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诊断紧张症及其维度:使用布什-弗朗西斯紧张症评定量表(BFCRS)进行聚类分析和因子分析

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

作者信息

Aandi Subramaniyam Bhaskaran, Muliyala Krishna Prasad, Suchandra Hari Hara, Reddi Venkata Senthil Kumar

机构信息

Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, 560029, India.

Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, 560029, India.

出版信息

Asian J Psychiatr. 2020 Aug;52:102002. doi: 10.1016/j.ajp.2020.102002. Epub 2020 Apr 10.

Abstract

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.

摘要

在过去二十年中,对紧张症的研究取得了进展,使人们对这一复杂综合征的各个方面有了越来越清晰的认识和更好的理解。尽管如此,仍有几个方面阻碍了对这些研究结果的更广泛解读,最常见的是在紧张症诊断标准上缺乏共识。虽然布什 - 弗朗西斯紧张症评定量表(BFCRS)是最常用的诊断工具,但诊断紧张症所需的量表体征数量仍不明确。本研究旨在确定使用BFCRS准确诊断紧张症所需的体征数量,并在印度的一个急性住院单元中描绘其维度。对300名患者的随机样本在入院后24小时内进行了紧张症评估。聚类分析,随后进行判别分析和受试者工作特征曲线分析(ROC),提供了诊断紧张症综合征的临界值。使用具有方差最大化旋转的主成分分析(PCA)来识别紧张症患者的因素。研究结果显示,布什 - 弗朗西斯紧张症筛查工具(BFCSI)的两个体征临界值(敏感性为100%,特异性为96.2%,阳性预测值[PPV]为79.6%,阴性预测值[NPV]为100%,ROC曲线下面积值为0.98)以及完整的BFCRS(敏感性为100%,特异性为90.7%,PPV为80.7,NPV为100%,至少两项临界值的ROC曲线下面积为0.95)能够准确检测出紧张症。然而,在同一人群中,使用BFCRS而非BFCSI时,紧张症的患病率从16.3%上升了4%,至20.3%。BFCRS生成了一个解释65.48%方差的三因素模型,拟合效果最佳,表明紧张症有三个不同维度,即迟缓型、兴奋型和我们命名的“异常意志型”。有趣的是,异常意志型维度包含需要诱发而非被动观察的体征,排除其中一项后,这些体征都不属于BFCSI。本研究结果表明,BFCRS比BFCSI更能准确检测紧张症。此外,紧张症的三个维度更连贯地解释了紧张症综合征,因为55.7%的样本同时具有来自多个因素的体征。我们建议,对于所有疑似紧张症病例,应常规使用BFCRS而非BFCSI进行评估,以确保更准确的检测,并更一致地识别异常意志型维度的体征。三维模型也为更系统地进一步揭示紧张症体征的病理生理基础提供了巨大机会。

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