Digital Cognitive Assessments for Dementia: Digital assessments may enhance the efficiency of evaluations in neurology and other clinics.
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ABSTRACT:
SUBMITTER: Staffaroni AM
PROVIDER: S-EPMC8078574 | biostudies-literature | 2020 Nov-Dec
REPOSITORIES: biostudies-literature
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Digital Cognitive Assessments for Dementia: Digital assessments may enhance the efficiency of evaluations in neurology and other clinics.
Staffaroni Adam M AM Tsoy Elena E Taylor Jack J Boxer Adam L AL Possin Katherine L KL
Practical neurology (Fort Washington, Pa.) 20201101
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Project description:BackgroundTimely diagnosis of dementia is a global healthcare priority, particularly in low to middle income countries where rapid increases in older adult populations are expected.ObjectiveTo investigate global perspectives on the role of brief cognitive assessments (BCAs) in dementia diagnosis, strengths and limitations of existing measures, and future directions and needs.MethodsThis is a qualitative study of 18 dementia experts from different areas of the world. Participants were selected using purposeful sampling based on the following criteria: 1) practicing in countries with projected growth of older adult population of over 100%by 2050; 2) expertise in dementia diagnosis and treatment; 3) involvement in clinical practice and training; and 4) recognition as a national dementia expert based on leadership positions within healthcare system, research, and/or policy work. Participants were individually interviewed in their language of choice over secure videoconference sessions. Interviews were analyzed by a multidisciplinary team using theme identification approach.ResultsFour domains with subthemes emerged illustrating participants' perspectives: 1) strengths of BCAs; 2) limitations of BCAs; 3) needs related to the use of BCAs; and 4) characteristics of an ideal BCA. While most experts agreed that BCAs were important and useful for dementia diagnosis, the themes emphasized the need for development and validation of novel measures that are sensitive, psychometrically sound, and culturally appropriate.ConclusionBCAs are important for guiding diagnosis and care for dementia patients. Findings provide a roadmap for novel BCA development to assist in diagnostic decision making for clinicians serving a rapidly growing and diverse dementia population.
| S-EPMC9450569 | biostudies-literature
Project description:Detecting early signs of cognitive decline is crucial for early detection and treatment of Alzheimer's Disease. Most of the current screening tools for Alzheimer's Disease represent a significant burden, requiring invasive procedures, or intensive and costly clinical testing. Recent findings have highlighted changes to speech and language patterns that occur in Alzheimer's Disease, and may be detectable prior to diagnosis. Automated tools to assess speech have been developed that can be used on a smartphone or tablet, from one's home, in under 10 min. In this study, we present the results of a study of older adults who completed a digital speech assessment task over a 6-month period. Participants were grouped according to those who scored above (N = 18) or below (N = 18) the recommended threshold for detecting cognitive impairment on the Montreal Cognitive Assessment (MoCA) and those with diagnoses of mild cognitive impairment (MCI) or early Alzheimer's Disease (AD) (N = 14). Older adults who scored above the MoCA threshold had better performance on speech composites reflecting language coherence, information richness, syntactic complexity, and word finding abilities. Those with MCI and AD showed more rapid decline in the coherence of language from baseline to 6-month follow-up, suggesting that this score may be useful both for detecting cognitive decline and monitoring change over time. This study demonstrates that automated speech assessments have potential as sensitive tools to detect early signs of cognitive impairment and monitor progression over time.
| S-EPMC8579012 | biostudies-literature
Project description:The dementia population is increasing as the world's population is growing older. The current systematic review aims to identify digital cognitive biomarkers from computerized tests for detecting dementia and its risk state of mild cognitive impairment (MCI), and to evaluate the diagnostic performance of digital cognitive biomarkers. A literature search was performed in three databases, and supplemented by a Google search for names of previously identified computerized tests. Computerized tests were categorized into five types, including memory tests, test batteries, other single/multiple cognitive tests, handwriting/drawing tests, and daily living tasks and serious games. Results showed that 78 studies were eligible. Around 90% of the included studies were rated as high quality based on the Newcastle-Ottawa Scale (NOS). Most of the digital cognitive biomarkers achieved comparable or even better diagnostic performance than traditional paper-and-pencil tests. Moderate to large group differences were consistently observed in cognitive outcomes related to memory and executive functions, as well as some novel outcomes measured by handwriting/drawing tests, daily living tasks, and serious games. These outcomes have the potential to be sensitive digital cognitive biomarkers for MCI and dementia. Therefore, digital cognitive biomarkers can be a sensitive and promising clinical tool for detecting MCI and dementia.
| S-EPMC9320101 | biostudies-literature
Project description:IntroductionWe aimed to develop an algorithm to predict the individualized risk of future dementia using brief cognitive tests suitable for primary care.MethodsWe included 612 participants with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, assessed for at least 4 years or until progression to dementia. A logistic regression model, using cognitive tests as predictors and dementia progression as an outcome, stratified participants into low, intermediate, or high risk. A second model, including 1-year cognitive test changes, was applied to the intermediate group. The models were replicated in 392 SCD/MCI participants from the BioFINDER-1 study.ResultsThe best two-step model for predicting dementia incorporated Trail Making Test B (attention/executive function), Animal Fluency (verbal fluency), Mini-Mental State Examination (global cognition), and 10-word list recall (memory). The model's positive predictive value in ADNI was 85.8% and negative predictive value was 92.2% versus 62.5% and 95.6%, respectively, in BioFINDER-1.DiscussionThis two-step model accurately predicts individualized dementia risk.HighlightsTo our knowledge, this is the first algorithm for predicting all-cause dementia using a novel two-step model utilizing brief cognitive tests. Applying a validated model including the Trail Making Test B, Animal Fluency, MMSE, Alzheimer's Disease Assessment Scale delayed, and immediate recall can robustly and accurately categorize individuals into low, intermediate, or high risk of dementia progression and can facilitate clinical decision-making and personalized patient care. We created an app that is available for research and educational purposes at https://brainapps.shinyapps.io/PredictAllCauseDementia to provide an individualized risk score for dementia progression.
| S-EPMC11667515 | biostudies-literature
Project description:ImportanceWith increasing dementia prevalence due to population aging, interpreters are needed to facilitate timely dementia diagnosis by supporting the complex verbal and nonverbal interplay between clinicians and patients during cognitive assessments. However, to our knowledge, no randomized clinical trials have previously evaluated interventions to improve interpreter communication during cognitive assessments for dementia.ObjectiveTo assess whether online training codesigned by interpreters, clinicians, and multilingual family carers improves the quality of interpreter communication during cognitive assessments for dementia.Design, setting, and participantsThe Improving Interpreting for Dementia Assessments (MINDSET) study was a single-blind, parallel-group randomized clinical trial including certified interpreters and certified provisional interpreters of Arabic, Cantonese, Greek, Italian, Mandarin, or Vietnamese with at least 6 months' experience. The trial was community based and conducted online across Australia between June 26, 2022, and April 2, 2023, with follow-up at 3 and 6 months after baseline.InterventionParticipants were randomized 1:1 to receive interpreter training during the study or, if assigned to the waiting list control, after their 6-month assessment.Main outcomes and measuresThe primary outcome was change in the quality of interpreted communication, as measured by a weighted score comprising 5 domains: (1) knowledge of dementia, (2) cross-cultural communication, (3) briefings and debriefings, (4) interpreting skills for cognitive assessments, and (5) ethical principles relevant during a cognitive assessment. Mixed-effects generalized linear regression was conducted with random effects accounting for repeated measures from participating interpreters. Secondary analyses were conducted for differences in individual interpreting domains. A secondary per-protocol analysis included only participants who completed at least 70% of the training in the intervention group.ResultsAt baseline, there were 126 participants (106 [84.1%] women); mean (SD) age was 44.13 (12.71) years, mean years of interpreting experience was 8.57 (8.48) years, and 106 of 120 (88.3%) lived in an urban area. A total of 22 (17.5%) were Arabic interpreters; 14 (11.1%), Cantonese; 6 (4.8%), Greek; 14 (11.1%), Italian; 64 (50.8%), Mandarin; and 6 (4.8%), Vietnamese. The primary outcome of communication quality in the main analysis did not significantly improve in the intervention group compared with controls (mean score difference, 2.10; 95% CI, -0.43 to 4.62; P = .10). Per-protocol findings showed a significant intervention effect (mean score difference, 2.73; 95% CI, 0.14-5.31; P = .04), suggesting that the MINDSET-trained interpreters benefited in the primary outcome when they completed at least 70% of the training. Of the 5 domains, a significant intervention effect was shown in only domain 1 (knowledge of dementia) in the main analysis (mean score difference, 1.15; 95% CI, 0.54-1.77; P < .001) and per-protocol analysis (1.03; 95% CI, 0.27-1.79; P = .008) at 3 months.Conclusions and relevanceIn this randomized clinical trial, results of the primary, intention-to-treat analysis showed that interpreters' overall interpreting communication quality did not improve in the intervention group compared with controls, but in the secondary, per-protocol analysis, it was improved when at least 70% of the training was completed. These findings suggest that an online training intervention can improve interpreters' communication quality during cognitive assessments for dementia if at least 70% of training is completed.Trial registrationANZCTR Identifier: ACTRN12621001281886.
| S-EPMC11822547 | biostudies-literature
Project description:IntroductionRemote unsupervised cognitive assessments have the potential to complement and facilitate cognitive assessment in clinical and research settings.MethodsHere, we evaluate the usability, validity, and reliability of unsupervised remote memory assessments via mobile devices in individuals without dementia from the Swedish BioFINDER-2 study and explore their prognostic utility regarding future cognitive decline.ResultsUsability was rated positively; remote memory assessments showed good construct validity with traditional neuropsychological assessments and were significantly associated with tau-positron emission tomography and downstream magnetic resonance imaging measures. Memory performance at baseline was associated with future cognitive decline and prediction of future cognitive decline was further improved by combining remote digital memory assessments with plasma p-tau217. Finally, retest reliability was moderate for a single assessment and good for an aggregate of two sessions.DiscussionOur results demonstrate that unsupervised digital memory assessments might be used for diagnosis and prognosis in Alzheimer's disease, potentially in combination with plasma biomarkers.HighlightsRemote and unsupervised digital memory assessments are feasible in older adults and individuals in early stages of Alzheimer's disease. Digital memory assessments are associated with neuropsychological in-clinic assessments, tau-positron emission tomography and magnetic resonance imaging measures. Combination of digital memory assessments with plasma p-tau217 holds promise for prognosis of future cognitive decline. Future validation in further independent, larger, and more diverse cohorts is needed to inform clinical implementation.
| S-EPMC11247711 | biostudies-literature
Project description:ImportanceTelemedicine is increasingly used to provide outpatient pediatric neurology consultations in underserved communities. Although telemedicine clinics have been shown to improve access, little is known about how they alter patients' utilization of hospital services.ObjectiveTo evaluate the association between access to telemedicine clinics and hospital utilization among underserved children with neurologic conditions.Design, setting, and participantsThis retrospective cross-sectional study included 4169 patients who received outpatient care from pediatric neurologists affiliated with an academic children's hospital in California between January 1, 2009, and July 31, 2017, either in person or using telemedicine.ExposuresConsultation modality (telemedicine or in person) in the outpatient neurology clinics.Main outcomes and measuresDemographic and clinical variables were abstracted from the hospital's electronic medical records. The association between the modality of outpatient neurology care and patients' utilization of the emergency department and hospitalizations was evaluated. Both all-cause and neurologic condition-related hospital utilization were analyzed using multivariable negative binomial regression in overall and matched samples.ResultsThe telemedicine cohort comprised 378 patients (211 [55.8%] male), and the in-person cohort comprised 3791 patients (2090 [55.1%] male). The mean (SD) age at the first encounter was 7.4 (5.4) years for the telemedicine cohort and 7.8 (5.1) years for the in-person cohort. The telemedicine cohort was more likely than the in-person cohort to have nonprivate insurance (public insurance, self-pay, or uninsured), lower education, and lower household income. The rates of all-cause and neurologic hospital encounters were lower among children who received pediatric neurology consultations over telemedicine compared with children who received care in the in-person clinics (5.7 [95% CI, 3.5-8.0] vs 20.1 [95% CI, 18.1-22.1] per 100 patient-years and 3.7 [95% CI, 2.0-5.3] vs 8.9 [95% CI, 7.8-10.0] per 100 patient-years, respectively; P < .001). Even after adjusting for demographic and clinical factors, the telemedicine cohort had a lower risk of hospital encounters (emergency department visits and admissions) with an adjusted incidence rate ratio of 0.57 (95% CI, 0.38-0.88) for all-cause encounters and an adjusted incidence rate ratio of 0.60 (95% CI, 0.36-0.99) for neurologic encounters. After matching on travel time to the neurology clinic, the adjusted incidence rate ratio was 0.19 (95% CI, 0.04-0.83) for all-cause admissions and 0.14 (95% CI, 0.02-0.82) for neurologic admissions.Conclusions and relevancePediatric neurology care through real-time, audiovisual telemedicine consultations was associated with lower hospital utilization compared with in-person consultations, suggesting that high-cost hospital encounters can be prevented by improving subspecialty access.
| S-EPMC6704740 | biostudies-literature
Project description: Not available
| S-EPMC3888169 | biostudies-literature
Project description:BackgroundDigital cognitive assessments, particularly those that can be done at home, present as low-burden biomarkers for participants and patients alike, but their effectiveness in the diagnosis of Alzheimer's disease (AD) or predicting its trajectory is still unclear. Here, we assessed what utility or added value these digital cognitive assessments provide for identifying those at high risk of cognitive decline.MethodsWe analyzed >500 Alzheimer's Disease Neuroimaging Initiative participants who underwent a brief digital cognitive assessment and amyloid beta (Aβ)/tau positron emission tomography scans, examining their ability to distinguish cognitive status and predict cognitive decline.ResultsPerformance on the digital cognitive assessment was superior to both cortical Aβ and entorhinal tau in detecting mild cognitive impairment and future cognitive decline, with mnemonic discrimination deficits emerging as the most critical measure for predicting decline and future tau accumulation.DiscussionDigital assessments are effective at identifying at-risk individuals, supporting their utility as low-burden tools for early AD detection and monitoring.HighlightsPerformance on digital cognitive assessments predicts progression to mild cognitive impairment at a higher proficiency compared to amyloid beta and tau. Deficits in mnemonic discrimination are indicative of future cognitive decline. Impaired mnemonic discrimination predicts future entorhinal and inferior temporal tau.
| S-EPMC11485398 | biostudies-literature
Project description:Healthcare-acquired infections (HCAI) represent a major health problem worldwide. Stroke and dementia are considered risk factors for HCAI. Preliminary data suggest that use of antipsychotic drugs also increase the risk for HCAI. Here, we performed a retrospective study aimed at investigating the major risk and protective factors for HCAI in a cohort of elderly subjects hospitalized at an Italian tertiary Neurology Clinics. We included all patients with age ≥ 65 years hospitalized at Neurology Clinics of National Institute on Ageing, Ancona, Italy from 1st January 2018 to 31st December 2021. For each patient, the following data were collected: age, sex, use of medical devices, comorbidities, use of antipsychotic medications, development of HCAI. We included 1543 patients (41.4% males; median age 85 years [80-89]). According to multivariable analysis, age, stroke, duration of urinary catheter placement (for all p < 0.001) and midline placement (p = 0.035) resulted to be risk factors for HCAI, Diabetes resulted to be a protective factor for pneumonia (p = 0.041), while dementia and nasogastric tube were risks factor for this condition (p = 0.022 and p < 0.001, respectively). Urinary catheter was a risk factor for urinary tract infections (p < 0.001). Duration of placement of vascular catheters and use of antipsychotic drugs resulted to significantly increase the risk for bloodstream infections. Stroke, age and use of medical devices were confirmed to be risk factors for HCAI. Antipsychotic drugs resulted to increase risk for bloodstream infections. Further prospective studies will be needed to confirm these findings.
| S-EPMC10618180 | biostudies-literature