Diagnosing catatonia and its dimensions: Cluster analysis and factor solution using the Bush Francis Catatonia Rating...

Advances in research into catatonia in the preceding two decades has offered increasing clarity and an improved understanding of various aspects of this complex syndrome. Despite the above, there are several aspects that hinder a broader interpretation of these findings, the most common being a lack of consensus on the criteria required for diagnosing catatonia. Whilst being the most frequently used tool for diagnosis, the number of signs from Bush-Francis Catatonia Rating Scale (BFCRS) needed to diagnose catatonia remain unclear. This study aimed to determine the number of signs required to accurately diagnose catatonia using BFCRS and delineate its dimensions in an acute inpatient unit in the Indian setting. A random sample of 300 patients were evaluated for catatonia within 24 h of admission. Cluster Analysis followed by discriminant analysis and receiver operating curve analysis (ROC) provided cut-off values for diagnosing catatonia syndrome. Principle Component Analysis (PCA) with varimax rotation was used to identify factors in those with catatonia. Findings revealed that a cut off of two signs from both Bush-Francis Catatonia Screening Instrument or BFCSI (sensitivity of 100 %, specificity of 96.2 % as well as a positive predictive value [PPV] of 79.6 % and negative predictive value [NPV] 100 % with ROC AUC value of 0.98) and complete BFCRS (sensitivity of 100 % and specificity of 90.7 %, PPV of 80.7 and NPV of 100 % with ROC AUC for at least two items cut-off being 0.95) accurately detected catatonia. However, the prevalence of catatonia in the same population increased by 4% from 16.3% to 20.3% using the BFCRS rather than the BFCSI. The BFCRS generated a 3-factor model accounting for 65.48 % variance offering the best fit, indicating three discrete dimensions to catatonia, namely retarded, excited and what we named as "aberrant volitional". Interestingly, the aberrant volitional dimension comprises of signs that need to be elicited rather than passively observed and excluding one, none of them are part of the BFCSI. Findings of this study suggest that the BFCRS more accurately detects catatonia rather than the BFCSI. Additionally, three dimensions of catatonia more coherently explain the catatonic syndrome given that 55.7 % of the sample had signs from more than one factor concurrently. We propose that the BFCRS rather than BFCSI be routinely administered for evaluating all suspected cases of catatonia to ensure more accurate detection as well as identifying the aberrant volitional dimensional signs more consistently. The three-dimensional model also offers great opportunities to further unravel the pathophysiological basis of catatonic signs more systematically.