What older adults do with the results of dementia screening programs

Study protocol for a prediction model for mild cognitive impairment in older adults with diabetes mellitus and construction of a nurse-led screening system: a prospective observational study

INTRODUCTION

With an increasing number of older adults in China, the number of people with cognitive impairment is also increasing. To decrease the risk of dementia, it is necessary to timely detect mild cognitive impairment (MCI), which is the preliminary stage of dementia. The prevalence of MCI is relatively high among older adults with diabetes mellitus (DM); however, no effective screening strategy has been designed for this population. This study will construct a nurse-led screening system to detect MCI in community-dwelling older adults with DM in a timely manner.

METHODS AND ANALYSIS

A total of 642 participants with DM will be recruited (n=449 for development, n=193 for validation). The participants will be divided into MCI and none-MCI groups. The candidate predictors will include demographic variables, lifestyle factors, history of diseases, physical examinations, laboratory tests and neuropsychological tests. Univariate analysis, least absolute shrinkage and selection operator regression screening, and multivariate logistic regression analysis will be conducted to identify the outcome indicators. Based on the multivariate logistic regression equation, we will develop a traditional model as a comparison criterion for the machine learning models. The Hosmer-Lemeshow goodness-of-fit test and calibration curve will be used to evaluate the calibration. Sensitivity, specificity, area under the curves and clinical decision curve analysis will be performed for all models. We will report the sensitivity, specificity, area under the curve and decision curve analysis of the validation dataset. A prediction model with better performance will be adopted to form the nurse-led screening system.

ETHICS AND DISSEMINATION

This prospective study has received institutional approval of the Medical Ethics Committee of Qidong Hospital of TCM (QDSZYY-LL-20220621). Study results will be disseminated through conference presentations, Chinese Clinical Trial Registry and publication.

TRIAL REGISTRATION NUMBER

ChiCTR2200062855.

Testing the 'Faith Moves Mountains model' to increase Alzheimer's disease awareness, detection, and diagnosis among rural, racially, and ethnically diverse older adults

OBJECTIVES

Racially and ethnically diverse populations have recently contributed to the majority of rural and small-town growth. Consequently, the disproportionately high risk and prevalence of Alzheimer's disease and related dementias (ADRD) among rural and minoritized older residents will likely increase. To address this threat, we tested the hypotheses that (1) a faith-based, resident-led approach would increase basic ADRD knowledge and diagnosis, and (2) older age, female gender, lower educational levels, and more years lived rural would predict number of referrals, new dementia diagnoses, and treatment.

METHODS

An adaptation of Schoenberg's Faith Moves Mountains model, previously successful in detection and management of other chronic illnesses in rural settings, guided this community-based participatory research. Local faith community members were trained as research assistants to recruit, administer surveys, conduct brief memory assessments, teach brain health strategies, and follow-up with residents. Outreaches were offered virtually during the pandemic, then in-person monthly at rotating church sites, and repeated ∼1 year later.

RESULTS

This rural sample was racially and ethnically diverse (74.5% non-White), with 28% reporting eight or less years of formal education. Findings included that referrals and years lived rural were significant and positive predictors of new ADRD treatments [(b = 3.74, χ2(1, n = 235) = 13.01, p < 0.001); (b = 0.02, χ2(1, n = 235 = 3.93, p = 0.048)], respectively, regardless of participant characteristics.

CONCLUSION

Resident-led action research in rural, diverse, faith communities is a successful approach to increasing ADRD disease knowledge, detection, diagnosis, and treatment.

Association of blood pressure variability during acute care hospitalization and incident dementia

Background and objectives

Recognized as a potential risk factor for Alzheimer's disease and related dementias (ADRD), blood pressure variability (BPV) could be leveraged to facilitate identification of at-risk individuals at a population level. Granular BPV data are available during acute care hospitalization periods for potentially high-risk patients, but the incident ADRD risk association with BPV measured in this setting is unknown. Our objective was to evaluate the relation of BPV, measured during acute care hospitalization, and incidence of ADRD.

Methods

We retrospectively studied adults, without a prior ADRD diagnosis, who were admitted to a large quaternary care medical center in Southern California between January 1, 2013 and December 31, 2019. For all patients, determined BPV, calculated as variability independent of the mean (VIM), using blood pressure readings obtained as part of routine clinical care. We used multivariable Cox proportional hazards regression to examine the association between BP VIM during hospitalization and the development of incident dementia, determined by new ICD-9/10 coding or the new prescription of dementia medication, occurring at least 2 years after the index hospitalization.

Results

Of 81,892 adults hospitalized without a prior ADRD diagnosis, 2,442 (2.98%) went on to develop ADRD (2.6 to 5.2 years after hospitalization). In multivariable-adjusted Cox models, both systolic (HR 1.05, 95% CI 1.00-1.09) and diastolic (1.06, 1.02-1.10) VIM were associated with incident ADRD. In pre-specified stratified analyses, the VIM associations with incident ADRD were most pronounced in individuals over age 60 years and among those with renal disease or hypertension. Results were similar when repeated to include incident ADRD diagnoses made at least 1 or 3 years after index hospitalization.

Discussion

We found that measurements of BPV from acute care hospitalizations can be used to identify individuals at risk for developing a diagnosis of ADRD within approximately 5 years. Use of the readily accessible BPV measure may allow healthcare systems to risk stratify patients during periods of intense patient-provider interaction and, in turn, facilitate engagement in ADRD screening programs.

Primary Care Provider Preferences on Dementia Training: A Qualitative Study

BACKGROUND

Dementia has no cure, but interventions can stabilize the progression of cognitive, functional, and behavioral symptoms. Primary care providers (PCPs) are vital for the early detection, and long-term management of these diseases, given their gatekeeping role in the healthcare system. However, PCPs rarely implement evidence-based dementia care due to time limitations and knowledge about diagnosis and treatment. Training PCPs may help address these barriers.

OBJECTIVE

We explored the preferences of PCPs for dementia care training programs.

METHODS

We conducted qualitative interviews with 23 PCPs recruited nationally via snowball sampling. We conducted remote interviews and organized the transcripts for qualitative review to identify codes and themes, using thematic analysis methods.

RESULTS

PCP preferences varied regarding many aspects of ADRD training. Preferences varied regarding how to best increase PCP participation in training, and what content and materials were needed to help them and the families they serve. We also found differences regarding the duration and timing of training, and the modality of training sessions (remote versus in-person).

CONCLUSION

The recommendations arising from these interviews have the potential to inform the development and refinement of dementia training programs to optimize their implementation and success.

Hierarchical Two-Stage Cost-Sensitive Clinical Decision Support System for Screening Prodromal Alzheimer's Disease and Related Dementias

BACKGROUND

The detection of subtle cognitive impairment in a clinical setting is difficult. Because time is a key factor in small clinics and research sites, the brief cognitive assessments that are relied upon often misclassify patients with very mild impairment as normal.

OBJECTIVE

In this study, we seek to identify a parsimonious screening tool in one stage, followed by additional assessments in an optional second stage if additional specificity is desired, tested using a machine learning algorithm capable of being integrated into a clinical decision support system.

METHODS

The best primary stage incorporated measures of short-term memory, executive and visuospatial functioning, and self-reported memory and daily living questions, with a total time of 5 minutes. The best secondary stage incorporated a measure of neurobiology as well as additional cognitive assessment and brief informant report questionnaires, totaling 30 minutes including delayed recall. Combined performance was evaluated using 25 sets of models, trained on 1,181 ADNI participants and tested on 127 patients from a memory clinic.

RESULTS

The 5-minute primary stage was highly sensitive (96.5%) but lacked specificity (34.1%), with an AUC of 87.5% and diagnostic odds ratio of 14.3. The optional secondary stage increased specificity to 58.6%, resulting in an overall AUC of 89.7% using the best model combination of logistic regression and gradient-boosted machine.

CONCLUSION

The primary stage is brief and effective at screening, with the optional two-stage technique further increasing specificity. The hierarchical two-stage technique exhibited similar accuracy but with reduced costs compared to the more common single-stage paradigm.

Exploring Reasons for Differential Vulnerability and Alzheimer's Disease Risk in Racial and Ethnic Minorities

BACKGROUND

African American and Hispanic older adults are reported to have up to a 2-fold higher risk of Alzheimer's disease and related disorders (ADRD), but the reasons for this increased vulnerability have not been fully explored. The Vulnerability Index (VI) was designed to identify individuals who are at risk of developing cognitive impairment in the future, capturing 12 sociodemographic variables and modifiable medical comorbidities associated with higher ADRD risk. However, a prior limitation of the VI was that the original study cohort had limited diversity. We examined the association of the VI within and between non-Hispanic White, African American, and Hispanic older adults with and without cognitive impairment and different socioeconomic strata enrolled in a community-based dementia screening study.

OBJECTIVE

To explore reasons for reported higher ADRD vulnerability in African Americans and Hispanics.

METHODS

In a cross-sectional study of 300 non-Hispanic White, African American, and Hispanic older adults with and without cognitive impairment, we studied the association between cognitive status, the VI, and socioeconomic status (SES).

RESULTS

When considering race/ethnicity, the presence of more vascular comorbidities drove greater vulnerability. When considering SES, vascular comorbidities played a less prominent role suggesting resources and access to care drives risk. The VI had differential effects on cognitive performance with the greatest effect in the earlier stages of impairment.

CONCLUSION

Findings from this study provide a deeper understanding of the differential risk of ADRD in multicultural older adults captured by the VI and how barriers to healthcare access may increase vulnerability in racial/ethnic minorities.

Using the Montreal cognitive assessment to identify individuals with subtle cognitive decline

OBJECTIVE

Dementia is a devastating neurological disease that may be better managed if diagnosed earlier when subclinical neurodegenerative changes are already present, including subtle cognitive decline and mild cognitive impairment. In this study, we used item-level performance on the Montreal Cognitive Assessment (MoCA) to identify individuals with subtle cognitive decline.

METHOD

Individual MoCA item data from the Alzheimer's Disease Neuroimaging Initiative was grouped using k-modes cluster analysis. These clusters were validated and examined for association with convergent neuropsychological tests. The clusters were then compared and characterized using multinomial logistic regression.

RESULTS

A three-cluster solution had 77.3% precision, with Cluster 1 (high performing) displaying no deficits in performance, Cluster 2 (memory deficits) displaying lower memory performance, and Cluster 3 (compound deficits) displaying lower performance on memory and executive function. Age at MoCA (older in compound deficits), gender (more females in memory deficits), and marital status (fewer married in compound deficits) were significantly different among clusters. Age was not associated with increased odds of membership in the high-performing cluster compared to the others.

CONCLUSIONS

We identified three clusters of individuals classified as cognitively unimpaired using cluster analysis. Individuals in the compound deficits cluster performed lower on the MoCA and were older and less often married than individuals in other clusters. Demographic analyses suggest that cluster identity was due to a combination of both cognitive and clinical factors. Identifying individuals at risk for future cognitive decline using the MoCA could help them receive earlier evidence-based interventions to slow further cognitive decline. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Factors affecting cognitive dysfunction screening for Latinx adults with type 2 diabetes

Aim

To examine influences on screening of Latinx adults with type 2 diabetes for cognitive problems by identifying patient-, clinician-, and clinic-level factors.

Methods

This was a mixed methods study consisting of semi-structured interviews with Latinx adults with type 2 diabetes (n = 30; mean age = 68; 57% Mexican American) and surveys and interviews with health care providers (n = 15) in Central Texas. Data were examined with thematic analysis (interviews) and descriptive statistics (surveys and inventories).

Results

For the interviewed patients, screening was important, but inability to work related to a possible diagnosis of dementia was a concern. Both providers and patients agreed that other health issues (e.g., hyperglycemia) took precedence over cognitive screening. Providers (96.7%) were expected to screen patients but lacked clinic support and time; they relied on patients for initial prompts. Only one clinic required staff education on cognitive screening, with an emphasis on potential cultural differences in test results and adequate resources related to dementia for Latinx adults.

Conclusions

Clinics serving Latinx adults have a responsibility to deliver appropriate care. Leadership should consider innovative practices such as the creation, with patients, of educational materials for screening—a need highlighted by most participants.

Acceptability and Preliminary Effectiveness of a Remote Dementia Educational Training Among Primary Care Providers and Health Navigators

BACKGROUND

Optimal care can improve lives of families with dementia but remains under-implemented. Most healthcare professional training is in person, time-intensive, and does not focus on key aspects such as early detection, and cultural competency.

OBJECTIVE

We explored the acceptability and preliminary effectiveness of a training, The Dementia Update Course, which addressed these issues. We hypothesized that the training would lead to increased levels of perceived dementia care competency among key healthcare workers, namely primary care providers (PCPs) and health navigators (HNs).

METHODS

We conducted pre-post training assessments among 22 PCPs and 32 HNs. The 6.5-h training was remote, and included didactic lectures, case discussion techniques, and materials on dementia detection and care. Outcomes included two 5-point Likert scales on acceptability, eleven on perceived dementia care competency, and the three subscales of the General Practitioners Confidence and Attitude Scale for Dementia. We used paired samples t-tests to assess the mean differences in all preliminary effectiveness outcomes.

RESULTS

The training included 28.6% of PCPs and 15.6% of HNs that self-identified as non-White or Latino and 45.5% of PCPs and 21.9% of HNs who served in rural areas. PCPs (84.2%) and HNs (91.7%) reported a high likelihood to recommend the training and high satisfaction. Most preliminary effectiveness outcomes analyzed among PCPs (11/14) and all among HNs (8/8) experienced an improvement from pre- to post-training (p < 0.05).

CONCLUSION

A relatively brief, remote, and inclusive dementia training was associated with high levels of acceptability and improvements in perceived dementia care competency among PCPs and HNs.

The Cognitive & Leisure Activity Scale (CLAS): A new measure to quantify cognitive activities in older adults with and without cognitive impairment

INTRODUCTION

Potentially modifiable dementia risk factors include diet and physical and cognitive activity. However, there is a paucity of scales to quantify cognitive activities. To address this, we developed the Cognitive & Leisure Activity Scale (CLAS).

METHODS

The CLAS was validated in 318 consecutive individuals with and without cognitive impairment. Psychometric properties were compared with sample characteristics, disease stage, and etiology.

RESULTS

The CLAS has very good data quality (Cronbach alpha: 0.731; 95% confidence interval: 0.67-0.78). CLAS scores correlated with gold standard measures of cognition, function, physical functionality, behavior, and caregiver burden. CLAS scores were positively correlated with other resilience factors (eg, diet, physical activity) and negatively correlated with vulnerability factors (eg, older age, frailty).

DISCUSSION

The CLAS is a brief inventory to estimate dosage of participation in cognitive activities. The CLAS could be used in clinical care to enhance cognitive activity or in research to estimate dosage of activities prior to an intervention.

Cognitive measures lacking in EHR prior to dementia or Alzheimer's disease diagnosis

Introduction

The extent that cognitive measures are documented in electronic health records (EHR) is important for quality care and addressing disparities in timely diagnosis of dementia or Alzheimer's disease (AD).

Methods

Analysis of U.S. EHR data to describe the frequency and factors associated with cognitive measures prior to diagnosis of dementia (N = 111,125) or AD (N = 30,203).

Results

Only 11% of dementia patients and 24% of AD patients had a cognitive measure documented in the 5 years prior to diagnosis. Black race, older age, non‐commercial health insurance, lower mean neighborhood income, greater in‐patient stays, and fewer out‐patient visits were associated with lacking cognitive measures.

Discussion

Extensive missing cognitive data and differences in the availability of cognitive measures by race, age, and socioeconomic factors hinder patient care and limit utility of EHR for dementia research. Structured fields and prompts for cognitive data inputs at the point of care may help address these gaps.

Detecting dementia among older, ethnically diverse residents of rural subsidized housing

Rural, ethnically diverse residents face at least twice the risk of Alzheimer's disease than urban residents. Chronic diseases such as diabetes and hypertension which increase dementia risk are more prevalent in rural areas with less access to specialty providers. A home-based approach for increasing dementia detection and treatment rates was tested among rural residents of government-assisted independent living facilities (N = 139; 78% non-White, and 70% with health literacy below 5th grade). Of 28 residents identified at risk during cognitive screening, 25 agreed to further in-depth assessment by adult gerontological nurse practitioners (AGNP). Fifteen of 25 (60%) completing consequent primary provider referrals were diagnosed with dementia and receiving new care (statistically significant; [χ2(1) = 76.67, p < .001, Phi = 0.743]). Home-based dementia management through a community engagement approach can help to meet the Healthy People 2030 goals of earlier detection and treatment and reduce the length of costly institutionalizations.

Screening for Early-Stage Alzheimer's Disease Using Optimized Feature Sets and Machine Learning

BACKGROUND

Detecting early-stage Alzheimer's disease in clinical practice is difficult due to a lack of efficient and easily administered cognitive assessments that are sensitive to very mild impairment, a likely contributor to the high rate of undetected dementia.

OBJECTIVE

We aim to identify groups of cognitive assessment features optimized for detecting mild impairment that may be used to improve routine screening. We also compare the efficacy of classifying impairment using either a two-class (impaired versus non-impaired) or three-class using the Clinical Dementia Rating (CDR 0 versus CDR 0.5 versus CDR 1) approach.

METHODS

Supervised feature selection methods generated groups of cognitive measurements targeting impairment defined at CDR 0.5 and above. Random forest classifiers then generated predictions of impairment for each group using highly stochastic cross-validation, with group outputs examined using general linear models.

RESULTS

The strategy of combining impairment levels for two-class classification resulted in significantly higher sensitivities and negative predictive values, two metrics useful in clinical screening, compared to the three-class approach. Four features (delayed WAIS Logical Memory, trail-making, patient and informant memory questions), totaling about 15 minutes of testing time (∼30 minutes with delay), enabled classification sensitivity of 94.53% (88.43% positive predictive value, PPV). The addition of four more features significantly increased sensitivity to 95.18% (88.77% PPV) when added to the model as a second classifier.

CONCLUSION

The high detection rate paired with the minimal assessment time of the four identified features may act as an effective starting point for developing screening protocols targeting cognitive impairment defined at CDR 0.5 and above.

The Resilience Index: A Quantifiable Measure of Brain Health and Risk of Cognitive Impairment and Dementia

BACKGROUND

There is increasing interest in lifestyle modification and integrative medicine approaches to treat and/or prevent mild cognitive impairment (MCI) and Alzheimer's disease and related dementias (ADRD).

OBJECTIVE

To address the need for a quantifiable measure of brain health, we created the Resilience Index (RI).

METHODS

This cross-sectional study analyzed 241 participants undergoing a comprehensive evaluation including the Clinical Dementia Rating and neuropsychological testing. Six lifestyle factors including physical activity, cognitive activity, social engagements, dietary patterns, mindfulness, and cognitive reserve were combined to derive the RI (possible range of scores: 1-378). Psychometric properties were determined.

RESULTS

The participants (39 controls, 75 MCI, 127 ADRD) had a mean age of 74.6±9.5 years and a mean education of 15.8±2.6 years. The mean RI score was 138.2±35.6. The RI provided estimates of resilience across participant characteristics, cognitive staging, and ADRD etiologies. The RI showed moderate-to-strong correlations with clinical and cognitive measures and very good discrimination (AUC: 0.836; 95% CI: 0.774-0.897) between individuals with and without cognitive impairment (diagnostic odds ratio = 8.9). Individuals with high RI scores (> 143) had better cognitive, functional, and behavioral ratings than individuals with low RI scores. Within group analyses supported that controls, MCI, and mild ADRD cases with high RI had better cognitive, functional, and global outcomes than those with low RI.

CONCLUSION

The RI is a brief, easy to administer, score and interpret assessment of brain health that incorporates six modifiable protective factors. Results from the RI could provide clinicians and researchers with a guide to develop personalized prevention plans to support brain health.

Overcoming the COVID-19 Pandemic for Dementia Research: Engaging Rural, Older, Racially and Ethnically Diverse Church Attendees in Remote Recruitment, Intervention and Assessment

BACKGROUND

Access to cognitive screening in rural underserved communities is limited and was further diminished during the COVID-19 pandemic. We examined whether a telephone-based cognitive screening intervention would be effective in increasing ADRD knowledge, detecting the need for further cognitive evaluation, and making and tracking the results of referrals.

METHOD

Using a dependent t-test design, older, largely African American and Afro-Caribbean participants completed a brief educational intervention, pre/post AD knowledge measure, and cognitive screening.

RESULTS

Sixty of 85 eligible individuals consented. Seventy-percent of the sample self-reported as African American, Haitian Creole, or Hispanic, and 75% were female, with an average age of 70. AD knowledge pre-post scores improved significantly (t (49) = -3.4, p < .001). Of the 11 referred after positive cognitive screening, 72% completed follow-up with their provider. Five were newly diagnosed with dementia. Three reported no change in diagnosis or treatment. Ninety-percent consented to enrolling in a registry for future research.

CONCLUSION

Remote engagement is feasible for recruiting, educating, and conducting cognitive screening with rural older adults during a pandemic.

Medical and Social Determinants of Brain Health and Dementia in a Multicultural Community Cohort of Older Adults

BACKGROUND

Socioeconomic status (SES), race, ethnicity, and medical comorbidities may contribute to Alzheimer's disease and related disorders (ADRD) health disparities.

OBJECTIVE

Analyze effects of social and medical determinants on cognition in 374 multicultural older adults participating in a community-based dementia screening program.

METHODS

We used the Montreal Cognitive Assessment (MoCA) and AD8 as measures of cognition, and a 3-way race/ethnicity variable (White, African American, Hispanic) and SES (Hollingshead index) as predictors. Potential contributors to health disparities included: age, sex, education, total medical comorbidities, health self-ratings, and depression. We applied K-means cluster analyses to study medical and social dimension effects on cognitive outcomes.

RESULTS

African Americans and Hispanics had lower SES status and cognitive performance compared with similarly aged Whites. We defined three clusters based on age and SES. Cluster #1 and #3 differed by SES but not age, while cluster #2 was younger with midlevel SES. Cluster #1 experienced the worse health outcomes while cluster #3 had the best health outcomes. Within each cluster, White participants had higher SES and better health outcomes, African Americans had the worst physical performance, and Hispanics had the most depressive symptoms. In cross-cluster comparisons, higher SES led to better health outcomes for all participants.

CONCLUSION

SES may contribute to disparities in access to healthcare services, while race and ethnicity may contribute to disparities in the quality and extent of services received. Our study highlights the need to critically address potential interactions between race, ethnicity, and SES which may better explain disparities in ADRD health outcomes.

The Number Symbol Coding Task: A brief measure of executive function to detect dementia and cognitive impairment

Introduction

Alzheimer’s disease and related dementias (ADRD) affect over 5.7 million Americans and over 35 million people worldwide. Detection of mild cognitive impairment (MCI) and early ADRD is a challenge to clinicians and researchers. Brief assessment tools frequently emphasize memory impairment, however executive dysfunction may be one of the earliest signs of impairment. To address the need for a brief, easy-to-score, open-access test of executive function for use in clinical practice and research, we created the Number Symbol Coding Task (NSCT).

Methods

This study analyzed 320 consecutive patient-caregiver dyads who underwent a comprehensive evaluation including the Clinical Dementia Rating (CDR), patient and caregiver versions of the Quick Dementia Rating System (QDRS), caregiver ratings of behavior and function, and neuropsychological testing, with a subset undergoing volumetric magnetic resonance imaging (MRI). Estimates of cognitive reserve were calculated using education, combined indices of education and occupation, and verbal IQ. Psychometric properties of the NSCT including data quality, data distribution, floor and ceiling effects, construct and known-groups validity, discriminability, and clinical profiles were determined.

Results

The patients had a mean age of 75.3±9.2 years (range 38-98y) with a mean education of 15.7±2.8 years (range 6-26y) of education. The patients had a mean CDR-SB of 4.8±4.7 (range 0–18) and a mean MoCA score of 18.6±7.1 (range 1–30). The mean NSCT score was 30.1±13.8 and followed a normal distribution. All healthy controls and MCI cases were able to complete the NSCT. The NSCT showed moderate-to-strong correlations with clinical and neuropsychological measures with the strongest association (all p’s < .001) for measures with executive components (e.g., Judgement and Problem Solving box of the CDR, Decision Making and Problem Solving domain of the QDRS, Trailmaking B, and Cognigram Attention and Executive Composite Scores). Women slightly outperformed men, and individuals with lower educational attainment and lower education-occupation indices had lower NSCT scores. Decreasing NSCT scores corresponded to older age, worse cognitive scores, higher CDR sum of boxes scores, worse caregiver ratings of function and behavior, worse patient and informant QDRS ratings, and smaller hippocampal volumes and hippocampal occupancy scores. The NSCT provided excellent discrimination (AUC: .866; 95% CI: .82-.91) with a cut-off score of 36 providing the best combination of sensitivity (0.880) and specificity (0.759). Combining the NSCT with patient QDRS and caregiver QDRS ratings improved discrimination (AUC: .908; 95% CI: .87-.94).

Discussion

The NSCT is a brief, 90-second executive task that incorporates attention, planning and set-switching that can be completed by individuals into the moderate-to-severe stages of dementia. The NSCT may be a useful tool for dementia screening, case-ascertainment in epidemiological or community-based ADRD studies, and in busy primary care settings where time is limited. Combining the NSCT with a brief structured interview tool such as the QDRS may provide excellent power to detect cognitive impairment. The NSCT performed well in comparison to standardized scales of a comprehensive cognitive neurology evaluation across a wide array of sociodemographic variables in a brief fashion that could facilitate its use in clinical care and research.

The Quick Physical Activity Rating (QPAR) scale: A brief assessment of physical activity in older adults with and without cognitive impairment

INTRODUCTION

Alzheimer's disease and related dementias (ADRD) currently affect over 5.7 million Americans and over 35 million people worldwide. At the same time, over 31 million older adults are physically inactive with impaired physical performance interfering with activities of daily living. Low physical activity is a risk factor for ADRD. We examined the utility of a new measure, the Quick Physical Activities Rating (QPAR) as an informant-rated instrument to quantify the dosage of physical activities in healthy controls, MCI and ADRD compared with Gold Standard assessments of objective measures of physical performance, fitness, and functionality.

METHODS

This study analyzed 390 consecutive patient-caregiver dyads who underwent a comprehensive evaluation including the Clinical Dementia Rating (CDR), mood, neuropsychological testing, caregiver ratings of patient behavior and function, and a comprehensive physical performance and gait assessment. The QPAR was completed prior to the office visit and was not considered in the clinical evaluation, physical performance assessment, staging or diagnosis of the patient. Psychometric properties including item variability and distribution, floor and ceiling effects, strength of association, known-groups performance, and internal consistency were determined.

RESULTS

The patients had a mean age of 75.3±9.2 years, 15.7±2.8 years of education and were 46.9% female. The patients had a mean CDR-SB of 4.8±4.7 and a mean MoCA score of 18.6±7.1 and covered a range of healthy controls (CDR 0 = 54), MCI or very mild dementia (CDR 0.5 = 161), mild dementia (CDR 1 = 92), moderate dementia (CDR 2 = 64), and severe dementia (CDR 3 = 29). The mean QPAR score was 20.2±18.9 (range 0-132) covering a wide range of physical activity. The QPAR internal consistency (Cronbach alpha) was very good at 0.747. The QPAR was correlated with measures of physical performance (dexterity, grip strength, gait, mobility), physical functionality rating scales, measures of activities of daily living and comorbidities, the UPDRS, and frailty ratings (all p < .001). The QPAR report of physical activities was able to discriminate between individuals with impaired physical functionality (32.2±23.9 vs 15.2±13.8, p < .001), falls risk (28.4±21.6 vs. 14.5±13.2, p < .001), and the presence of frailty (28.1±22.7 vs. 11.8±9.4, p < .001). The QPAR showed strong psychometric properties and excellent data quality, and worked equally well across different patient ages, sexes, informant relationships, and in individuals with and without cognitive impairment.

DISCUSSION

The QPAR is a brief detection tool that captures informant reports of physical activities and differentiates individuals with normal physical functionality from those individuals with impaired physical functionality. The QPAR correlated with Gold Standard assessments of strength and sarcopenia, activities of daily living, gait and mobility, fitness, health related quality of life, frailty, global physical performance, and provided good discrimination between states of physical functionality, falls risk, and frailty. The QPAR performed well in comparison to standardized scales of objective physical performance, but in a brief fashion that could facilitate its use in clinical care and research.

Using a patient-reported outcome to improve detection of cognitive impairment and dementia: The patient version of the Quick Dementia Rating System (QDRS)

INTRODUCTION

Community detection of mild cognitive impairment (MCI) and Alzheimer's disease and related disorders (ADRD) is a challenge. While Gold Standard assessments are commonly used in research centers, these methods are time consuming, require extensive training, and are not practical in most clinical settings or in community-based research projects. Many of these methods require an informant (e.g., spouse, adult child) to provide ratings of the patients' cognitive and functional abilities. A patient-reported outcome that captures the presence of cognitive impairment and corresponds to Gold Standard assessments could improve case ascertainment, clinical care, and recruitment into clinical research. We tested the patient version of the Quick Dementia Rating System (QDRS) as a patient-reported outcome to detect MCI and ADRD.

METHODS

The patient QDRS was validated in a sample of 261 consecutive patient-caregiver dyads compared with the informant version of the QDRS, the Clinical Dementia Rating (CDR), neuropsychological tests, and Gold Standard measures of function, behavior, and mood. Psychometric properties including item variability, floor and ceiling effects, construct, concurrent, and known-groups validity, and internal consistency were determined.

RESULTS

The patient QDRS strongly correlated with Gold Standard measures of cognition, function, mood, behavior, and global staging methods (p-values < .001) and had strong psychometric properties with excellent data quality and internal consistency (Cronbach alpha = 0.923, 95%CI:0.91-0.94). The patient QDRS had excellent agreement with the informant QDRS, the CDR and its sum of boxes (Intraclass Correlation Coefficients: 9.781-0.876). Receiver operator characteristic curves showed excellent discrimination between normal controls from CDR 0.5 (AUC:0.820;95% CI: 0.74-0.90) and for normal controls from any cognitive impairment (AUC:0.885;95% CI: 0.83-0.94).

DISCUSSION

The patient QDRS validly and reliably differentiates individuals with and without cognitive impairment and can be completed by patients through all stages of dementia. The patient QDRS is highly correlated with Gold Standard measures of cognitive, function, behavior, and global staging. The patient QDRS provides a rapid method to screen patients for MCI and ADRD in clinical practice, determine study eligibility, improve case ascertainment in community studies.