H G Stampfer1. 1. University Department of Psychiatry, QEII Medical Centre, Nedlands, Australia. hgstamp@cyllene.uwa.edu.au
Abstract
OBJECTIVE: The aim of this study was to investigate the relationship between psychiatric status and the circadian pattern of heart rate. METHOD: Serial 24-hour recordings of minute average heart rate were obtained from 30 normal volunteers and 200 patients representing a range of DSM-III-R diagnoses. Records were compared in terms of their circadian 'morphology' and grouped into different pattern types. The distribution of patterns in different diagnoses was analysed statistically. RESULTS: It was found that states such as generalised anxiety and depression are strongly associated with a distinctive circadian pattern, whereas others such as somatoform disorder show more variation in this regard. Serial recordings show that the relationship between psychiatric status and circadian pattern is state-dependent; a change in clinical status leads to a change in the circadian pattern. CONCLUSIONS: The presented findings together suggest that there is a systematic relationship between psychiatric status and heart rate in which core physiological differences between certain states are reflected in distinctively different circadian patterns of activity. The state-dependent nature of this relationship suggests obvious practical applications, and examples are given of how these adjunct data can provide objective indices of clinical status and change. At a theoretical level, the physiological dimension revealed by these data may help to define more reliable syndromal distinctions between various clinical manifestations and hence contribute to a more robust nosology.
OBJECTIVE: The aim of this study was to investigate the relationship between psychiatric status and the circadian pattern of heart rate. METHOD: Serial 24-hour recordings of minute average heart rate were obtained from 30 normal volunteers and 200 patients representing a range of DSM-III-R diagnoses. Records were compared in terms of their circadian 'morphology' and grouped into different pattern types. The distribution of patterns in different diagnoses was analysed statistically. RESULTS: It was found that states such as generalised anxiety and depression are strongly associated with a distinctive circadian pattern, whereas others such as somatoform disorder show more variation in this regard. Serial recordings show that the relationship between psychiatric status and circadian pattern is state-dependent; a change in clinical status leads to a change in the circadian pattern. CONCLUSIONS: The presented findings together suggest that there is a systematic relationship between psychiatric status and heart rate in which core physiological differences between certain states are reflected in distinctively different circadian patterns of activity. The state-dependent nature of this relationship suggests obvious practical applications, and examples are given of how these adjunct data can provide objective indices of clinical status and change. At a theoretical level, the physiological dimension revealed by these data may help to define more reliable syndromal distinctions between various clinical manifestations and hence contribute to a more robust nosology.
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