Background The purpose of our study was to identify predictors of a high risk of involuntary psychiatric in-patient treatment. Methods We carried out a detailed analysis of the 1773 mental health records of all the persons treated as in-patients under the PsychKG NRW (Mental Health Act for the state of North Rhine-Westphalia, Germany) in a metropolitan region of Germany (the City of Cologne) in 2011. 3991 mental health records of voluntary in-patients from the same hospitals served as a control group. We extracted medical, sociodemographic and socioeconomic data from these records. Apart from descriptive statistics, we used a prediction model employing chi-squared automatic interaction detection (CHAID). Results Among involuntary patients, organic mental disorders (ICD10: F0) and schizophrenia and other psychotic disorders (ICD10: F2) were overrepresented. Patients treated as in-patients against their will were on average older, they were more often retired and had a migratory background. The Exhaustive CHAID analysis confirmed the main diagnosis to be the strongest predictor of involuntary in-patient psychiatric treatment. Other predictors were the absence of outpatient treatment prior to admission, admission outside of regular service hours and migratory background. The highest risk of involuntary treatment was associated with patients with organic mental disorders (ICD 10: F0) who were married or widowed and patients with non-organic psychotic disorders (ICD10: F2) or mental retardation (ICD10: F7) in combination with a migratory background. Also, referrals from general hospitals were frequently encountered. Conclusions We identified modifiable risk factors for involuntary psychiatric in-patient treatment. This implies that preventive measures may be feasible and should be implemented to reduce the rate of involuntary psychiatric in-patient treatment. This may include efforts to establish crisis resolution teams to improve out-patient treatment, train general hospital staff in deescalation techniques, and develop special programs for patients with a migratory background.

Carbamazepine (CBZ) has been successfully employed in a variety of neurological and psychiatric disorders. The side-effects of CBZ treatment have been extensively studied. As little is known about the symptoms and prognosis of CBZ overdose, our objective was to identify the factors relevant to its prognosis. In a retrospective study of 427 cases, we analysed the distribution of age, sex, total CBZ dose, CBZ plasma level, frequency of symptoms and their association with outcome. In those patients who recovered, coma, somnolence, cerebellar syndrome and epileptic seizures were the most common manifestations of CBZ overdose. In fatal courses coma, epileptic seizures, respiratory depression and respiratory arrest ranked highest. Cardiac arrhythmias and other cardiovascular complications were rare. In 41 of 307 patients (13%) in whom outcome was reported, intoxication was fatal. The occurrence of seizures and CBZ doses exceeding 24 g proved to be important indicators of a fatal outcome. The course of intoxication seems to be more benign in patients aged below 15 years.

Background The purpose of this study was to identify factors associated with a high risk of involuntary psychiatric in-patient hospitalization both on the individual level and on the level of mental health services and the socioeconomic environment that patients live in. Methods The present study expands on a previous analysis of the health records of 5764 cases admitted as in-patients in the four psychiatric hospitals of the Metropolitan City of Cologne, Germany, in the year 2011 (1773 cases treated under the Mental Health Act and 3991 cases treated voluntarily). Our previous analysis had included medical, sociodemographic and socioeconomic data of every case and used a machine learning-based prediction model employing chi-squared automatic interaction detection (CHAID). Our current analysis attempts to improve the previous one through (1) optimizing the machine learning procedures (use of a different type of decision-tree prediction model (Classification and Regression Trees (CART) and application of hyperparameter tuning (HT)), and (2) the addition of patients’ environmental socioeconomic data (ESED) to the data set. Results Compared to our previous analysis, model fit was improved. Main diagnoses of an organic mental or a psychotic disorder (ICD-10 groups F0 and F2), suicidal behavior upon admission, admission outside of regular service hours and absence of outpatient treatment prior to admission were confirmed as powerful predictors of detention. Particularly high risks were shown for (1) patients with an organic mental disorder, specifically if they were retired, admitted outside of regular service hours and lived in assisted housing, (2) patients with suicidal tendencies upon admission who did not suffer from an affective disorder, specifically if it was unclear whether there had been previous suicide attempts, or if the affected person lived in areas with high unemployment rates, and (3) patients with psychosis, specifically those who lived in densely built areas with a large proportion of small or one-person households. Conclusions Certain psychiatric diagnoses and suicidal tendencies are major risk factors for involuntary psychiatric hospitalization. In addition, service-related and environmental socioeconomic factors contribute to the risk for detention. Identifying modifiable risk factors and particularly vulnerable risk groups should help to develop suitable preventive measures.

Medical and psychological care of refugees is among the most important current challenges in German health politics. Work with patients from this heterogeneous group who have often faced severe stress before, during and after their migration is currently based on a thin data foundation. Based on introductory information on current knowledge concerning psychiatric morbidity of refugees this article presents the psychiatric care of refugees at LVR Clinics Cologne - a psychiatric specialty hospital situated in North Rhine-Westphalia, Germany. A sample of 239 cases of refugee patients who were referred to in- and outpatient departments of the LVR Clinics Cologne between April 2015 and March 2016 are evaluated in respect of diagnoses, admission modalities and socio-demographic variables. The majority of principal diagnoses (40.2%) belong to the group of stress-related and somatoform disorders (F4 in ICD-10). Mood disorders (F3 in ICD-10) represented 31.0%, followed by mental and behavioral disorders due to psychoactive substance use (F1 in ICD-10) with 15.1%. Posttraumatic Stress Disorder (PTSD) was the most prevalent diagnose (13.0%). Among the 29 countries of the patients' origin Afghanistan (10,0%), Serbia (9.6%) and Kosovo (8.8%) were the most abundant. The diagnoses and the high rate of acute psychiatric events reflect the massive psychological pressure of the patients. The important role of interpreters and mediators specialized in language and integration in the treatment process is emphasized.