Progress in neuro-psychopharmacology & biological psychiatry · 2025
Predicting the response to Lorazepam in catatonia: a network analysis approach.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Mastellari Tomas, Gauld Christophe, Fovet Thomas, Amad Ali
Аннотация
BACKGROUND: Lorazepam, a widely used benzodiazepine, is the first-line treatment for catatonia. In case of resistance to Lorazepam, a trial-and-error approach is usually followed, increasing the risk of severe medical complications. To date, the mechanisms underlying non-response to Lorazepam remain unclear. The aims of this study were to determine whether network analysis can identify symptom-based predictors of response to Lorazepam and assess whether the structure of catatonic symptoms differs between responders and non-responders.
METHODS: A cohort of patients with catatonia (n = 136) was recruited at a specialized clinical center. Network analyses were conducted using the Bush-Francis Catatonia Rating Scale items, to describe the structure of catatonic symptoms in responders and non-responders to Lorazepam. Symptom clusters were identified using a spinglass algorithm and centrality measures were compared between groups. Additionally, network outcome analyses were performed to identify clinical predictors of Lorazepam response.
RESULTS: Three clusters of catatonic symptoms were identified, with similar structure between responders and non-responders. No significant differences were found in centrality measures. The most central symptoms were characteristics of hyperkinetic catatonia. Immobility / stupor emerged as the unique direct predictor of response to Lorazepam.
CONCLUSION: The overall structure of catatonic symptoms appears stable between responders and non-responders. Hypokinetic symptoms, particularly immobility and stupor, serve as strong predictors of Lorazepam response. Given the critical need for early treatment prediction to optimize therapeutic interventions and reduce catatonia-related mortality, further research is needed to refine clinical predictors of Lorazepam response.
METHODS: A cohort of patients with catatonia (n = 136) was recruited at a specialized clinical center. Network analyses were conducted using the Bush-Francis Catatonia Rating Scale items, to describe the structure of catatonic symptoms in responders and non-responders to Lorazepam. Symptom clusters were identified using a spinglass algorithm and centrality measures were compared between groups. Additionally, network outcome analyses were performed to identify clinical predictors of Lorazepam response.
RESULTS: Three clusters of catatonic symptoms were identified, with similar structure between responders and non-responders. No significant differences were found in centrality measures. The most central symptoms were characteristics of hyperkinetic catatonia. Immobility / stupor emerged as the unique direct predictor of response to Lorazepam.
CONCLUSION: The overall structure of catatonic symptoms appears stable between responders and non-responders. Hypokinetic symptoms, particularly immobility and stupor, serve as strong predictors of Lorazepam response. Given the critical need for early treatment prediction to optimize therapeutic interventions and reduce catatonia-related mortality, further research is needed to refine clinical predictors of Lorazepam response.