Confusion: delirium and dementia - a smartphone app to improve cognitive assessment.
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ABSTRACT:
SUBMITTER: Sangha S
PROVIDER: S-EPMC4645948 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
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Confusion: delirium and dementia - a smartphone app to improve cognitive assessment.
Sangha Selina S George J J Winthrop Craig C Panchal Sonia S
BMJ quality improvement reports 20150121 1
Older patients with dementia and delirium are more prone to adverse events in hospital, but formal cognitive assessment to identify these vulnerable patients on admission is often not carried out by junior doctors. A smartphone app was created and provided on hospital wards to facilitate the use of standard cognitive assessments for delirium and dementia. Before the introduction of the app, 36% of patients over 75 years old were assessed cognitively. After the app, the percentage of cognitive as ...[more]
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Project description:BackgroundRecently, the Ultra-Brief Confusion Assessment Method (UB-CAM), designed to help physicians and nurses to recognize delirium, showed high, but imperfect, accuracy compared with Research Reference Standard Delirium Assessments (RRSDAs). The aim of this study is to identify factors associated with disagreement between clinicians' app-based UB-CAM assessments and RRSDAs.MethodsThis is a secondary analysis of a prospective diagnostic test study. The study was conducted at two hospitals and included 527 inpatients (≥70 years old) and 289 clinicians (53 physicians, 236 nurses). Trained research associates performed RRSDAs and determined delirium presence using the CAM. Clinicians administered the UB-CAM using an iPad app. Disagreement factors considered were clinician, patient, and delirium characteristics. We report odds ratios and 95% confidence intervals.ResultsOne thousand seven hundred and ninety-five clinician UB-CAM assessments paired with RRSDAs were administered. The prevalence of delirium was 17%. The rate of disagreement between clinician UB-CAM assessments and RRSDAs was 12%. Significant factors associated with disagreement between clinician UB-CAM assessments and RRSDAs (OR [95% CI]) included: presence of dementia (2.7 [1.8-4.1]), patient education high school or less (1.9 [1.3-2.9]), psychomotor retardation (2.5 [1.4-4.2]), and the presence of mild delirium or subsyndromal delirium (5.5 [3.5-8.7]). Significant risk factors for false negatives were patient age less than 80 (2.2 [1.1-4.3]) and mild delirium (3.5 [1.6-7.4]). Significant risk factors for false positives were presence of dementia (4.0 [2.3-7.0]), subsyndromal delirium (5.1 [2.9-9.1]), and patient education high school or less (2.0 [1.2-3.6]). Clinician characteristics were not significantly associated with disagreement.ConclusionsThe strongest factors associated with disagreement between clinician UB-CAM screens and RRSDAs were the presence of dementia and subsyndromal delirium as risk factors for false positives, and mild delirium and younger age as a risk factor for false negatives. These disagreement factors contrast with previous studies of risk factors for incorrect clinician delirium screening, and better align screening results with patient outcomes.
| S-EPMC10947955 | biostudies-literature
Project description:BackgroundBy enabling frequent, sensitive, and economic remote assessment, smartphones will facilitate the detection of early cognitive decline at scale. Previous studies have sustained participant engagement with remote cognitive assessment over a week; extending this to a period of 1 month clearly provides a greater opportunity for measurement. However, as study durations are increased, the need to understand how participant burden and scientific value might be optimally balanced also increases.ObjectiveThis study explored the little but often approach to assessment employed by the Mezurio app when prompting participants to interact every day for over a month. Specifically, this study aimed to understand whether this extended duration of remote study is feasible, and which factors promote sustained participant engagement over such periods.MethodsA total of 35 adults (aged 40-59 years) with no diagnosis of cognitive impairment were prompted to interact with the Mezurio smartphone app platform for up to 36 days, completing short, daily episodic memory tasks in addition to optional executive function and language tests. A subset (n=20) of participants completed semistructured interviews focused on their experience of using the app.ResultsParticipants complied with 80% of the daily learning tasks scheduled for subsequent tests of episodic memory, with 88% of participants still actively engaged by the final task. A thematic analysis of the participants' experiences highlighted schedule flexibility, a clear user interface, and performance feedback as important considerations for engagement with remote digital assessment.ConclusionsDespite the extended study duration, participants demonstrated high compliance with the schedule of daily learning tasks and were extremely positive about their experiences. Long durations of remote digital interaction are therefore definitely feasible but only when careful attention is paid to the design of the users' experience.
| S-EPMC7163418 | biostudies-literature
Project description:ObjectivesDelirium is a common and frequently underdiagnosed complication in acutely hospitalized patients, and its severity is associated with worse clinical outcomes. We propose a physiologically based method to quantify delirium severity as a tool that can help close this diagnostic gap: the Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S).DesignRetrospective cohort study.SettingSingle-center tertiary academic medical center.PatientsThree-hundred seventy-three adult patients undergoing electroencephalography to evaluate altered mental status between August 2015 and December 2019.InterventionsNone.Measurements and main resultsWe developed the E-CAM-S based on a learning-to-rank machine learning model of forehead electroencephalography signals. Clinical delirium severity was assessed using the Confusion Assessment Method Severity (CAM-S). We compared associations of E-CAM-S and CAM-S with hospital length of stay and inhospital mortality. E-CAM-S correlated with clinical CAM-S (R = 0.67; p < 0.0001). For the overall cohort, E-CAM-S and CAM-S were similar in their strength of association with hospital length of stay (correlation = 0.31 vs 0.41, respectively; p = 0.082) and inhospital mortality (area under the curve = 0.77 vs 0.81; p = 0.310). Even when restricted to noncomatose patients, E-CAM-S remained statistically similar to CAM-S in its association with length of stay (correlation = 0.37 vs 0.42, respectively; p = 0.188) and inhospital mortality (area under the curve = 0.83 vs 0.74; p = 0.112). In addition to previously appreciated spectral features, the machine learning framework identified variability in multiple measures over time as important features in electroencephalography-based prediction of delirium severity.ConclusionsThe E-CAM-S is an automated, physiologic measure of delirium severity that predicts clinical outcomes with a level of performance comparable to conventional interview-based clinical assessment.
| S-EPMC8678335 | biostudies-literature
Project description:ObjectivesTo compare performance characteristics of the Confusion Assessment Method (CAM) algorithm for screening and delirium diagnosis with criteria for delirium from the International Classification of Diseases, Tenth Revision (ICD-10) and Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) in high-risk individuals.DesignProspective cohort study.SettingAcademic geriatric hospital.ParticipantsOne hundred two individuals aged 80 to 100 hospitalized for acute medical illness.MeasurementsComplete CAM instrument (nine items), scored using the four-item CAM diagnostic algorithm. Criterion standard classification of delirium was rated independently according to expert consensus based on DSM-IV and ICD-10 criteria for delirium.ResultsIn 79 hospitalized participants, the CAM performed well for delirium screening (delirium prevalence of 24% according to DSM-IV and 14% according to ICD-10). Of all CAM features, acute onset and fluctuating course are most important for diagnosis (area under the receiver operating characteristic curve (AUC) = 0.92 in DSM-IV and 0.83 in ICD-10). The CAM diagnostic algorithm had a sensitivity of 0.74, a specificity of 1.0, and an AUC of 0.88 compared with the DSM-IV reference standard and a sensitivity of 0.82, a specificity of 0.91, and an AUC of 0.85 compared with the ICD-10. Compared with the ICD-10, adding psychomotor change to the CAM algorithm improved specificity to 97%, but sensitivity fell to 55% (AUC = 0.96). Applying psychomotor change sequentially only to the group that the CAM algorithm identified as having no delirium improved sensitivity to 91% with specificity of 85% (AUC = 0.95).ConclusionAlthough the CAM diagnostic algorithm performed well against a DSM-IV reference standard, adding psychomotor change to the CAM algorithm improved specificity and diagnostic value against ICD-10 criteria overall in older adults with dementia and improved sensitivity and screening performance when applied sequentially in CAM-negative individuals.
| S-EPMC3422775 | biostudies-literature
Project description:ObjectiveTo examine the ability of the family-rated Family Confusion Assessment Method (FAM-CAM) to identify delirium in the emergency department (ED) among patients with and without dementia, as compared to the reference-standard Confusion Assessment Method (CAM).DesignValidation study.SettingUrban academic ED.ParticipantsDyads of ED patients, aged 70 years and older, and their family caregivers (N = 108 dyads).MeasurementsA trained reference standard interviewer performed a cognitive screen, delirium symptom assessment, and scored the CAM. The caregiver self-administered the FAM-CAM. Dementia was assessed using the Informant Questionnaire on Cognitive Decline in the Elderly and the medical record. For concurrent validity, performance of the FAM-CAM was compared to the CAM. For predictive validity, clinical outcomes (ED visits, hospitalization, and mortality) over 6 months were compared in FAM-CAM positive and negative patients, controlling for age, sex, comorbidity, and cognitive status.ResultsAmong the 108 patients, 30 (28%) were CAM positive for delirium and 58 (54%) presented with dementia. The FAM-CAM had a specificity of 83% and a negative predictive value of 83%. Most false negatives (n = 9 of 13, 69%) were due to caregivers not identifying the inattention criteria for delirium on the FAM-CAM. In patients with dementia, sensitivity was higher than in patients without (61% vs 43%). In adjusted models, a hospitalization in the following 6 months was more than three times as likely in FAM-CAM positive compared to negative patients (odds ratio = 3.4; 95% confidence interval = 1.2-9.3).ConclusionsAmong patients with and without dementia, the FAM-CAM shows qualities that are important in the ED setting for identification of delirium. Using the FAM-CAM as part of a systematic screening strategy for the ED, in which families' assessments could supplement healthcare professionals' assessments, is promising. J Am Geriatr Soc 68:983-990, 2020.
| S-EPMC7370702 | biostudies-literature
Project description:BackgroundSmartphone-assisted technologies potentially provide the opportunity for large-scale, long-term, repeated monitoring of cognitive functioning at home.ObjectiveThe aim of this proof-of-principle study was to evaluate the feasibility and validity of performing cognitive tests in people at increased risk of dementia using smartphone-based technology during a 6 months follow-up period.MethodsWe used the smartphone-based app iVitality to evaluate five cognitive tests based on conventional neuropsychological tests (Memory-Word, Trail Making, Stroop, Reaction Time, and Letter-N-Back) in healthy adults. Feasibility was tested by studying adherence of all participants to perform smartphone-based cognitive tests. Validity was studied by assessing the correlation between conventional neuropsychological tests and smartphone-based cognitive tests and by studying the effect of repeated testing.ResultsWe included 151 participants (mean age in years=57.3, standard deviation=5.3). Mean adherence to assigned smartphone tests during 6 months was 60% (SD 24.7). There was moderate correlation between the firstly made smartphone-based test and the conventional test for the Stroop test and the Trail Making test with Spearman ρ=.3-.5 (P<.001). Correlation increased for both tests when comparing the conventional test with the mean score of all attempts a participant had made, with the highest correlation for Stroop panel 3 (ρ=.62, P<.001). Performance on the Stroop and the Trail Making tests improved over time suggesting a learning effect, but the scores on the Letter-N-back, the Memory-Word, and the Reaction Time tests remained stable.ConclusionsRepeated smartphone-assisted cognitive testing is feasible with reasonable adherence and moderate relative validity for the Stroop and the Trail Making tests compared with conventional neuropsychological tests. Smartphone-based cognitive testing seems promising for large-scale data-collection in population studies.
| S-EPMC5465383 | biostudies-literature
Project description:OBJECTIVES:Delirium severity is independently associated with longer hospital stays, nursing home placement, and death in patients outside the ICU. Delirium severity in the ICU is not routinely measured because the available instruments are difficult to complete in critically ill patients. We designed our study to assess the reliability and validity of a new ICU delirium severity tool, the Confusion Assessment Method for the ICU-7 delirium severity scale. DESIGN:Observational cohort study. SETTING:Medical, surgical, and progressive ICUs of three academic hospitals. PATIENTS:Five hundred eighteen adult (? 18 yr) patients. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Patients received the Confusion Assessment Method for the ICU, Richmond Agitation-Sedation Scale, and Delirium Rating Scale-Revised-98 assessments. A 7-point scale (0-7) was derived from responses to the Confusion Assessment Method for the ICU and Richmond Agitation-Sedation Scale items. Confusion Assessment Method for the ICU-7 showed high internal consistency (Cronbach's ? = 0.85) and good correlation with Delirium Rating Scale-Revised-98 scores (correlation coefficient = 0.64). Known-groups validity was supported by the separation of mechanically ventilated and nonventilated assessments. Median Confusion Assessment Method for the ICU-7 scores demonstrated good predictive validity with higher odds (odds ratio = 1.47; 95% CI = 1.30-1.66) of in-hospital mortality and lower odds (odds ratio = 0.8; 95% CI = 0.72-0.9) of being discharged home after adjusting for age, race, gender, severity of illness, and chronic comorbidities. Higher Confusion Assessment Method for the ICU-7 scores were also associated with increased length of ICU stay (p = 0.001). CONCLUSIONS:Our results suggest that Confusion Assessment Method for the ICU-7 is a valid and reliable delirium severity measure among ICU patients. Further research comparing it to other delirium severity measures, its use in delirium efficacy trials, and real-life implementation is needed to determine its role in research and clinical practice.
| S-EPMC5392153 | biostudies-literature
Project description:BackgroundDelirium is common, distressing and associated with poor outcomes. Previous studies investigating the impact of delirium on cognitive outcomes have been limited by incomplete ascertainment of baseline cognition or lack of prospective delirium assessments. This study quantified the association between delirium and cognitive function over time by prospectively ascertaining delirium in a cohort aged ≥ 65 years in whom baseline cognition had previously been established.MethodsFor 12 months, we assessed participants from the Cognitive Function and Ageing Study II-Newcastle for delirium daily during hospital admissions. At 1-year, we assessed cognitive decline and dementia in those with and without delirium. We evaluated the effect of delirium (including its duration and number of episodes) on cognitive function over time, independently of baseline cognition and illness severity.ResultsEighty two of 205 participants recruited developed delirium in hospital (40%). One-year outcome data were available for 173 participants: 18 had a new dementia diagnosis, 38 had died. Delirium was associated with cognitive decline (-1.8 Mini-Mental State Examination points [95% CI -3.5 to -0.2]) and an increased risk of new dementia diagnosis at follow up (OR 8.8 [95% CI 1.9-41.4]). More than one episode and more days with delirium (>5 days) were associated with worse cognitive outcomes.ConclusionsDelirium increases risk of future cognitive decline and dementia, independent of illness severity and baseline cognition, with more episodes associated with worse cognitive outcomes. Given that delirium has been shown to be preventable in some cases, we propose that delirium is a potentially modifiable risk factor for dementia.
| S-EPMC8099011 | biostudies-literature
Project description:BackgroundHeart rate (HR) assessment is crucial in neonatal resuscitation, but pulse oximetry (PO) and electrocardiography (ECG) are rarely accessible in low-resource to middle-resource settings. This study evaluated a free-of-charge smartphone application, NeoTap, which records HR with a screen-tapping method bypassing mental arithmetic calculations.MethodsThis observational study was carried out during three time periods between May 2015 and January 2019 in Uganda in three phases. In phase 1, a metronome rate (n=180) was recorded by low-end users (midwives) using NeoTap. In phase 2, HR (n=69) in breathing neonates was recorded by high-end users (paediatricians) using NeoTap versus PO. In phase 3, HR (n=235) in non-breathing neonates was recorded by low-end users using NeoTap versus ECG.ResultsIn high-end users the mean difference was 3 beats per minute (bpm) higher with NeoTap versus PO (95% agreement limits -14 to 19 bpm), with acquisition time of 5 seconds. In low-end users, the mean difference was 6 bpm lower with NeoTap versus metronome (95% agreement limits -26 to 14 bpm) and 3 bpm higher with NeoTap versus ECG in non-breathing neonates (95% agreement limits -48 to 53 bpm), with acquisition time of 2.7 seconds. The agreement between NeoTap and ECG was good in the HR categories of 60-99 bpm and ≥100 bpm; HR <60 bpm had few measurements (kappa index 0.71, 95% CI 0.63 to 0.79).ConclusionHR could be accurately and rapidly assessed using a smartphone application in breathing neonates in a low-resource setting. Clinical assessment by low-end users was less accurate with wider CI but still adds clinically important information in non-breathing neonates. The authors suggest low-end users may benefit from auscultation-focused training. More research is needed to evaluate its feasibility in clinical use.
| S-EPMC7381998 | biostudies-literature
Project description:BackgroundMild cognitive impairment (MCI) is a major risk factor for delirium. Few studies with mid- to long-term follow-up periods have examined delirium, MCI, and the conversion of MCI to dementia. This prospective, longitudinal cohort study aims to assess the incidence of dementia after delirium onset in patients with MCI and to develop an artificial intelligence algorithm for predicting the conversion of MCI to dementia.MethodsA 30-day evaluation for delirium will be performed for adults aged ≥ 65 years diagnosed with MCI who score 18-23 on the Korean Mini-Mental State Exam. Individuals exhibiting delirium at least once will be classified into the delirium group and the remainder into the non-delirium group. Over 3 years, patients will undergo follow-ups for survival and conversion to dementia at 30-day intervals to analyze risk factors for delirium and clinical outcomes. Differences between the two groups will be analyzed using the chi-square and independent t-tests. Kaplan-Meier survival and Cox proportional hazard regression will be used to assess the effects on 30-day, 60-day, 12-month, 24-month, and 36-month mortality, whereas linear regression will be used to assess the length of stay at long-term care facilities and medical costs.DiscussionThe results will emphasize the importance of preventing delirium in MCI patients, and preventive interventions can be strengthened.Trial registrationNCT05113446 (ClinicalTrials.gov). Registered 9 November 2021 - Retrospectively registered.
| S-EPMC11542405 | biostudies-literature