Feasibility and usefulness of brain imaging in catatonia

Clinical and neuroimaging predictors of benzodiazepine response in catatonia: A machine learning approach

Catatonia is a well characterized psychomotor syndrome combining motor, behavioural and neurovegetative signs. Benzodiazepines are the first-choice treatment, effective in 70 % of cases. Currently, the factors associated with benzodiazepine resistance remain unknown. We aimed to develop machine learning models using clinical and neuroimaging data to predict benzodiazepine response in catatonic patients. This study examined a cohort of catatonic patients who underwent standardized clinical evaluation, 3 T brain MRI, and benzodiazepine trial. Based on clinical response, patients were classified as benzodiazepine responders or non-responders. Cortical thickness and regional brain volumes were measured. Two machine learning models (linear model and gradient boosting tree model) were developed to identify predictors of treatment response using clinical, demographic, and neuroimaging data. The cohort included 65 catatonic patients, comprising 30 benzodiazepine responders and 35 non-responders. Using clinical data alone, the linear model achieved 63% precision, 51% recall, a specificity of 61%, and 58% AUC, while the gradient boosting tree (GBT) model attained 46% precision, 60% recall, a specificity of 62% and 64% AUC. Incorporating neuroimaging data improved model performance, with the linear model achieving 66% precision, 57% recall, a specificity of 67%, and 70% AUC, and the GBT model attaining 50% precision, 50% recall, a specificity of 62% and 70% AUC. The integration of imaging data with demographic and clinical information significantly enhanced the predictive performance of the models. The duration of the catatonic syndrome, along with the presence of mitgehen (passive obedience) and immobility/stupor, and the volume of the right medial orbito-frontal cortex emerged as important factors in predicting non-response to benzodiazepines.

Exploring seasonality in catatonia diagnosis: Evidence from a large-scale population study

Catatonia is a severe psychomotor syndrome mainly associated with psychiatric disorders, such as mood disorders and schizophrenia. Seasonal patterns have been described for these psychiatric disorders, and a previous study conducted in South London showed for the first time a seasonal pattern in the onset of catatonia. In this study, we aim to extend those findings to a larger national sample of patients admitted to French metropolitan hospitals, between 2015 and 2022, and to perform subgroup analyses by the main associated psychiatric disorder. A total of 6225 patients diagnosed with catatonia were included. A seasonal pattern for catatonia diagnosis was described, using cosinor models. Two peaks of diagnoses for catatonic cases were described in March and around September-October. Depending on the associated psychiatric disorder, the seasonality of catatonia diagnosis differed. In patients suffering with mood disorders, peaks of catatonia diagnosis were found in March and July. For patients suffering with schizophrenia, no seasonal pattern was found.

Evidence-based consensus guidelines for the management of catatonia: Recommendations from the British Association for Psychopharmacology

The British Association for Psychopharmacology developed an evidence-based consensus guideline on the management of catatonia. A group of international experts from a wide range of disciplines was assembled. Evidence was gathered from existing systematic reviews and the primary literature. Recommendations were made on the basis of this evidence and were graded in terms of their strength. The guideline initially covers the diagnosis, aetiology, clinical features and descriptive epidemiology of catatonia. Clinical assessments, including history, physical examination and investigations are then considered. Treatment with benzodiazepines, electroconvulsive therapy and other pharmacological and neuromodulatory therapies is covered. Special regard is given to periodic catatonia, malignant catatonia, neuroleptic malignant syndrome and antipsychotic-induced catatonia. There is attention to the needs of particular groups, namely children and adolescents, older adults, women in the perinatal period, people with autism spectrum disorder and those with certain medical conditions. Clinical trials were uncommon, and the recommendations in this guideline are mainly informed by small observational studies, case series and case reports, which highlights the need for randomised controlled trials and prospective cohort studies in this area.