Development and Validation of eRADAR: A Tool Using EHR Data to Detect Unrecognized Dementia.

ObjectivesEarly recognition of dementia would allow patients and their families to receive care earlier in the disease process, potentially improving care management and patient outcomes, yet nearly half of patients with dementia are undiagnosed. Our aim was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia (EHR Risk of Alzheimer's and Dementia Assessment Rule [eRADAR]).DesignRetrospective cohort study.SettingKaiser Permanente Washington (KPWA), an integrated healthcare delivery system.ParticipantsA total of 16 665 visits among 4330 participants in the Adult Changes in Thought (ACT) study, who undergo a comprehensive process to detect and diagnose dementia every 2 years and have linked KPWA EHR data, divided into development (70%) and validation (30%) samples.MeasurementsEHR predictors included demographics, medical diagnoses, vital signs, healthcare utilization, and medications within the previous 2 years. Unrecognized dementia was defined as detection in ACT before documentation in the KPWA EHR (ie, lack of dementia or memory loss diagnosis codes or dementia medication fills).ResultsOverall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 498 (49%) were unrecognized in the KPWA EHR. The final 31-predictor model included markers of dementia-related symptoms (eg, psychosis diagnoses, antidepressant fills), healthcare utilization pattern (eg, emergency department visits), and dementia risk factors (eg, cerebrovascular disease, diabetes). Discrimination was good in the development (C statistic = .78; 95% confidence interval [CI] = .76-.81) and validation (C statistic = .81; 95% CI = .78-.84) samples, and calibration was good based on plots of predicted vs observed risk. If patients with scores in the top 5% were flagged for additional evaluation, we estimate that 1 in 6 would have dementia.ConclusionThe eRADAR tool uses existing EHR data to detect patients with good accuracy who may have unrecognized dementia. J Am Geriatr Soc 68:103-111, 2019

Memory impairment at initial clinical presentation in posterior cortical atrophy

Posterior cortical atrophy (PCA) is characterized by core visuospatial and visuoperceptual deficits, and predominant atrophy in the parieto-occipital cortex. The most common underlying pathology is Alzheimer's disease (AD). Existing diagnostic criteria suggest that episodic memory is relatively preserved. The aim of this study was to examine memory performance at initial clinical presentation in PCA, compared to early-onset AD patients (EOAD). 15 PCA patients and 32 EOAD patients, and 34 healthy controls were entered into the study. Patients were tested on the Addenbrooke's Cognitive Examination (ACE-R), consisting of subscales in memory and visuospatial skills. PCA and EOAD patients were significantly impaired compared to controls on the ACE total score (p <  0.001), visuospatial skills (p <  0.001), and memory (p <  0.001). Consistent with the salient diagnostic deficits, PCA patients were significantly more impaired on visuospatial skills compared to EOAD patients (p <  0.001). However, there was no significant difference between patient groups in memory. Further analysis of learning, recall, and recognition components of the memory subscale showed that EOAD and PCA patients were significantly impaired compared to controls on all three components (p <  0.001), however, there was no significant difference between EOAD and PCA patients. The results of this study show that memory is impaired in the majority of PCA patients at clinical presentation. The findings suggest that memory impairment must be considered in assessment and management of PCA and second. Further study into memory in PCA is warranted, since the ACE-R is a brief screening tool and is likely to underestimate the presence of memory impairment

Cognitive performance in multiple system atrophy

The cognitive performance of a group of patients with multiple system atrophy (MSA) of striato-nigral predominance was compared with that of age and IQ matched control subjects, using three tests sensitive to frontal lobe dysfunction and a battery sensitive to memory and learning deficits in Parkinson's disease and dementia of the Alzheimer type. The MSA group showed significant deficits in all three of the tests previously shown to be sensitive to frontal lobe dysfunction. Thus, a significant proportion of patients from the MSA group failed an attentional set-shifting test, specifically at the stage when an extra-dimensional shift was required. They were also impaired in a subject-ordered test of spatial working memory. The MSA group showed deficits mostly confined to measures of speed of thinking, rather than accuracy, on the Tower of London task. These deficits were seen in the absence of consistent impairments in language or visual perception. Moreover, the MSA group showed no significant deficits in tests of spatial and pattern recognition previously shown to be sensitive to patients early in the course of probable Alzheimer's disease and only a few patients exhibited impairment on the Warrington Recognition Memory Test. There were impairments on other tests of visual memory and learning relative to matched controls, but these could not easily be related to fundamental deficits of memory or learning. Thus, on a matching-to-sample task the patients were impaired at simultaneous but not delayed matching to sample, whereas difficulties in a pattern-location learning task were more evident at its initial, easier stages. The MSA group showed no consistent evidence of intellectual deterioration as assessed from their performance on subtests of the Wechsler Adult Intelligence Scale (WAIS) and the National Adult Reading Test (NART). Consideration of individual cases showed that there was some heterogeneity in the pattern of deficits in the MSA group, with one patient showing no impairment, even in the face of considerable physical disability. The results show a distinctive pattern of cognitive deficits, unlike those previously seen using the same tests in patients with Parkinson's and Alzheimer's diseases, and suggesting a prominent frontal-lobe-like component. The implications for concepts of 'subcortical' dementia and 'fronto-striatal' cognitive dysfunction are considered

Accent processing in dementia

Accented speech conveys important nonverbal information about the speaker as well as presenting the brain with the problem of decoding a non-canonical auditory signal. The processing of non-native accents has seldom been studied in neurodegenerative disease and its brain basis remains poorly understood. Here we investigated the processing of non-native international and regional accents of English in cohorts of patients with Alzheimer's disease (AD; n=20) and progressive nonfluent aphasia (PNFA; n=6) in relation to healthy older control subjects (n=35). A novel battery was designed to assess accent comprehension and recognition and all subjects had a general neuropsychological assessment. Neuroanatomical associations of accent processing performance were assessed using voxel-based morphometry on MR brain images within the larger AD group. Compared with healthy controls, both the AD and PNFA groups showed deficits of non-native accent recognition and the PNFA group showed reduced comprehension of words spoken in international accents compared with a Southern English accent. At individual subject level deficits were observed more consistently in the PNFA group, and the disease groups showed different patterns of accent comprehension impairment (generally more marked for sentences in AD and for single words in PNFA). Within the AD group, grey matter associations of accent comprehension and recognition were identified in the anterior superior temporal lobe. The findings suggest that accent processing deficits may constitute signatures of neurodegenerative disease with potentially broader implications for understanding how these diseases affect vocal communication under challenging listening conditions

Quality of life evidence for patients with Alzheimer’s disease: use of existing quality of life evidence from the ADENA trials to estimate the utility impact of Exelon®

This paper utilises the Mini-Mental State Examination (MMSE) score of patients with Alzheimer’s disease to establish a relationship between disease progression and quality of life measures, and the author also compares his results to findings from the literature review about Alzheimer’s patient utility.Alzheimer's disease; quality of life

Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review.

Preserving cognition and mental capacity is critical to aging with autonomy. Early detection of pathological cognitive decline facilitates the greatest impact of restorative or preventative treatments. Artificial Intelligence (AI) in healthcare is the use of computational algorithms that mimic human cognitive functions to analyze complex medical data. AI technologies like machine learning (ML) support the integration of biological, psychological, and social factors when approaching diagnosis, prognosis, and treatment of disease. This paper serves to acquaint clinicians and other stakeholders with the use, benefits, and limitations of AI for predicting, diagnosing, and classifying mild and major neurocognitive impairments, by providing a conceptual overview of this topic with emphasis on the features explored and AI techniques employed. We present studies that fell into six categories of features used for these purposes: (1) sociodemographics; (2) clinical and psychometric assessments; (3) neuroimaging and neurophysiology; (4) electronic health records and claims; (5) novel assessments (e.g., sensors for digital data); and (6) genomics/other omics. For each category we provide examples of AI approaches, including supervised and unsupervised ML, deep learning, and natural language processing. AI technology, still nascent in healthcare, has great potential to transform the way we diagnose and treat patients with neurocognitive disorders

The Use of the Gaps-In-Noise Test as an Index of the Enhanced Left Temporal Cortical Thinning Associated with the Transition between Mild Cognitive Impairment and Alzheimer's Disease

Background: The known link between auditory perception and cognition is often overlooked when testing for cognition. Purpose: To evaluate auditory perception in a group of older adults diagnosed with mild cognitive impairment (MCI). Research Design: A cross-sectional study of auditory perception. Study Sample: Adults with MCI and adults with no documented cognitive issues and matched hearing sensitivity and age. Data collection: Auditory perception was evaluated in both groups, assessing for hearing sensitivity, speech in babble (SinB), and temporal resolution. Results: Mann‐Whitney test revealed significantly poorer scores for SinB and temporal resolution abilities of MCIs versus normal controls for both ears. The right-ear gap detection thresholds on the Gaps-In-Noise (GIN) Test clearly differentiated between the two groups (p < 0.001), with no overlap of values. The left ear results also differentiated the two groups (p < 0.01); however, there was a small degree of overlap ∼8-msec threshold values. With the exception of the left-ear inattentiveness index, which showed a similar distribution between groups, both impulsivity and inattentiveness indexes were higher for the MCIs compared to the control group. Conclusions: The results support central auditory processing evaluation in the elderly population as a promising tool to achieve earlier diagnosis of dementia, while identifying central auditory processing deficits that can contribute to communication deficits in the MCI patient population. A measure of temporal resolution (GIN) may offer an early, albeit indirect, measure reflecting left temporal cortical thinning associated with the transition between MCI and Alzheimer’s disease

Macro-Level Cognitive and Linguistic Function in Early Stage Alzheimer’s Disease and Mild Cognitive Impairment

Alzheimer’s disease (AD) is a global health concern, particularly as there is currently no cure for the disease. Interventions to slow progression of disease, pharmacological or non-pharmacological, need to be targeted early on before any significant neurodegeneration has occurred, as these changes are irreversible, and lost cognitive function cannot be recovered. This makes it imperative to detect pathological cognitive decline as early as possible. Although biomarkers have received a lot of attention in this regard, they have several limitations, particularly outside of research settings, such as cost and availability. Cognitive markers, other than traditional neuropsychological test measures, on the other hand, have received comparatively less attention with regards to early detection; and, particularly cognitive markers that are rooted in real-world, everyday cognition, have been lacking. Due to the disease being incurable, interventions are aimed at maintaining independent living and good quality of life for as long as possible. This necessitates outcomes that can measure meaningful change in cognition and everyday functioning. The goal of the present dissertation was to identify gaps in the current literature on cognitive and linguistic assessments that are embedded in aspects of everyday cognition in AD, and work towards developing paradigms to address the gaps. Due to the emphasis on early detection, the work focused on patients in the very early stage of AD and on its preceding stage of Mild Cognitive Impairment (MCI). In light of evidence reporting the inability of AD patients to follow narratives, be it verbal or non-verbal, a systematic review of text comprehension studies was conducted to characterize and evaluate macro-level measures of discourse comprehension in their sensitivity to early stage AD, and their ability to distinguish pathological ageing due to AD or MCI from cognitive ageing. Results showed that, not only AD patients, but also MCI patients were significantly more impaired on macro-level measures of comprehension compared to cognitively healthy older adults. These findings were consistent across all eight studies included in the review, indicating a robust effect, though there were minor differences in the sensitivity of different measures. Next, moving towards non-verbal narratives, a novel picture-based paradigm assessing event cognition, with a focus on event integration and macro-event recognition, was introduced. This study aimed to examine the macro-level processing of events by using a format requiring integration of micro-events, depicted in pictures, into a larger macro-event. AD and MCI patients’ ability to connect the micro-events temporally and causally to identify the depicted macro-event was assessed. As hypothesized, the findings showed that patient groups had significant difficulties in determining temporal order of micro-events, even when provided with a verbal cue, as well as in conceptualizing the macro-event from the presented micro-events, when compared to healthy older adults. Finally, using traditional neuropsychological tests, the cognitive processes involved in performing the macro-event recognition task were determined by examining correlations. Primarily, semantic memory and executive functioning appear to play a role. However, the strength of correlations was fairly moderate, indicating added value of event recognition task in cognitive assessment. Taken together, these findings show the sensitivity of macro-level cognitive and linguistic markers based in everyday cognition in the early stages of AD, and highlight the positive role of such cognitive assessment methods in bringing together objective assessment methods and everyday cognition