Primary care companion to the Journal of clinical psychiatry · 2007
Dynamic patterns in mood among newly diagnosed patients with major depressive episode or panic disorder and normal controls.
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Katerndahl David, Ferrer Robert, Best Rick, Wang Chen-Pin
Аннотация
OBJECTIVE: The purpose of this pilot study was to compare the dynamic patterns of hourly mood variation among newly diagnosed primary care patients with major depressive disorder or panic disorder with patterns in patients with neither disorder.
METHOD: Five adult patients with major depressive episode, 5 with panic disorder, and 5 with neither disorder were asked to complete hourly self-assessments of anxiety and depression (using 100-mm visual analog scales) for each hour they were awake during a 30-day period. Time series were analyzed using ARIMA (autoregression, integration, moving average) modeling (to assess periodicity), Lyapunov exponents (to assess sensitivity to initial conditions indicative of chaotic patterns), and correlation dimension saturation (to assess whether an attractor is limiting change). The study was conducted from March to June 2003.
RESULTS: Controls displayed circadian rhythms with underlying chaotic variability. Depressed patients did not display circadian rhythm, but did show chaotic dynamics. Panic disorder patients showed circadian rhythms, but 2 of the 4 patients completing the self-assessments displayed nonchaotic underlying patterns.
CONCLUSIONS: Patients with major depressive disorder or panic disorder may differ from controls and from each other in their patterns of mood variability. There is a need for more research on the dynamics of mood among patients with mental disorders.
METHOD: Five adult patients with major depressive episode, 5 with panic disorder, and 5 with neither disorder were asked to complete hourly self-assessments of anxiety and depression (using 100-mm visual analog scales) for each hour they were awake during a 30-day period. Time series were analyzed using ARIMA (autoregression, integration, moving average) modeling (to assess periodicity), Lyapunov exponents (to assess sensitivity to initial conditions indicative of chaotic patterns), and correlation dimension saturation (to assess whether an attractor is limiting change). The study was conducted from March to June 2003.
RESULTS: Controls displayed circadian rhythms with underlying chaotic variability. Depressed patients did not display circadian rhythm, but did show chaotic dynamics. Panic disorder patients showed circadian rhythms, but 2 of the 4 patients completing the self-assessments displayed nonchaotic underlying patterns.
CONCLUSIONS: Patients with major depressive disorder or panic disorder may differ from controls and from each other in their patterns of mood variability. There is a need for more research on the dynamics of mood among patients with mental disorders.