Characteristics, symptomatology and naturalistic treatment in individuals at-risk for bipolar disorders: Baseline results in the first 180 help-seeking individuals assessed at the dresden high-risk project

AbstractBackground ering results from the early recognition and intervention in psychosis, identification and treatment of individuals with at-risk states for the development of bipolar disorders (BD) could improve the course and severity of illness and prevent long-term consequences. Different approaches to define risk factors and groups have recently been published, data on treatment options are still missing. s eeking persons at the early recognition center in Dresden, Germany, were assessed with a standardized diagnostic procedure including following risk factors for BD: familial risk, increasing mood swings, subsyndromal (hypo)manic symptoms, specific sleep and circadian rhythm disturbances, anxiety/fearfulness, affective disorder, decreased psychosocial functioning, increasing periodic substance use, and attention-deficit/hyperactivity disorder. Based on symptomatology and current and/or life-time psychiatric diagnosis, subjects with an at-risk state were offered individual treatment options. s 180 referred and screened persons, 29 (16%) met criteria for at-risk state for BD. Altogether, 27 (93%) at-risk individuals fulfilled criteria for a current and/or life-time mental illness other than BD; 14 (48%) had received pharmacological and/or psychotherapeutic treatment in the past. Treatments recommended included psychoeducation (100%), psychotherapy alone (62%), pharmacotherapy alone (17%), and psychotherapy+pharmacotherapy (14%). sions ntify at-risk states for BD, a multifactorial approach including all known risk markers should be used. As most at-risk patients meet criteria for other mental disorders, the short- and long-term impact of different treatment strategies on symptomatic, functional and diagnostic outcomes requires detailed investigation. tions sample size of at-risk individuals, lack of sufficient prospective data and control groups.