Background Although obsessive-compulsive disorder (OCD) is one of the most common mental disorders, it takes up to 17 years for patients with OCD to receive adequate therapy. According to existing outdated literature, this study aimed to investigate the current duration between symptom onset and diagnosis and between diagnosis and the beginning of therapy separately. Methods In a cross-sectional study, N = 100 patients diagnosed with OCD undergoing treatment in a psychiatric outpatient department were assessed, using self-report questionnaires on sociodemographic and clinical variables. Based on self-reported information, the durations between age at symptom onset and age at diagnosis, and between age at diagnosis and beginning of therapy were calculated. To investigate associated factors, two subgroups of patients, one with a short duration between symptom onset and diagnosis < 7 years, and another with a long duration between symptom onset and diagnosis ≥ 7 years, respectively, were compared. Results and conclusion Patients reported first symptoms of OCD at a mean age of 18.72 years. The mean duration between age at symptom onset and age at diagnosis was 12.78 years and the mean duration between age at diagnosis and the beginning of therapy was 1.45 years. Subgroup comparison indicated that patients with a short duration between symptom onset and diagnosis were significantly younger than patients with a long duration. However, patients with a short duration between symptom onset and diagnosis were at an older age when they reported first symptoms of OCD. Further, they showed less severe symptoms of OCD, higher functioning levels, and less self-stigmatization than patients with a long duration. It can be concluded that the duration until patients with OCD are diagnosed correctly and receive adequate treatment is still very long. Therefore, the duration between symptom onset and diagnosis should be shortened. Further, the duration between diagnosis and the beginning of therapy could be a good additional approach to reduce the overall duration of untreated disorder.

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Ultra-rapid cycling is a rare form of bipolar affective disorder with more than four mood episodes per month (ICD-10: F31.8). A dysregulation of brain arousal has been discussed as a potential pathogenetic mechanism underlying both affective disorders and attention deficit hyperactivity disorder (ADHD). 2 Brain arousal denotes a global functional state of the brain and corresponds behaviorally to different levels of wakefulness. In healthy individuals, brain arousal adapts flexibly to changing environmental requirements. For example, during the wake-sleep transition, brain arousal is gradually downregulated, whereas an external threat may result in a sudden upregulation of arousal. Brain arousal and its regulation can be reliably assessed using electroencephalography (EEG).A previous study provided first evidence that bipolar patients with depressive episodes differ in their arousal regulation from bipolar patients with manic episodes. Specifically, upregulated arousal was found during depressive episodes, whereas patients with manic episodes show an earlier decline to low arousal levels than healthy controls. 3 To date, such comparisons have not been conducted based on longitudinal studies of the same individuals. In addition, brain arousal regulation has not been previously studied in patients with ultra-rapid cycling. In this context, we examined the patterns of brain arousal regulation in a successfully treated patient with ultra-rapid cycling. Based on the arousal regulation model of affective disorders, 2 we expected to find upregulated (hyperstable) arousal in the depressive state and a faster onset of low EEG-vigilance stages (indicating states of arousal) and lower arousal level in the hypomanic state as compared to the remitted state. To objectively assess brain arousal and its regulation, we applied the Vigilance Algorithm Leipzig (VIGALL; version 2.1; manual and download at https://research.uni-leipzig.de/vigall/) in the current study. VIGALL is an EEG-and electrooculogram (EOG)-based algorithm, using low-resolution electromagnetic tomography, that allows an automatic classification of EEG-vigilance stages within multichannel EEG recordings (for a detailed description, see 1 ). Preprocessing and EEG-vigilance staging were conducted as previously described. 3 | CASE PRESENTATIONMr. J, a 46-year-old white male (body mass index [BMI] 33.6), was admitted to our inpatient psychiatric unit with rapidly switching mood states for adjustment of medication. Ten months prior to presentation, he first developed ultra-rapid cycling after antidepressant therapy with venlafaxine. Following this hospitalization, he was diagnosed with bipolar disorder as a patient of our outpatient clinic, and then stabilized with lithium. On current presentation, Mr. J was complaining about depressed mood, irritability and high inner tension, sleeplessness and feeling high. He reported cycling of affective states between 24 and 72 hours, with depressive states in the morning and switches to mania in the afternoon as well as mixed moo...

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