Background:The reference standard in studies on delirium assessment tools is usually based on the clinical judgment of only one delirium expert and may be concise, unstandardized, or not specified at all. This multicenter study investigated the performance of the Delirium Interview, a new reference standard for studies on delirium assessment tools allowing classification of delirium based on written reports. Methods:We tested the diagnostic accuracy of our standardized Delirium Interview by comparing delirium assessments of the reported results with live assessments. Our reference, the live assessment, was performed by two delirium experts and one well-trained researcher who registered the results. Their delirium assessment was compared to the majority vote of three other independent delirium experts who judged the rapportage of the Delirium Interview.Our total pool consisted of 13 delirium experts with an average of 13 ± 8 years of experience.Results: We included 98 patients (62% male, mean age 69 ± 12 years), of whom 56 (57%) intensive care units (ICUs) patients, 22 (39%) patients with a Richmond Agitation Sedation Scale (RASS) < 0 and 26 (27%) non-verbal assessments. The overall prevalence of delirium was 28%. The Delirium Interview had a sensitivity of 89% (95% confidence interval [CI]: 71%-98%) and specificity of 82% (95% CI: 71%-90%), compared to the diagnosis of an independent panel of two delirium experts and one researcher who examined the patients themselves. Negative and positive predictive values were 95% (95% CI:
Background The reference standard in studies on delirium assessment tools is usually based on the clinical judgement of only one delirium expert, and may be concise, unstandardized, or not specified at all. This multicenter study investigated the performance of the Delirium Interview, a new reference standard for studies on delirium assessment tools, allowing classification of delirium based on written reports. Methods We tested the diagnostic accuracy of our standardized Delirium Interview by comparing delirium assessments of the reported results with live assessments. Our reference, the live assessment, was performed by two delirium experts and one well-trained researcher who registered the results. Their delirium assessment was compared with the majority vote of three other independent delirium experts who judged the rapportage of the Delirium Interview. Our total pool consisted of 13 delirium experts with an average of 13 SD 8 years of experience. Results We included 98 patients (62% male, mean age 69 SD 12 years), of whom 56 (57%) Intensive Care Units (ICU) patients, 22 (39%) patients with a Richmond Agitation Sedation Scale (RASS)<0 and 26 (27%) non-verbal assessments. The overall prevalence of delirium was 28%. The Delirium Interview had a sensitivity of 89% (95% Confidence Interval (CI): 71-98%) and specificity of 82% (95%CI: 71-90%), compared to the diagnosis of an independent panel of two delirium experts and one researcher who examined the patients themselves. Negative and positive predictive values were 95% (95%CI: 86-0.99%) respectively 66% (95%CI: 49-80%). Stratification into ICU and non-ICU patients yielded similar results. Conclusion The Delirium Interview is a feasible reference method for large study cohorts evaluating delirium assessment tools since experts could assess delirium with high accuracy without seeing the patient at the bedside.
Aim Delirium, a clinical manifestation of acute encephalopathy, is often unrecognised. An important electroencephalography (EEG) characteristic of acute encephalopathy is polymorphic delta activity (PDA), which can be detected automatically. We aimed to study whether automated assessment of PDA in unselected EEG could detect acute encephalopathy that presents clinically as delirium. Methods We assessed PDA in 145 elderly patients using the first 96 seconds of unselected single-channel EEG (Fp2,Pz). We compared fully automated PDA detection with visual inspection by EEG experts. Additionally, we tested its performance as a delirium monitor by comparing PDA detection with a standardized delirium assessment by a clinical expert panel. Results PDA detection showed an area under the receiver operating characteristic (AUC) of 0.86 compared to EEG experts. When compared with the delirium classification of clinical experts, PDA detection achieved an AUC of 0.78. PDA detection correlated with the likelihood of delirium, its severity and the levels of attention and consciousness (all p<0.001). Conclusion Automated PDA detection in unselected, single-channel EEG can classify acute encephalopathy clinically presenting as delirium. Significance A fully automated EEG algorithm can assist in the recognition of delirium.
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