phase of illness, includes a wide range of positive and negative symptoms and/or a broad range of cognitive symptoms. Epidemiological studies have shown that schizophrenia affects approximately 1% of the population, with point prevalence ranging from 0.6 to 8.3 cases per 1000 population.1,2

Previously, Ruschena et al. reported that patients with schizophrenia are threefold more likely to experience sudden unexpected death than individuals from the general population.3 Increased mortality in patients with schizophrenia, compared to the general population, has been consistently reported worldwide.4 Furthermore, individuals with schizophrenia have more major coronary heart disease events, such as acute myocardial infarction.5,6 The underlying bio-psychological mechanisms, however, which are complex and multidimensional and might affect diverse neurophysiologic systems, remain unknown.

Although all body systems contribute, the relative stability of the human internal environment depends largely on the functioning of the autonomic nervous system (ANS) that innervates organs and glands throughout the body. Therefore, even a slight disorder of the ANS could induce broadly ranged neuropsychophysiological disorders and ultimately, far-reaching adverse effects on health.

The electrocardiogram (ECG) R-R interval or inter-beat interval is determined by the net effect of sympathetic and parasympathetic input. Because it is accessible and non-invasive, the spectral analysis of heart rate variability (HRV) has gained popularity as a functional indicator of the ANS.7–9 In addition, HRV power spectral analysis lightens the burden imposed on subjects during an experiment, unlike invasive measurements, such as plasma catecholamine concentration and muscle sympathetic nervous activity. In short, it offers a practical and valuable approach to evaluation of the sympatho-vagal activity in various clinical science fields, including psychiatry research.7–12

Accordingly, the present study was proposed to evaluate resting ANS activity by means of HRV power spectral analysis of patients with schizophrenia and healthy well-matched controls and to investigate whether reduced sympatho-vagal activity contributes to unfavorable pathological alteration in patients with schizophrenia. We also examined a possible association between psychiatric severity and sympatho-vagal activities to investigate the nature of ANS alteration as a possible clinical feature of schizophrenia.

METHODS

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONCLUSIONS
  7. ACKNOWLEDGMENTS
  8. REFERENCES

Subjects

The present study involved 71 schizophrenia patients (56.2 ± 1.7 years; 23 male, 159.4 ± 1.1 cm, 57.4 ± 1.3 kg) hospitalized in the psychiatric clinic at Seishinkai Fujisawa Hospital. They met diagnostic criteria for schizophrenia according to the DSM-IV.13 Patient data were compared with those obtained from 72 healthy control subjects (52.2 ± 1.2 years; 30 male, 163.3 ± 1.8 cm, 63.7 ± 1.6 kg). None of the controls had any history of physical and/or psychiatric disorders, and none was taking any medication. The study protocol was approved by the Institutional Review Board of the Seishinkai Fujisawa Hospital and was performed in accordance with the Declaration of Helsinki of the World Medical Association. All subjects received an explanation of the nature and purpose of the study, and all gave their written informed consent to participate in the study.

Experimental procedure

All experiments were performed between 9.00 hours and 15.00 hours in a quiet comfortable room with minimal arousal stimuli. First, body composition was measured (DS-320, Tanita, Tokyo, Japan). After appropriate skin preparation, the subjects were fitted with ECG electrodes; they then rested for at least 20 min before the start of the experiment. After the resting period, the CM5 lead ECG was continuously recorded for 5 min while the individual remained in a sitting position. During the experiments, all subjects breathed in synchrony to a metronome at 15 b.p.m. (0.25 Hz) to ensure that respiratory-linked variations in heart rate did not overlap with lower-frequency heart rate fluctuations (<0.15 Hz) from other sources.

The Global Assessment of Functioning (GAF) Scale in DSM-IV was used to evaluate psychiatric assessment.13 The GAF is an observer-based rating scale for the current overall functioning of a patient on a continuum from the most severe mental disorder to complete mental health, defined as Axis V of the DSM-IV. Scale values range from 1 (sickest individual) to 100 (healthiest individual). Daily dosage of antipsychotic drugs was converted to approximate chlorpromazine equivalents (CPZeq) using published guidelines.14

R-R interval power spectral analysis procedure

The present R-R interval power spectral analysis procedures have been fully described elsewhere.9,15,16 To review them briefly, the ECG signal was amplified (Bio-Tex, BBA-8321, Kyoto, Japan), digitized via a 13-bit analogue-to-digital converter (Daq AD132, Elan, UK) at a sampling rate of 1024 Hz, and sequentially stored on a hard disk for later analysis. The stored ECG signal was differentiated, and the QRS spikes and the intervals of the impulses (R-R intervals) were detected. The R-R interval data were aligned to obtain equally spaced samples with an effective sampling frequency of 2 Hz17 and displayed on a computer screen for visual inspection. Then, the direct current component and trend were completely eliminated by digital filtering for the band-pass between 0.03 and 0.4 Hz. After passing through the Hamming-type data window, power spectral analysis by means of a fast Fourier transform was performed on a consecutive 256-s time series of R-R interval data obtained during the test. The spectral powers in frequency domain were quantified by integrating the areas under the curves for the following respective bandwidth: low-frequency (LF: 0.03–0.15 Hz) of HRV representing both sympathetic nervous system (SNS) and parasympathetic nervous system (PNS) activity; high-frequency (HF: 0.15–0.4 Hz) of HRV associated almost entirely with PNS activity; and the total power (TP: 0.03–0.4 Hz) representing overall ANS activity.18,19 The HRV power spectral analysis has been proven as a reliable non-invasive method and has provided a comprehensive quantitative and qualitative evaluation of autonomic function under various physiological conditions.18–21

Biochemistry

Blood was drawn from the antecubital vein of the schizophrenia patients as they sat comfortably. Blood samples were immediately transferred to siliconized tubes containing Na2 ethylenediamine tetra-acetic acid (1 mg/mL) and centrifuged at 4°C. Plasma and serum were immediately frozen and stored at −20°C until assay. Plasma glucose was measured by the hexokinase method, and serum high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol, and triglyceride levels (Daiichi Pure Chemicals, Tokyo, Japan) were determined by enzymatic methods. Hemoglobin A1c (HbA1c) was measured by latex agglutination methods (SRL, Tokyo, Japan).

Statistical analysis

All statistical analyses were performed using a commercial software package (SPSS 11.5J for Windows, SPSS, Tokyo, Japan). We first assessed group differences between 71 schizophrenia patients and 72 control subjects using Student's unpaired t-test and analysis of covariance (ancova) with adjustment for confounding factors: age, gender, and body mass index (BMI). The difference in the male–female ratio between these groups was compared using χ2 test. Then, considering the effects of cardiovascular risks on HRV, we excluded 26 schizophrenia patients with hypertension, hyperlipidemia, diabetes or other cardiovascular complications and conducted group comparisons between the control subjects and 45 schizophrenia patients without major cardiovascular risks. Furthermore, in 45 schizophrenia patients without major cardiovascular risks, we performed a comparison between low- and high-GAF groups using Student's unpaired t-test and ancova with adjustment for confounding factors. In addition, partial correlation coefficients were calculated on the relationships between ANS-related spectral powers and GAF scores among 45 patients without major cardiovascular risks to eliminate the effects of age, gender, BMI, CPZeq, and biochemical profiles (plasma glucose, HDL- and LDL-cholesterol, triglyceride levels, and HbA1c). P < 0.05 was considered statistically significant. All data are expressed as mean ± SE.

RESULTS

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONCLUSIONS
  7. ACKNOWLEDGMENTS
  8. REFERENCES

Comparison between the schizophrenia patients and control groups

There were no significant differences in age (56.2 ± 1.7 vs 52.2 ± 1.2 years, P = 0.061), gender (23 male and 48 female vs 30 male and 42 female, P = 0.254), or height (159.4 ± 1.1 cm vs 163.3 ± 1.8 cm, P = 0.082) between 71 schizophrenia patients and 72 controls. The schizophrenia group had significantly lower body mass (57.4 ± 1.3 vs 63.7 ± 1.6 kg, P = 0.003) and BMI (22.3 ± 0.6 vs 23.9 ± 0.5, P = 0.028) compared to the control group.

As to the R-R spectral parameters between the two groups, the schizophrenia group had a significantly higher resting heart rate (89.1 ± 2.0 b.p.m. vs 69.6 ± 1.2 b.p.m., P < 0.001) compared with the control group. All the spectral powers were markedly lower in the schizophrenia group than in the control group, as we expected (TP: 142 ± 26 ms2 vs 474 ± 96 ms2, P = 0.001; LF power: 75 ± 15 ms2 vs 261 ± 67 ms2, P = 0.008; HF power: 67 ± 14 ms2 vs 213 ±43 ms2, P = 0.002). Further statistical analysis detected that the HRV spectral powers were also significantly more depressed in the schizophrenia group than in the control group after adjusting for age, gender, and BMI (TP, P = 0.004; LF power, P = 0.028; HF power, P = 0.003).

Because ANS activity and GAF score might be affected by the possible effects of limited physical ability, hypertension, hyperlipidemia, diabetes, and other cardiovascular complications, we then eliminated 26 patients from the original 71 patients according to the aforementioned criteria so as to minimize these compounding factors influencing our results. Comparing clinical features and ANS-related power spectral parameters, we found no significant difference in age (55.5 ± 2.2 vs 52.2 ± 1.2 years, P = 0.195) and gender (15 male and 30 female vs 30 male and 42 female, P = 0.436) between 45 patients and 72 controls. Body mass (56.1 ± 1.5 kg vs 63.7 ± 1.6 kg, P = 0.001) and BMI (22.0 ± 0.5 vs 23.9 ± 0.5, P = 0.007) were lower in the schizophrenia group than in the control group. Regarding ANS activity, all the spectral powers were markedly decreased in the schizophrenia group than in the control group (TP: 122 ± 23 ms2 vs 474 ± 96 ms2, P = 0.001; LF power: 65 ± 11 ms2 vs 261 ± 67 ms2, P = 0.005; HF power: 57 ± 14 ms2 vs 213 ±43 ms2, P = 0.001). This indicated that both overall ANS and PNS activities severely decreased in the schizophrenia patients without major cardiovascular risks compared to the controls. The HRV spectral powers were also lower in the schizophrenia group than in the control group after adjusting for age, gender, and BMI (TP, P = 0.017; LF power, P = 0.068; HF power, P = 0.014).

Comparison between low- and high-GAF groups

To investigate the association between the severity of schizophrenia and ANS activity, we further divided the 45 patients without major cardiovascular risks into two groups based on the median values of the GAF scores: low-GAF (<30), and high-GAF (>30).

Table 1 shows physical and clinical characteristics of the low- and high-GAF groups. The low-GAF group was significantly younger than the high-GAF group (P = 0.021), while all other clinical characteristics were not significantly different between the two groups.

Table 1.  Clinical patient characteristics vs GAF score (mean ± SE)
 Low GAF (n = 27)High GAF (n = 18)P
  1. High GAF: score > 30; low GAF: score < 30.

  2. GAF, Global Assessment of Functioning; HDL, high-density lipoprotein; LDL, low-density lipoprotein.

Gender (male/female)9/186/121.000
GAF (score)24.1 ± 0.937.8 ± 1.3<0.001
Age (years)51.4 ± 2.861.6 ± 3.00.021
Height (cm)159.7 ± 1.8159.8 ± 2.50.980
Body mass (kg)57.9 ± 1.953.3 ± 2.30.134
Body mass index (kg/m2)22.7 ± 0.720.8 ± 0.80.078
Waist circumference (cm)87.4 ± 1.983 ± 2.20.141
Antipsychotic dose (mg)1646.8 ± 219.51022.1 ± 228.60.063
Blood glucose (mmol/L)82.8 ± 2.385.4 ± 2.00.432
Triglyceride (mmol/L)78.9 ± 5.977.7 ± 8.10.902
HDL-cholesterol (mmol/L)62.9 ± 2.361.6 ± 3.20.736
LDL-cholesterol (mmol/L)98.9 ± 4.299.9 ± 5.90.881
Hemoglobin A1c (%)5.0 ± 0.15.1 ± 0.00.522

Figure 1 represents typical sets of raw R-R intervals and the power spectral data obtained from subjects belonging to the low- and high-GAF groups, respectively, during the resting condition. Upon visual inspection, the low-GAF subjects had markedly reduced R-R variability, as well as LF and HF components of the power spectrum, compared with the high-GAF subjects.

image

Figure 1. Examples of (a,b) electrocardiogram R-R interval changes and (c,d) the corresponding power spectra for (a,c) low Global Assessment of Functioning (GAF) and (b,d) high GAF groups at rest. HF, high-frequency power (0.15–0.4 Hz); LF, low-frequency power (0.03–0.15 Hz).

Download figure to PowerPoint

Figure 2 represents the group data on R-R power spectral parameters obtained from the low- and high-GAF groups. As the data indicate, TP (78 ± 22 ms2 vs 189 ± 44 ms2, P = 0.033) and HF power (27 ± 10 ms2 vs 101 ± 29 ms2, P = 0.025) representing overall ANS and PNS activities, respectively, were significantly reduced in the low-GAF group compared with the high-GAF group. The LF power, representing sympatho-vagal activity, was also reduced in the low-GAF group compared with the high-GAF group (50 ± 14 ms2 vs 87 ± 18 ms2, P = 0.111), but statistical analysis indicated no significant difference. Additionally, partial correlation analyses demonstrated that TP (r = 0.432, P = 0.009) and HF power (r = 0.400, P = 0.016) had significant positive correlations with GAF scores while statistically eliminating the effects of age, gender, BMI, CPZeq, blood glucose, and lipid profiles of the entire patient population.

image

Figure 2. Comparison of total power (TP), low- and high-frequency (LF, HF) power between the (□) low-GAF (score < 30) and (inline image) high-GAF (score > 30) groups (mean ± SE). GAF, Global Assessment of Functioning. *P < 0.05.

Download figure to PowerPoint

DISCUSSION

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONCLUSIONS
  7. ACKNOWLEDGMENTS
  8. REFERENCES

Schizophrenia, a severe mental disorder, requires lifelong treatment, and therefore information on its pathophysiological features and psychotropic effects together with cardiovascular health, is of clinical importance. Although schizophrenia has a multicausal origin, and its pathogenesis is not yet clearly understood, it is conceivable that altered function of the ANS – a vital player in modulating the relative stability of a human's internal environment – is associated with the severity and frequency of the symptom cluster appearing with schizophrenia.

In the present study we used a computer-assisted 5-min measurement of resting HRV to evaluate ANS activity in schizophrenia patients. Measurement of HRV integrates pre-synaptic and post-synaptic end-organ response and provides a comprehensive quantitative and qualitative evaluation of autonomic function under various physiological conditions and clinical settings.19,21,22 Although quantification and interpretation of HRV remain an intricate issue,7,23 the efficacy and applicability of the technique as demonstrated in a pharmacological blockade experiment with atropine, a parasympathetic muscarinic antagonist and propranolol, a β-adrenoceptor antagonist,15,24 have supported the classical studies18,19 and confirmed that (i) HF power is associated solely with PNS activity and LF power is jointly mediated by PNS and SNS activity; and (ii) R-R interval variability and TP – the integrated values of all the components of power spectra – could reflect overall ANS activity.

We are aware of the fact that LF and HF powers in schizophrenia are reduced as reported in previous studies.12,25 In the present study we therefore attempted to determine the extent of ANS activity depression with respect to (i) healthy, well-matched control subjects and (ii) the severity of psychiatric disorders as determined by the GAF scale among schizophrenia patients with special reference to daily dosage of antipsychotic drugs.

We found three–fourfold lower ANS activities in the patient group than in the control group, implying that the previously reported threefold-higher mortality rate, including sudden cardiac death, might be, at least in part, associated with severely depressed PNS activity in schizophrenia patients.3 Further evidence would be provided by the significantly higher resting heart rate often seen in diabetics, with some degree of autonomic neuropathy, which in turn causes cardiac parasympathetic withdrawal leading to elevated heart rate.9,21,22,26

In addition, we have re-examined the effect of antipsychotic dosages27–29 and other lipid and cardiovascular complications15,21,26 that may have a large impact upon ANS activity as well as, indirectly, the GAF scores. After eliminating patients with these complications, we then compared the net relationship between ANS activity and low- and high-GAF groups. Intriguingly, we found that the low-GAF group showed significantly lower TP (overall ANS activity) and HF power (PNS activity), despite the fact that the low-GAF group was significantly younger (nearly 10 years difference), with non-significant differences in CPZeq as well as BMI, waist circumference, blood glucose, and lipid profiles.

Among the entire patient population, partial correlation analysis demonstrated that TP and HF power had significant correlation with the GAF score, while statistically eliminating the effects of age, gender, BMI, CPZeq, and biochemical profiles. We think that these findings, derived from comparisons between normal and patient groups as well as low- and high-GAF patients, do provide some new insight into the pathophysiological nature of schizophrenia, that is, depression of PNS activity may play an important role in the development of schizophrenia and possible etiology of sudden cardiac death.3–5,21,26

Previous studies suggest that a dysfunction of both SNS and PNS contribute to psychosomatic disorders as well as to cardiovascular and metabolic malfunction.9,11,15,21,22,26,30 As to psychiatric diseases, a recent clinical study by Bar et al. showed that patients displaying stronger psychotic symptoms as according to total scores of the Brief Psychiatric Rating Scale, exhibit more severe cardiac autonomic disturbances as indicated by a reduced HF power compared with controls.25 According to Jindal et al., autonomic deficits have been shown to be more pronounced during acute psychotic episodes in patients with first-episode schizophrenia, implying that autonomic dysfunction in schizophrenia may also be a ‘disease effect’.31 Toichi et al., using HRV measurements, showed that psychotic states affect the ANS, suggesting a relationship between cerebral cognitive and peripheral ANS activities, and that this is presumably mediated through PNS activity.32

The present study supports these previous findings and suggests that schizophrenia patients possessed markedly depressed ANS activity, which was further associated with the degree of psychiatric severity on schizophrenia. Taken together, physiological functions in both branches of the ANS might deteriorate more as the schizophrenia becomes more severe. Further research is needed to assess patient condition using other scores of psychiatric symptoms, such as the Positive and Negative Syndrome Scale and the Brief Psychiatric Rating Scale and to examine an association between ANS activity and these scores. As to the pharmacological effects, previous research has found significant negative correlation between the daily dosage of anticholinergic drugs converted into biperiden milligram equivalents and HRV.30 Wang et al., in contrast, recently examined an association of ANS activity and atypical antipsychotic drugs and demonstrated that amisulpride has more vagotonic effect as compared with olanzapine when subjects are switched from typical antipsychotic agents.33 Although we investigated the effect of CPZeq as an index of daily dose of antipsychotic drugs on ANS activity in schizophrenia patients, it would also be of clinical importance to further scrutinize how and to what extent pharmacological treatments – dosage, types, and combination of medications and duration of drug administration – influence schizophrenia symptomatology as well as sympatho-vagal function together with cardiovascular safety.

CONCLUSIONS

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONCLUSIONS
  7. ACKNOWLEDGMENTS
  8. REFERENCES

The present study has shown a potential association between ANS activity and schizophrenia: overall ANS and PNS activity were more decreased in schizophrenia patients with a greater degree of psychiatric severity. The underlying pathological mechanisms of schizophrenia at the moment remain enigmatic. Although causes and consequences continue to elude researchers, the present study provides additional intriguing evidence that the altered functioning of ANS could be associated with diverse physical, mental, and/or behavioral symptoms appearing in schizophrenia. The study further implies that such autonomic malfunction might also induce metabolic and cardiovascular complications and, ultimately, higher mortality rates.

ACKNOWLEDGMENTS

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONCLUSIONS
  7. ACKNOWLEDGMENTS
  8. REFERENCES

We are grateful to the subjects for their enthusiastic participation. We also appreciate the staff of the Seishinkai Fujisawa Hospital for their cooperation and assistance during the experiments.

REFERENCES

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONCLUSIONS
  7. ACKNOWLEDGMENTS
  8. REFERENCES
  • 1
    Awad AG, Voruganti LN. The burden of schizophrenia on caregivers: A review. Pharmacoeconomics 2008; 26: 149162.
  • 2
    Goldacre M, Shiwach R, Yeates D. Estimating incidence and prevalence of treated psychiatric disorders from routine statistics: The example of schizophrenia in Oxfordshire. J. Epidemiol. Community Health 1994; 48: 318322.
  • 3
    Ruschena D, Mullen PE, Burgess P et al. Sudden death in psychiatric patients. Br. J. Psychiatry 1998; 172: 331336.
  • 4
    Capasso RM, Lineberry TW, Bostwick JM, Decker PA, St Sauver J. Mortality in schizophrenia and schizoaffective disorder: An Olmsted County, Minnesota cohort: 1950–2005. Schizophr. Res. 2008; 98: 287294.
  • 5
    Hennekens CH, Hennekens AR, Hollar D, Casey DE. Schizophrenia and increased risks of cardiovascular disease. Am. Heart J. 2005; 150: 11151121.
  • 6
    Druss BG, Bradford DW, Rosenheck RA, Radford MJ, Krumholz HM. Mental disorders and use of cardiovascular procedures after myocardial infarction. JAMA 2000; 283: 506511.
  • 7
    Conny M, Louis A, Jeroen C, Gerard B, Herman P. Heart rate variability. Ann. Intern. Med. 1993; 118: 436447.
  • 8
    Task Force of the European Society of Cardiology, the North American Society of Pacing and Electrophysiology. Heart rate variability. Standard of measurements, physiological interpretation and clinical use. Circulation 1996; 93: 10431065.
  • 9
    Moritani T, Hayashi T, Shinohara M, Mimasa F, Masuda I, Nakao K. Sympatho-vagal activities of NIDDM patients during exercise as determined by heart rate spectral analysis. In : KawamoriR, VranicM, HortonE, KubotaM (eds). Glucose Fluxes, Exercise and Diabetes. Smith-Gordon, London, 1995; 9196.
  • 10
    Davy KP, DeSouza CA, Jones PP, Seals DR. Elevated heart rate variability in physically active young and older adult women. Clin. Sci. (Lond.) 1998; 94: 579584.
  • 11
    Matsumoto T, Ushiroyama T, Kimura T, Sakuma K, Moritani T. Therapeutic effects of psychological treatment in the outpatient climacteric clinic evaluated with an index of autonomic nervous system activity. J. Jpn Menopause Soc. 2007; 15: 135145.
  • 12
    Mujica-Parodi LR, Yeragani V, Malaspina D. Nonlinear complexity and spectral analyses of heart rate variability in medicated and unmedicated patients with schizophrenia. Neuropsychobiology 2005; 51: 1015.
  • 13
    American Psychiatric Association. American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders, 4th edn. American Psychiatric Association, Washington, DC, 1994.
  • 14
    Sim K, Su A, Fujii S et al. Antipsychotic polypharmacy in patients with schizophrenia: A multicentre comparative study in East Asia. Br. J. Clin. Pharmacol. 2004; 58: 178183.
  • 15
    Hayashi T, Masuda I, Shinohara M, Moritani T, Nakao K. Autonomic nerve activity during physical exercise and postural change: Investigation by power spectral analysis of heart rate variability. Jpn J. Biochem. Exerc. 1994; 6: 3037.
  • 16
    Kimura T, Matsumoto T, Akiyoshi M et al. Body fat and blood lipids in postmenopausal women are related to resting autonomic nervous system activity. Eur. J. Appl. Physiol. 2006; 97: 542547.
  • 17
    Rompelman O, Coenen AJ, Kitney RI. Measurement of heart-rate variability: Part 1: Comparative study of heart-rate variability analysis methods. Med. Biol. Eng. Comput. 1977; 15: 233239.
  • 18
    Akselrod S, Gordon D, Ubel FA, Shannon DC, Berger AC, Cohen RJ. Power spectrum analysis of heart rate fluctuation: A quantitative probe of beat-to-beat cardiovascular control. Science 1981; 213: 220222.
  • 19
    Pagani M, Lombardi F, Guzzetti S et al. Power spectral analysis of heart rate and arterial pressure variabilities as a marker of sympatho-vagal interaction in man and conscious dog. Circ. Res. 1986; 59: 178193.
  • 20
    Amano M, Kanda T, Ue H, Moritani T. Exercise training and autonomic nervous system activity in obese individuals. Med. Sci. Sports Exerc. 2001; 33: 12871291.
  • 21
    Ue H, Masuda I, Yoshitake Y, Inazumi T, Moritani T. Assessment of cardiac autonomic nervous activities by means of ECG R-R interval power spectral analysis and cardiac depolarization-repolarization process. Ann. Noninvas. Electrocardiol. 2000; 5: 336345.
  • 22
    Moritani T, Hayashi T, Shinohara M, Mimasa F, Shibata M. Comparison of sympatho-vagal function among diabetic patients, normal controls and endurance athletes by heart rate spectral analysis. J. Sports Med. Sci. 1993; 7: 3139.
  • 23
    Eckberg DL. Sympathovagal balance: A critical appraisal. Circulation 1997; 96: 32243232.
  • 24
    Matsumoto T, Miyawaki T, Ue H, Kanda T, Zenji C, Moritani T. Autonomic responsiveness to acute cold exposure in obese and non-obese young women. Int. J. Obes. Relat. Metab. Disord. 1999; 23: 793800.
  • 25
    Bar KJ, Wernich K, Boettger S et al. Relationship between cardiovagal modulation and psychotic state in patients with paranoid schizophrenia. Psychiatry Res. 2008; 157: 255257.
  • 26
    Moritani T, Kimura T, Hamada T, Nagai N. Electrophysiology and kinesiology for health and disease. J. Electromyogr. Kinesiol. 2005; 15: 240255.
  • 27
    Yeragani VK, Pesce V, Jayaraman A, Roose S. Major depression with ischemic heart disease: Effects of paroxetine and nortriptyline on long-term heart rate variability measures. Biol. Psychiatry 2002; 52: 418429.
  • 28
    Ikawa M, Tabuse H, Ueno S, Urano T, Sekiya M, Murakami T. Effects of combination psychotropic drug treatment on heart rate variability in psychiatric patients. Psychiatry Clin. Neurosci. 2001; 55: 341345.
  • 29
    Hempel RJ, Tulen JH, Van Beveren NJ, Roder CH, Hengeveld MW. Cardiovascular variability during treatment with haloperidol, olanzapine or risperidone in recent-onset schizophrenia. J. Psychopharmacol. 2009 (in press).
  • 30
    Matsumoto T, Ushiroyama T, Morimura M et al. Autonomic nervous system activity in the late luteal phase of eumenorrheic women with premenstrual symptomatology. J. Psychosom. Obstet. Gynaecol. 2006; 27: 131139.
  • 31
    Jindal R, MacKenzie EM, Baker GB, Yeragani VK. Cardiac risk and schizophrenia. J. Psychiatry Neurosci. 2005; 30: 393395.
  • 32
    Toichi M, Kubota Y, Murai T et al. The influence of psychotic states on the autonomic nervous system in schizophrenia. Int. J. Psychophysiol. 1999; 31: 147154.
  • 33
    Wang YC, Yang CC, Bai YM, Kuo TB. Heart rate variability in schizophrenic patients switched from typical antipsychotic agents to amisulpride and olanzapine: 3-month follow-up. Neuropsychobiology 2008; 57: 200205.