The Physiological Predictors of Concurrent Cardiovascular Diseases in Bipolar Disorder

The mortality rates of patients with bipolar disorder are 2 to 4 times higher than that of the general population. Notably, this higher mortality rate results in a 10- to 25-year reduction in life expectancy. Mounting evidence suggests that this excessive and premature mortality is attributable not only to suicides and accidents but also to various medical conditions, with cardiovascular diseases constituting the most common cause of natural death. Dysfunctional regulation of body systems and highly associated unique characteristics of bipolar disorder, including the pathophysiology, lifestyle changes, and psychotropic side effects, are the possible explanation for this unfavorable outcome. However, reports on the direct physiological measurement of the dysfunctional regulation of body systems in patients with bipolar disorder across life still remain limited. Early identification of such physiological predictors might be of value on the prevention of the subsequent cardiovascular morbidity and mortality in this high risk group. Standard 12-lead electrocardiogram, complete blood count, as well as serum fasting glucose, cholesterol, high-density cholesterol, and triglyceride are the routine and reliable examination in clinical practice. Furthermore, these laboratory examinations could reflect the autonomic nervous system dysfunction, systemic inflammation, and metabolic dysregulation in human body. Therefore, investigation of the association between these data and the subsequent cardiovascular diseases across life might give us an initial insight to find out early physiological predictors. In the ongoing study, we prepare to recruit inpatients who were more than 56 years old and had DSM-IV bipolar I disorder from Taipei City Psychiatric Center and Taipei Medical University Hospital. Those receiving the diagnosis of cardiovascular diseases (ICD 401-429) during the index hospitalization will be assigned to the case group. Each subject in the case group will be matched with two control patients without cardiovascular diseases for the age, sex, and date of index admission. Clinical data and the results of laboratory tests at the acute psychiatric hospitalizations across life will then be longitudinally obtained by reviewing medical records. After collecting the data, we will use generalized estimating equation in the statistical model to identify physiological predictors for cardiovascular diseases in patients with bipolar disorder. It is estimated a total of 100 bipolar cases comorbid with cardiovascular diseases and 200 age-and-sex matched bipolar controls recruited in this study. Hopefully, our results will be helpful in identifying early physiological predictors of cardiovascular diseases in bipolar disorder.