The role of the electroencephalogram (EEG) in determining the aetiology of catatonia: a systematic review and meta-analysis of diagnostic test accuracy
Paris Hosseini, Rebecca Whincup, Karrish Devan, Dory Anthony Ghanem, Jack B. Fanshawe, Aman Saini, Benjamin Cross, Apoorva Vijay, Tomas Mastellari, Umesh Vivekananda, Steven R. White, Franz Brunnhuber, Michael S. Zandi, Anthony S. David, Ben Carter, Dominic Oliver, Glyn Lewis, Charles Fry, Puja R. Mehta, Biba Stanton, Jonathan Rogers
Abstract
Background: Catatonia is a psychomotor syndrome that has a wide range of aetiologies. Determining whether catatonia is due to a medical or psychiatric cause is important for directing treatment but is clinically challenging. We aimed to ascertain the performance of the electroencephalogram (EEG) in determining whether catatonia has a medical or psychiatric cause, conventionally defined. Methods: < 5), which were unsuitable for formal meta-analytic methods but had detailed individual patient level data, enabling additional sensitivity analyses. Risk of bias and applicability were assessed with the QUADAS-2 tool for larger studies, and with a published tool designed for case reports and series for smaller studies. The primary outcomes were sensitivity and specificity, which were derived using a bivariate mixed-effects regression model. Findings: of 74% (95% CI 42-100%). The area under the summary ROC curve offered excellent discrimination (AUC = 0.83). The positive likelihood ratio was 2.4 (95% CI 1.4-4.1) and the negative likelihood ratio was 0.28 (95% CI 0.15-0.51). Only 5 studies had low concerns in terms of risk of bias and applicability, but a sensitivity analysis limited to these studies was similar to the main analysis. Among the 343 smaller studies, 399 patients were included, resulting in a sensitivity of 0.76 (95% CI 0.71-0.81), specificity of 0.67 (0.57-0.76) and AUC = 0.71 (95% CI 0.67-0.76). In multiple sensitivity analyses, the results were robust to the exclusion of reports of studies and individuals considered at high risk of bias. Features of limbic encephalitis, epileptiform discharges, focal abnormality, or status epilepticus were highly specific to medical catatonia, but features of encephalopathy had only moderate specificity and occurred in 23% of the cases of psychiatric catatonia in smaller studies. Interpretation: In cases of diagnostic uncertainty, the EEG should be used alongside other investigations to ascertain whether the underlying cause of catatonia is medical. The main limitation of this review is the differing thresholds for considering an EEG abnormal between studies. Funding: Wellcome Trust, NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust.