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 ◽  
...  

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.

2021 ◽  
pp. 1-8
Author(s):  
Takehiko Yamanashi ◽  
Kaitlyn J. Crutchley ◽  
Nadia E. Wahba ◽  
Eleanor J. Sullivan ◽  
Katie R. Comp ◽  
...  

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.


2015 ◽  
Vol 27 (6) ◽  
pp. 881-882 ◽  
Author(s):  
Karin J. Neufeld

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.


10.2196/13440 ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. e13440 ◽  
Author(s):  
Nicholas Bott ◽  
Sharon Wexler ◽  
Lin Drury ◽  
Chava Pollak ◽  
Victor Wang ◽  
...  

Background Hospitalized older adults often experience isolation and disorientation while receiving care, placing them at risk for many inpatient complications, including loneliness, depression, delirium, and falls. Embodied conversational agents (ECAs) are technological entities that can interact with people through spoken conversation. Some ECAs are also relational agents, which build and maintain socioemotional relationships with people across multiple interactions. This study utilized a novel form of relational ECA, provided by Care Coach (care.coach, inc): an animated animal avatar on a tablet device, monitored and controlled by live health advocates. The ECA implemented algorithm-based clinical protocols for hospitalized older adults, such as reorienting patients to mitigate delirium risk, eliciting toileting needs to prevent falls, and engaging patients in social interaction to facilitate social engagement. Previous pilot studies of the Care Coach avatar have demonstrated the ECA’s usability and efficacy in home-dwelling older adults. Further study among hospitalized older adults in a larger experimental trial is needed to demonstrate its effectiveness. Objective The aim of the study was to examine the effect of a human-in-the-loop, protocol-driven relational ECA on loneliness, depression, delirium, and falls among diverse hospitalized older adults. Methods This was a clinical trial of 95 adults over the age of 65 years, hospitalized at an inner-city community hospital. Intervention participants received an avatar for the duration of their hospital stay; participants on a control unit received a daily 15-min visit from a nursing student. Measures of loneliness (3-item University of California, Los Angeles Loneliness Scale), depression (15-item Geriatric Depression Scale), and delirium (confusion assessment method) were administered upon study enrollment and before discharge. Results Participants who received the avatar during hospitalization had lower frequency of delirium at discharge (P<.001), reported fewer symptoms of loneliness (P=.01), and experienced fewer falls than control participants. There were no significant differences in self-reported depressive symptoms. Conclusions The study findings validate the use of human-in-the-loop, relational ECAs among diverse hospitalized older adults.


2021 ◽  
Vol 12 ◽  
Author(s):  
Jennifer Connell ◽  
Ahra Kim ◽  
Nathan E. Brummel ◽  
Mayur B. Patel ◽  
Simon N. Vandekar ◽  
...  

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 &lt; 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.


2012 ◽  
Vol 24 (7) ◽  
pp. 1065-1075 ◽  
Author(s):  
James T. Becker ◽  
Ranjan Duara ◽  
Ching-Wen Lee ◽  
Leonid Teverovsky ◽  
Beth E. Snitz ◽  
...  

ABSTRACTBackground: Population-based studies face challenges in measuring brain structure relative to cognitive aging. We examined the feasibility of acquiring state-of-the-art brain MRI images at a community hospital, and attempted to cross-validate two independent approaches to image analysis.Methods: Participants were 49 older adults (29 cognitively normal and 20 with mild cognitive impairment (MCI)) drawn from an ongoing cohort study, with annual clinical assessments within one month of scan, without overt cerebrovascular disease, and without dementia (Clinical Dementia Rating (CDR) < 1). Brain MRI images, acquired at the local hospital using the Alzheimer's Disease Neuroimaging Initiative protocol, were analyzed using (1) a visual atrophy rating scale and (2) a semi-automated voxel-level morphometric method. Atrophy and volume measures were examined in relation to cognitive classification (any MCI and amnestic MCI vs. normal cognition), CDR (0.5 vs. 0), and presumed etiology.Results: Measures indicating greater atrophy or lesser volume of the hippocampal formation, the medial temporal lobe, and the dilation of the ventricular space were significantly associated with cognitive classification, CDR = 0.5, and presumed neurodegenerative etiology, independent of the image analytic method. Statistically significant correlations were also found between the visual ratings of medial temporal lobe atrophy and the semi-automated ratings of brain structural integrity.Conclusions: High quality MRI data can be acquired and analyzed from older adults in population studies, enhancing their capacity to examine imaging biomarkers in relation to cognitive aging and dementia.


2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 155-155
Author(s):  
Elizabeth Rhodus ◽  
Justin Barber ◽  
Erin Abner ◽  
Shani Bardach ◽  
Graham Rowles ◽  
...  

Abstract Autism spectrum disorder (ASD) is commonly recognized by the time of adolescence, but is poorly understood in older adults. The possibility of late-life emergence of ASD has been poorly explored. In order to investigate late-life emergence of behaviors characteristic of ASD in MCI and AD, we surveyed caregivers of 142 older adults with neurodegenerative cognitive impairment using the Gilliam Autism Rating Scale-2. Participants with high autism index ratings (Autism ‘Possible/Very Likely’, n=23) reported significantly (statistically and clinically) younger age at onset of cognitive impairment than those who scored in the Autism ‘Unlikely’ range (n=119): 71.14±10.9 vs. 76.65±8.25 (p = 0.034). Additionally, those in Autism ‘Possible/Very Likely’ group demonstrated advanced severity of cognitive impairment, indicated by Clinical Dementia Rating Scale Sum of Boxes scores. Data demonstrate that ASD behaviors may appear de novo of degenerative dementia and such behaviors are more prevalent in those with early onset dementia. Further work elucidating a connection between ASD and dementia could shed light on subclinical forms of ASD, identify areas of shared neuroanatomic involvement between ASD and dementias, and provide valuable insights that might hasten the development of therapeutic strategies.


2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 520-520
Author(s):  
Benjamin Helfand ◽  
Elke Detroyer ◽  
Koen Milisen ◽  
Dimitrios Adamis ◽  
Richard Jones

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.


2018 ◽  
Author(s):  
Lindroth H. ◽  
Bratzke L. ◽  
Twadell S. ◽  
Rowley P. ◽  
Kildow J. ◽  
...  

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.


2020 ◽  
Vol 15 (9) ◽  
pp. 544-547
Author(s):  
Andrea Yevchak Sillner ◽  
Long Ngo ◽  
Yoojin Jung ◽  
Sharon Inouye ◽  
Marie Boltz ◽  
...  

The authors’ sought to develop an ultrabrief screen for postoperative delirium in cognitively intact patients older than 70 years undergoing major elective surgery. All possible combinations of one-, two- and three-item screens and their sensitivities, specificities, and 95% confidence intervals were calculated and compared with the delirium reference standard Confusion Assessment Method (CAM). Among the 560 participants (mean age, 77 years; 58% women), delirium occurred in 134 (24%). We considered 1,100 delirium assessments from postoperative days 1 and 2. The screen with the best overall performance consisted of three items: (1) Patient reports feeling confused, (2) Months of the year backward, and (3) “Does the patient appear sleepy?” with sensitivity of 92% and specificity of 72%. This brief, three-item screen rules out delirium quickly, identifies a subset of patients who require further testing, and may be an important tool to improve recognition of postoperative delirium.


Sign in / Sign up

Export Citation Format

Share Document