Evaluation of point-of-care thumb-size bispectral electroencephalography device to quantify delirium severity and predict mortality

2021 ◽  
pp. 1-8
Author(s):  
Takehiko Yamanashi ◽  
Kaitlyn J. Crutchley ◽  
Nadia E. Wahba ◽  
Eleanor J. Sullivan ◽  
Katie R. Comp ◽  
...  
Keyword(s):  
Rating Scale ◽  
Point Of Care ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Negative Group ◽  
Positive Group ◽  
Prediction Of Mortality ◽  
Eeg Data ◽  
Poor Outcomes ◽  
Screening Scale

Background We have developed the bispectral electroencephalography (BSEEG) method for detection of delirium and prediction of poor outcomes. Aims To improve the BSEEG method by introducing a new EEG device. Method In a prospective cohort study, EEG data were obtained and BSEEG scores were calculated. BSEEG scores were filtered on the basis of standard deviation (s.d.) values to exclude signals with high noise. Both non-filtered and s.d.-filtered BSEEG scores were analysed. BSEEG scores were compared with the results of three delirium screening scales: the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), the Delirium Rating Scale-Revised-98 (DRS) and the Delirium Observation Screening Scale (DOSS). Additionally, the 365-day mortalities and the length of stay (LOS) in the hospital were analysed. Results We enrolled 279 elderly participants and obtained 620 BSEEG recordings; 142 participants were categorised as BSEEG-positive, reflecting slower EEG activity. BSEEG scores were higher in the CAM-ICU-positive group than in the CAM-ICU-negative group. There were significant correlations between BSEEG scores and scores on the DRS and the DOSS. The mortality rate of the BSEEG-positive group was significantly higher than that of the BSEEG-negative group. The LOS of the BSEEG-positive group was longer compared with that of the BSEEG-negative group. BSEEG scores after s.d. filtering showed stronger correlations with delirium screening scores and more significant prediction of mortality. Conclusions We confirmed the usefulness of the BSEEG method for detection of delirium and of delirium severity, and prediction of patient outcomes with a new EEG device.

Delirium classification by the diagnostic and statistical manual – a moving target

2015 ◽  
Vol 27 (6) ◽  
pp. 881-882 ◽  
Author(s):  
Karin J. Neufeld
Keyword(s):  
Rating Scale ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Classification Systems ◽  
Diagnostic Systems ◽  
Delirium Assessment ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Medical Inpatients ◽  
Dsm Iv

The following paper, entitled “A Comparison of Delirium Diagnosis in Elderly Medical Inpatients using the CAM, DRS-R98, DSM-IV and DSM-5 Criteria” by Adamis and colleagues, reports the results of a single delirium assessment of 200 medical inpatients, aged 70 years and older. The aim was to compare the prevalence of delirium using two different diagnostic classification systems (DSM-5 and DSM-IV) and two commonly used research tools (Confusion Assessment Method and the Delirium Rating Scale-Revised ‘98). This editorial focuses on the comparison of the two versions of the DSM. The authors conclude that, while both diagnostic systems identify a core concept of delirium, the DSM-IV criteria are the most inclusive of the four approaches and the DSM-5, the most restrictive, identifying a prevalence of 19.5% and 13%, respectively in this sample. Furthermore, they conclude that these two systems do not appear to detect the same patients: only 14 of 26 (54%) individuals identified as delirious by the more exclusive DSM-5 criteria were also identified as such by DSM-IV.

scholarly journals Advanced Age Is Associated With Catatonia in Critical Illness: Results From the Delirium and Catatonia Prospective Cohort Investigation

2021 ◽  
Vol 12 ◽  
Author(s):  
Jennifer Connell ◽  
Ahra Kim ◽  
Nathan E. Brummel ◽  
Mayur B. Patel ◽  
Simon N. Vandekar ◽  
...  
Keyword(s):  
Intensive Care ◽  
Critical Illness ◽  
Critically Ill ◽  
Rating Scale ◽  
Medical Center ◽  
Adult Population ◽  
Academic Medical Center ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Advanced Age

Introduction: Catatonia, characterized by motor, behavioral and affective abnormalities, frequently co-occurs with delirium during critical illness. Advanced age is a known risk factor for development of delirium. However, the association between age and catatonia has not been described. We aim to describe the occurrence of catatonia, delirium, and coma by age group in a critically ill, adult population.Design: Convenience cohort, nested within two clinical trials and two observational cohort studies.Setting: Intensive care units in an academic medical center in Nashville, TN.Patients: 378 critically ill adult patients on mechanical ventilation and/or vasopressors.Measurements and Main Results: Patients were assessed for catatonia, delirium, and coma by independent and blinded personnel, the Bush Francis Catatonia Rating Scale, the Confusion Assessment Method for the Intensive Care Unit (ICU) and the Richmond Agitation and Sedation Scale. Of 378 patients, 23% met diagnostic criteria for catatonia, 66% experienced delirium, and 52% experienced coma during the period of observation. There was no relationship found between age and catatonia severity or age and presence of specific catatonia items. The prevalence of catatonia was strongly associated with age in the setting of critical illness (p < 0.05). Delirium and comas' association with age was limited to the setting of catatonia.Conclusion: Given the significant relationship between age and catatonia independent of coma and delirium status, these data demonstrate catatonia's association with advanced age in the setting of critical illness. Future studies can explore the causative factors for this association and further elucidate the risk factors for acute brain dysfunction across the age spectrum.

scholarly journals LO040: Do combined electrocardiogram rhythm and point of care ultrasound findings predict outcome during cardiac arrest? The second Sonography in Hypotension and Cardiac Arrest in the Emergency Department (SHOC-ED 2) Study

CJEM ◽  
2016 ◽  
Vol 18 (S1) ◽  
pp. S43-S44
Author(s):  
N. Beckett ◽  
P.R. Atkinson ◽  
J. Fraser ◽  
J. French ◽  
D. Lewis
Keyword(s):  
Cardiac Arrest ◽  
Hospital Discharge ◽  
Point Of Care ◽  
Cardiac Activity ◽  
Spontaneous Circulation ◽  
Final Outcome ◽  
Point Of Care Ultrasound ◽  
Negative Group ◽  
Positive Group ◽  
Negative Findings

Introduction: Survival to hospital discharge is better for PEA than asystole in out-of-hospital cardiac arrest. Point of care ultrasound (PoCUS) is widely used in cardiac arrest, although not mandated by ACLS guidelines. This study examines if initial PoCUS findings combined with cardiac rhythm are predictive of outcomes including return of spontaneous circulation (ROSC), survival to hospital admission (SHA), and hospital discharge (SHD). Methods: A database review was completed for patients arriving to a tertiary ED in asystole or PEA arrest from 2010 to 2014. Patients under 19y or with a previous DNR were excluded. Patients were grouped into those with cardiac activity on PoCUS and PEA on ECG (Positive group); those with no cardiac activity recorded on PoCUS and asystole on ECG (Negative group); and those with a mix of positive and negative findings (Indeterminate group). Data was analyzed for the frequency of ROSC, SHA, and SHD. Results: 186 patients met the study criteria, with 14 (8%) in the positive group, 134 (72%) in the negative group, and 38 (20%) in the indeterminate group. The positive group had significantly better initial outcomes than the negative group: ROSC: 78% (95% CI 49-95%) vs 17% (11-25%); OR 17.70 (4.57-168.5; p < 0.0001) and SHA: 29% (8-58%) vs 7% (3-12%); OR 5.56 (1.45-21.28; p = 0.022), and then the combined negative and indeterminate groups: ROSC: 22% (16-29%), OR 12.93 (3.43-48.73; p < 0.0001; SHA: 8% (5-13%); OR 4.51 (1.25-16.27; p = 0.033). There was no difference between the positive group and either the negative or combined groups for final outcome of SHD: 0% (0-23%) vs 1% (0-5%); OR 1.83 (0.08-39.97; p = 1.00; and vs 1% (0-5%); OR 1.67 (0.08-33.96; p = 1.00). The negative group had worse initial outcomes than the combined positive and indeterminate groups: ROSC 17% (11-25%) vs. 50% (36-64%) OR 0.21 (0.10-0.42; p < 0.0001); SHA 6% (3-12%) vs. 8% (5-13%) OR 0.34 (0.13-0.92; p = 0.0490). There was no difference in SHD: 1% (0-5%) vs. 1% (0-5%) OR 0.77 (0.07-8.71; p = 1.00). Conclusion: Our results suggest that although finding positive cardiac activity on ECG (PEA) and also on PoCUS is associated with greater ROSC and SHA, it does not identify patients with a final outcome of SHD.

scholarly journals The Harmonization of Four Delirium Instruments

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 520-520
Author(s):  
Benjamin Helfand ◽  
Elke Detroyer ◽  
Koen Milisen ◽  
Dimitrios Adamis ◽  
Richard Jones
Keyword(s):  
Structural Equation ◽  
Structural Equation Models ◽  
Rating Scale ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Clinical Syndrome ◽  
Kappa Statistics ◽  
Highly Correlated ◽  
Sum Scores ◽  
Meta Analyses

Abstract Delirium is a clinical syndrome characterized by acute cognitive dysfunction, which is pervasive in older persons. Delirium affects over 2.6 million Americans over age 65 annually. One major problem in detection of delirium is that over 40 different instruments have been created to identify delirium in different clinical settings. There is no single agreed upon reference standard instrument. In previous work, we performed a systematic review to identify the four most commonly cited and well-validated instruments for delirium identification. The aim of this study is to harmonize these four commonly used instruments: Confusion Assessment Method (CAM), Delirium Observation Screening Scale (DOSS), Delirium Rating Scale-Revised-98 (DRS-R-98), and Memorial Delirium Assessment Scale (MDAS). We used data from three separate sources (N = 1623). Participants were rated by multiple and overlapping instruments across studies, allowing us to apply item response theory linking procedures. We fit generalized structural equation models, and found unidimensional factor models fit well. We found the instruments were highly correlated (all r &gt; 0.9) and kappa statistics for delirium case identification were high (range: 0.89 to 0.95). We generated crosswalks to map sum scores on one instrument to another. Our results suggest the same underlying construct, propensity to delirium, is measured across the four instruments. The crosswalks facilitate comparison and combination for immediate clinical use or for future meta-analyses. In future steps, we will use our results to find the optimal cut-points for use across all instruments to identify delirium.

scholarly journals Derivation of a simple postoperative delirium incidence and severity prediction model

2018 ◽  
Author(s):  
Lindroth H. ◽  
Bratzke L. ◽  
Twadell S. ◽  
Rowley P. ◽  
Kildow J. ◽  
...  
Keyword(s):  
Prediction Model ◽  
Postoperative Delirium ◽  
Rating Scale ◽  
Factor Model ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Improvement Program ◽  
Risk Of Death ◽  
Framingham Risk ◽  
Severity Prediction

SummaryBackgroundDelirium is an important postoperative complication, yet a simple and effective delirium prediction model remains elusive. We hypothesized that the combination of the National Surgical Quality Improvement Program (NSQIP) risk calculator for serious complications (NSQIP-SC) or risk of death (NSQIP-D), and cognitive tests of executive function (Trail Making Test A and B [TMTA, TMTB]), could provide a parsimonious model to predict postoperative delirium incidence or severity.MethodsData were collected from 100 adults (≥65yo) undergoing major non-cardiac surgery. In addition to NSQIP-SC, NSQIP-D, TMTA and TMTB, we collected participant age, sex, ASA score, tobacco use, type of surgery, depression, Framingham risk score, and preoperative blood pressure. Delirium was diagnosed with the Confusion Assessment Method (CAM), and the Delirium Rating Scale-R-98 (DRS) was used to assess symptom severity. LASSO and Best Subsets logistic and linear regression were employed in line with TRIPOD guidelines.ResultsThree participants were excluded due to intraoperative deaths (2) and alcohol withdrawal (1). Ninety-seven participants with a mean age of 71.68±4.55, 55% male (31/97 CAM+, 32%) and a mean Peak DRS of 21.5±6.40 were analyzed. Of the variables included, only NSQIP-SC and TMTB were identified to be predictors of postoperative delirium incidence (p<0.001, AUROC 0.81, 95% CI: 0.72, 0.90) and severity (p<0.001, Adj. R2: 0.30).ConclusionsIn this cohort, preoperative NSQIP-SC and TMTB were identified as predictors of postoperative delirium incidence and severity. Future studies should verify whether this two-factor model could be used for accurate delirium prediction.

scholarly journals Pilot Testing of the UB-CAM Delirium Screening App

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 985-985
Author(s):  
Ashley Kuzmik ◽  
John Joseph Hannan ◽  
Long Ngo ◽  
Marie Boltz ◽  
Priyanka Shrestha ◽  
...  
Keyword(s):  
Older Adults ◽  
Rating Scale ◽  
Pragmatic Trial ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Clinical Dementia Rating ◽  
Systematic Screening ◽  
Pilot Testing ◽  
Computer Scientists ◽  
Hospitalized Older Adults

Abstract Systematic screening improves delirium detection among hospitalized older adults. This poster describes the development and pilot testing of an iOS-based app that incorporates the Ultra-Brief Confusion Assessment Method (UB-CAM), a two-step, delirium detection protocol that combines the UB-2 (2-item screener) and 3D-CAM. Previous work tested a RedCAP-based UB-CAM app in 527 patients with 399 physicians, nurses, and certified nursing assistants (CNAs) showing it can be successfully completed by all three disciplines in 97% of eligible patients in 80 seconds on average with over 85% accuracy relative to a gold standard. To improve accessibility to the clinical setting, our research team now collaborated with a computer scientist to develop and refine an iOS-based UB-CAM app for the iPhone and iPad through iterative “laboratory” testing. The app was piloted by non-clinician, research testers in hospitalized older adults (age x̄ =83, SD= 8.0) with dementia (Clinical Dementia Rating Scale x̄ =1.1, SD= .30); 64% were assessed to be delirium positive. The app demonstrated preliminary efficiency (90 seconds on average), high acceptability (100% satisfaction of users), and reliability (100% inter-rater). This project underscores the need for close collaboration between researchers, clinicians, and computer scientists with iterative testing of bedside-facing apps prior to testing with patients. Next steps include testing effectiveness in a pragmatic trial with clinician users (physicians, nurses, CNAs), integrating the UB-CAM app into the routine hospital care of all older patients. Having rapid, accurate bedside delirium detection has the potential to transform care.

Characterisation and outcome of neuropsychiatric symptoms in patients with anti-NMDAR encephalitis

2020 ◽  
Vol 32 (2) ◽  
pp. 92-98
Author(s):  
Miguel Restrepo-Martinez ◽  
Jesus Ramirez-Bermudez ◽  
Leo Bayliss ◽  
Mariana Espinola-Nadurille
Keyword(s):  
Rating Scale ◽  
Neuropsychiatric Symptoms ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Prospective Longitudinal Study ◽  
Aspartate Receptor ◽  
Immune Mediated ◽  
The Mean ◽  
Prospective Longitudinal ◽  
Receptor Antibodies

AbstractBackground:Encephalitis due to anti-N-methyl-D-aspartate receptor antibodies (ANMDARE) is the most frequent immune-mediated encephalitis. It is distinguished by the subacute onset of neuropsychiatric symptoms.Objective:To evaluate the characteristic neuropsychiatric symptoms and their outcome in patients diagnosed with ANMDARE.Methods:This was a prospective, longitudinal study in patients with a diagnostic suspicion of ANMDARE that presented to the National Institute of Neurology from March 2018 to February 2019. A comparative analysis of two groups (positive N-methyl-D-aspartate receptor [NMDAR] vs. negative NMDAR antibodies in cerebrospinal fluid [CSF]) was done on admission and at discharge. Neuropsychiatric systematic assessments included the Neuropsychiatric Inventory Questionnaire, the Bush Francis Catatonia Rating Scale, the Confusion Assessment Method Severity, the Montreal Cognitive Assessment, and the Overt Agitation Severity Scale.Results:24 individuals were analysed: 14 had positive NMDAR antibodies, and 10 had negative NMDAR antibodies in CSF. On admission, agitation/aggression, euphoria/exaltation, and disinhibition were more common in patients with positive antibodies. Excited catatonia and delirium were diagnosed more frequently in patients with positive antibodies. At discharge, there was an important decrease in neuropsychiatric symptoms, but substantial cognitive impairment remained. The mean hospitalisation length was 41.71 (SD 39.33) days for patients with definitive ANMDARE (p 0.259).Conclusions:Neuropsychiatric symptoms profile in ANMDARE was associated with the early onset of euphoria/exaltation and disinhibition, accompanied by marked psychomotor agitation. When ANMDARE was suspected, the presence of excited-type catatonia and delirium showed a tendency to predict definitive ANMDARE. At discharged, most patients recovered from catatonia, delirium, and psychosis, but marked cognitive symptoms, anxiety, and depression persisted at discharge.

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