DeltaScan for the Assessment of Acute Encephalopathy and Delirium in ICU and non-ICU Patients, a Prospective Cross-Sectional Multicenter Validation Study.

OBJECTIVES: To measure the diagnostic accuracy of DeltaScan: a portable real-time brain state monitor for identifying delirium, a manifestation of acute encephalopathy (AE) detectable by polymorphic delta activity (PDA) in single-channel electroencephalograms (EEGs). DESIGN: Prospective cross-sectional study. SETTING: Six Intensive Care Units (ICU's) and 17 non-ICU departments, including a psychiatric department across 10 Dutch hospitals. PARTICIPANTS: 494 patients, median age 75 (IQR:64-87), 53% male, 46% in ICUs, 29% delirious. MEASUREMENTS: DeltaScan recorded 4-minute EEGs, using an algorithm to select the first 96 seconds of artifact-free data for PDA detection. This algorithm was trained and calibrated on two independent datasets. METHODS: Initial validation of the algorithm for AE involved comparing its output with an expert EEG panel's visual inspection. The primary objective was to assess DeltaScan's accuracy in identifying delirium against a delirium expert panel's consensus. RESULTS: DeltaScan had a 99% success rate, rejecting 6 of the 494 EEG's due to artifacts. Performance showed and an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.86 (95% CI: 0.83-0.90) for AE (sensitivity: 0.75, 95%CI=0.68-0.81, specificity: 0.87 95%CI=0.83-0.91. The AUC was 0.71 for delirium (95%CI=0.66-0.75, sensitivity: 0.61 95%CI=0.52-0.69, specificity: 72, 95%CI=0.67-0.77). Our validation aim was an NPV for delirium above 0.80 which proved to be 0.82 (95%CI: 0.77-0.86). Among 84 non-delirious psychiatric patients, DeltaScan differentiated delirium from other disorders with a 94% (95%CI: 87-98%) specificity. CONCLUSIONS: DeltaScan can diagnose AE at bedside and shows a clear relationship with clinical delirium. Further research is required to explore its role in predicting delirium-related outcomes.

The Delirium Interview as a new reference standard in studies on delirium assessment tools.

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: 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.

Acquisition of L2 morphology by adult language learners.

Learning a new language requires the acquisition of morphological units that enable the fluent use of words in different grammatical contexts. While accumulating research has elucidated the neural processing of native morphology, much less is known about how second-language (L2) learners acquire and process morphology in their L2. To address this question, we presented native speakers as well as beginning and advanced learners of Finnish with spoken (1) derived words, (2) inflected words, (3) novel derivations (novel combinations of existing stem + suffix), and (4) pseudo-suffixed words (existing stem + pseudo-suffix) in a passive listening EEG experiment. An early (60 msec after suffix deviation point) positive ERP response showed no difference between inflections and derivations, suggesting similar early parsing of these complex words. At 130 msec, derivations elicited a lexical ERP pattern of full-form memory-trace activation, present in the L2 beginners and advanced speakers to different degrees, implying a shift from lexical processing to more dual parsing and lexical activation of the complex forms with increasing proficiency. Pseudo-suffixed words produced a syntactic pattern in a later, 170-240 msec time-window, exhibiting enhanced ERPs compared to well-formed inflections, indicating second-pass syntactic parsing. Overall, the L2 learners demonstrated a gradual effect of proficiency towards L1-like responses. Advanced L2 learners seem to have developed memory traces for derivations and their neurolinguistic system is capable of early automatic parsing. This suggests that advanced learners have already developed sensitivity to morphological information, while such knowledge is weak in beginners. Discrepancies in ERP dynamics and topographies indicate partially differing recruitment of the language network in L1 and L2. In beginners, response differences between existing and novel morphology were scarce, implying that representations for complex forms are not yet well-established. The results suggest successful development of brain mechanisms for automatic processing of L2 morphology, capable of gradually attaining L1-like functionality with increasing proficiency.

Shaving Bridges and Tuning Kitaraa: The Effect of Language Switching on Semantic Processing.

Language switching has been repeatedly found to be costly. Yet, there are reasons to believe that switches in language might benefit language comprehension in some groups of people, such as less proficient language learners. This study therefore investigated the interplay between language switching and semantic processing in groups with varying language proficiency. EEG was recorded while L2 learners of English with intermediate and high proficiency levels read semantically congruent or incongruent sentences in L2. Translations of congruent and incongruent target words were additionally presented in L1 to create intrasentential language switches. A control group of English native speakers was tested in order to compare responses to non-switched stimuli with those of L2 learners. An omnibus ANOVA including all groups revealed larger N400 responses for non-switched incongruent stimuli compared to congruent stimuli. Additionally, despite switches to L1 at target word position, semantic N400 responses were still elicited in both L2 learner groups. Further switching effects were reflected by an N400-like effect and a late positivity complex, pointing to possible parsing efforts after language switches. Our results therefore show that although language switches are associated with increased mental effort, switches may not necessarily be costly on the semantic level. This finding contributes to the ongoing discussion on language inhibition processes, and shows that, in these intermediate and high proficient L2 learners, semantic processes look similar to those of native speakers of English.

Language control mechanisms differ for native languages: Neuromagnetic evidence from trilingual language switching.

How does the brain process and control languages that are learned at a different age, when proficiency in all these languages is high? Early acquired strong languages are likely to have higher baseline activation levels than later learned less-dominant languages. However, it is still largely unknown how the activation levels of these different languages are controlled, and how interference from an irrelevant language is prevented. In this magnetoencephalography (MEG) study on language switching during auditory perception, early Finnish-Swedish bilinguals (N = 18) who mastered English with high proficiency after childhood were presented with spoken words in each of the three languages, while performing a simple semantic categorisation task. Switches from the later learned English to either of the native languages resulted in increased neural activation in the superior temporal gyrus (STG) 400-600ms after word onset (N400m response), whereas such increase was not detected for switches from native languages to English or between the native languages. In an earlier time window of 350-450ms, English non-switch trials showed higher activation levels in the inferior frontal gyrus (IFG), pointing to ongoing inhibition of the native languages during the use of English. Taken together, these asymmetric switch costs suggest that native languages are suppressed during the use of a non-native language, despite the receptive nature of the language task. This effect seems to be driven mostly by age of acquisition or language exposure, rather than proficiency. Our results indicate that mechanisms of control between two native languages differ from those of a later learned language, as upbringing in an early bilingual environment has likely promoted automatiation of language control specifically for the native languages.