Using electronic health records to estimate the prevalence of agitation in Alzheimer disease/dementia

Brexpiprazole treatment for agitation in Alzheimer's dementia: A randomized study

INTRODUCTION

We evaluated the efficacy and safety of brexpiprazole for the treatment of agitation in Alzheimer's dementia (AAD) in Japanese patients.

METHODS

This was a phase 2/3 multicenter, randomized, double-blind, placebo-controlled, parallel-group study. Patients with AAD were randomized to receive brexpiprazole 1 mg/day or 2 mg/day, or placebo (3:4:4) for 10 weeks.

RESULTS

For the primary endpoint (change in Cohen-Mansfield Agitation Inventory [CMAI] total score from baseline to Week 10), both brexpiprazole 1 mg and 2 mg groups demonstrated statistically significant improvement versus placebo (2 mg: least squares [LS] mean difference -7.2 [95% confidence interval (CI): -10.0 to -4.3], p-value < 0.0001, 1 mg: LS mean difference -3.7 [95% CI: -6.8 to -0.7], p-value = 0.0175). The incidences of treatment-emergent adverse events reported in the brexpiprazole 1 mg, 2 mg, and placebo groups were 76.8%, 84.6%, and 73.8%, respectively.

DISCUSSION

Brexpiprazole 1 mg/day and 2 mg/day for 10 weeks was efficacious and well tolerated.

HIGHLIGHTS

Brexpiprazole treatment for 10 weeks improved agitation in Alzheimer's dementia. The efficacy of brexpiprazole 1 mg/day has been confirmed for the first time. The incidence of adverse events was higher compared to the previous studies. Both brexpiprazole 1 mg/day and 2 mg/day were generally well tolerated.

Association between risk of Alzheimer's disease and related dementias and angiotensin receptor Ⅱ blockers treatment for individuals with hypertension in high-volume claims data

BACKGROUND

Findings regarding the protective effect of Angiotensin II receptor blockers (ARBs) against Alzheimer's disease and related dementias (AD/ADRD) and cognitive decline have been inconclusive.

METHODS

Individuals with hypertension who do not have any prior ADRD diagnosis were included in this retrospective cohort study from Optum's de-identified Clinformatics® Data Mart. We identified antihypertensive medication (AHM) drug classes and subclassified ARBs by blood-brain barrier (BBB) permeability. We compared baseline characteristics and used the Kaplan-Meier (KM) survival curve and adjusted Cox proportional hazards (PH) model for survival analyses.

FINDINGS

From 6,390,826 individuals with hypertension, there were 1,839,176 ARB users, 3,366,841 non-ARB AHM users, and 1,184,809 AHM non-users. The unadjusted KM curve showed that ARB users had lower cumulative hazard than other AHM users or AHM non-users (P < 0.0001). In Cox PH analysis, ARB users showed a 20% lower adjusted hazard of developing ADRD compared to angiotensin-converting enzyme inhibitor (ACEI) users and a 29% and 18% reduced hazard when compared to non-ARB/ACEI AHM users and AHM non-users (all P < 0.0001). Consumption of BBB-crossing ARBs was linked to a lower hazard of ADRD development than non-BBB-crossing ARBs, undetermined ARBs, and non-consumption of AHMs by 11%, 25%, and 31% (all P < 0.0001).

INTERPRETATION

This study suggests that ARBs are superior to ACEIs, non-ARB/ACEI AHMs, or non-use of AHMs in reducing the hazard of ADRD among patients with hypertension. Also, BBB-permeability in ARBs was associated with lower ADRD incidence. There is no cure for AD, ADRD, or vascular dementia; hence, these findings are significant in preventing those disorders in an inexpensive, convenient, and safe way. Limitations in claims data should be considered when interpreting our findings.

FUNDING

This research was supported by the National Institute on Aging grants (R01AG084236, R01AG083039, RF1AG072799, R56AG074604).

Extracting Critical Information from Unstructured Clinicians' Notes Data to Identify Dementia Severity Using a Rule-Based Approach: Feasibility Study

BACKGROUND

The severity of Alzheimer disease and related dementias (ADRD) is rarely documented in structured data fields in electronic health records (EHRs). Although this information is important for clinical monitoring and decision-making, it is often undocumented or "hidden" in unstructured text fields and not readily available for clinicians to act upon.

OBJECTIVE

We aimed to assess the feasibility and potential bias in using keywords and rule-based matching for obtaining information about the severity of ADRD from EHR data.

METHODS

We used EHR data from a large academic health care system that included patients with a primary discharge diagnosis of ADRD based on ICD-9 (International Classification of Diseases, Ninth Revision) and ICD-10 (International Statistical Classification of Diseases, Tenth Revision) codes between 2014 and 2019. We first assessed the presence of ADRD severity information and then the severity of ADRD in the EHR. Clinicians' notes were used to determine the severity of ADRD based on two criteria: (1) scores from the Mini Mental State Examination and Montreal Cognitive Assessment and (2) explicit terms for ADRD severity (eg, "mild dementia" and "advanced Alzheimer disease"). We compiled a list of common ADRD symptoms, cognitive test names, and disease severity terms, refining it iteratively based on previous literature and clinical expertise. Subsequently, we used rule-based matching in Python using standard open-source data analysis libraries to identify the context in which specific words or phrases were mentioned. We estimated the prevalence of documented ADRD severity and assessed the performance of our rule-based algorithm.

RESULTS

We included 9115 eligible patients with over 65,000 notes from the providers. Overall, 22.93% (2090/9115) of patients were documented with mild ADRD, 20.87% (1902/9115) were documented with moderate or severe ADRD, and 56.20% (5123/9115) did not have any documentation of the severity of their ADRD. For the task of determining the presence of any ADRD severity information, our algorithm achieved an accuracy of >95%, specificity of >95%, sensitivity of >90%, and an F1-score of >83%. For the specific task of identifying the actual severity of ADRD, the algorithm performed well with an accuracy of >91%, specificity of >80%, sensitivity of >88%, and F1-score of >92%. Comparing patients with mild ADRD to those with more advanced ADRD, the latter group tended to contain older, more likely female, and Black patients, and having received their diagnoses in primary care or in-hospital settings. Relative to patients with undocumented ADRD severity, those with documented ADRD severity had a similar distribution in terms of sex, race, and rural or urban residence.

CONCLUSIONS

Our study demonstrates the feasibility of using a rule-based matching algorithm to identify ADRD severity from unstructured EHR report data. However, it is essential to acknowledge potential biases arising from differences in documentation practices across various health care systems.

Effects of Bright Light Therapy on Agitation Among Older Adults Living with Dementia in Macao: A Pilot Study

A randomized controlled trial was conducted to examine the effects of bright light therapy on agitation in older adults with dementia in Macao. This study involved 31 participants: 10 in the outdoor light treatment group, 11 in the indoor light-box treatment group, and 10 in the control group. Significant reductions in agitation were observed in the two treatment groups over four weeks compared to the control group. However, no statistical difference in cognitive function between experimental and control groups was found. This study supports the use of bright light therapy to reduce agitation in older people with dementia.

Agitation in cognitive disorders: Progress in the International Psychogeriatric Association consensus clinical and research definition

BACKGROUND

The International Psychogeriatric Association (IPA) published a provisional consensus definition of agitation in cognitive disorders in 2015. As proposed by the original work group, we summarize the use and validation of criteria in order to remove "provisional" from the definition.

METHODS

This report summarizes information from the academic literature, research resources, clinical guidelines, expert surveys, and patient and family advocates on the experience of use of the IPA definition. The information was reviewed by a working group of topic experts to create a finalized definition.

RESULTS

We present a final definition which closely resembles the provisional definition with modifications to address special circumstances. We also summarize the development of tools for diagnosis and assessment of agitation and propose strategies for dissemination and integration into precision diagnosis and agitation interventions.

CONCLUSION

The IPA definition of agitation captures a common and important entity that is recognized by many stakeholders. Dissemination of the definition will permit broader detection and can advance research and best practices for care of patients with agitation.

Care partner evaluation of the behaviors in the Cohen-Mansfield Agitation Inventory

Introduction

Agitation is a common symptom in patients with Alzheimer's dementia. But agitation can be a heterogeneous symptom, encompassing a diverse array of behaviors exhibited by patients. The Cohen-Mansfield Agitation Inventory (CMAI) is a 29-item scale that is used to systematically assess the frequency and severity of agitation in older adults as rated by a primary caregiver. The CMAI was originally designed for use by professional care givers in institutional care settings. Alzheimer's dementia, however, is associated with a significant burden on family members, who provide the majority of care, and other informal care partners.

Methods

Our qualitative study aimed to assess the accuracy and applicability of the CMAI according to the needs and perceptions of non-professional care partners. Specifically, we wanted to determine if the behaviors included in the instrument reflect: (a) the care partner's experience with agitation in Alzheimer's dementia patients, (b) how the behaviors and their frequency are related to the perception of agitation severity, and (c) what changes in agitation behaviors are meaningful to care partners. We interviewed 30 care partners for patients with Alzheimer's dementia in the United States.

Results

The care partners confirmed all behaviors listed in the CMAI as relevant. The behaviors reflect a spectrum of severity, with aggressive behaviors considered more severe than non-aggressive behaviors and physical behaviors generally considered more severe than verbal behaviors. Any reduction or increase in the frequency of a behavior was meaningful to care partners. Generally, a change from physical to verbal behaviors and aggressive to non-aggressive was considered a meaningful improvement while a change from verbal to physical and non-aggressive to aggressive was considered a meaningful worsening.

Discussion

The CMAI appropriately captures relevant behaviors of agitation in Alzheimer's dementia and provides insight into the relative improvement or worsening of agitation symptoms.

Care sequences leading to the diagnosis of Alzheimer's disease and related dementias: An analysis of electronic health records

BACKGROUND

We examined the sequences of clinical care leading to diagnoses of Alzheimer's disease and related dementias (ADRD) using electronic health records from a large academic medical center.

METHODS

We included patients aged 65+ with their first ADRD diagnoses from January 1, 2014 to December 31, 2019. Using state sequence analysis, care sequences were defined by the ordering of healthcare utilizations occurred in the 2 years before ADRD diagnosis.

RESULTS

Of 3621 patients (median age 80), nearly half followed a care sequence of having one primary care visit close to their ADRD diagnosis. Additional care sequences included periodic (n = 322, 8.9%) and multiple (n = 416, 11.5%) outpatient visits to primary care and having one (n = 395, 10.9%), multiple (n = 469, 13.0%), or highly frequent (n = 357, 10.7%) outpatient visits to other specialties. Patients' sociodemographic traits contributed to the variability in care sequences.

CONCLUSIONS

Several distinct patterns of care leading to ADRD diagnoses were identified. Integrated care models are needed to promote early identification of ADRD.

HIGHLIGHTS

Dementia patients followed distinct care pathways prior to their dementia diagnoses. Key sociodemographic traits contributed to the variation in the sequences of care. Racial differences in the sequencing of care were also found, but only in women.

A real-world assessment of healthcare costs associated with agitation in Alzheimer's dementia

AIMS

To describe and compare clinical characteristics, healthcare costs, and institutionalization/mortality outcomes among patients with and without agitation associated with Alzheimer's dementia (AAD).

METHODS

Data from the Reliant Medical Group database (01/01/2016-03/31/2020) were used, including claims, electronic medical records, and clinical information/physician notes abstracted from medical charts. Patients aged ≥55 years with Alzheimer's dementia (AD) were observed during a randomly selected 12-month study period after AD diagnosis. Using information recorded in medical charts, patients were classified into cohorts based on experiencing (agitation cohort) and not experiencing (no agitation cohort) agitated behaviours during the study period. Entropy balancing was used to create reweighted cohorts with similar characteristics. Study outcomes (patient demographic and clinical characteristics, treatments received, healthcare costs, institutionalization and death events) were compared between cohorts; agitation characteristics were described for the agitation cohort only.

RESULTS

Among 711 patients included in the study, 240 were classified in the agitation cohort and 471 in the no agitation cohort. After reweighting, several comorbidities were more frequently observed in the agitation versus no agitation cohort, including infection, depression, and altered mental status. Use of antidepressants, anticonvulsants, antipsychotics, and antianxiety medications was more common in the agitation versus no agitation cohort. Common agitated behaviours included hitting (20.8%), pacing/aimless wandering (17.5%), and cursing/verbal aggression (15.0%). Total all-cause healthcare costs were $4287 per-patient-per-year higher in the agitation cohort versus no agitation cohort (p = 0.04), driven by higher inpatient costs. Death was more common and time to death and institutionalization were shorter in the agitation versus no agitation cohort.

LIMITATIONS

Results may not be generalizable to the US population with AD.

CONCLUSIONS

Among patients with AD, agitation was associated with shorter time to death/institutionalization and increased comorbidities, medication use, and healthcare costs, highlighting the additional clinical and economic burden that agitation poses to patients and the healthcare system.

A Confirmatory and an Exploratory Factor Analysis of the Cohen-Mansfield Agitation Inventory (CMAI) in a European Case Series of Patients with Dementia: Results from the RECage Study

BACKGROUND

One of the most widely used instruments for assessing agitation in dementia patients is the Cohen-Mansfield Agitation Inventory (CMAI), nevertheless no global score has been proposed. The aim of this study is: (a) to conduct a confirmatory (CFA) and exploratory factor analysis (EFA) of CMAI on people with dementia and Psychological and Behavioral Symptoms (BPSD), and (b) to propose an alternative structure, based on clinical criteria including all CMAI items.

METHODS

Confirmatory and exploratory factor analyses were carried out on the CMAI 29 items administered at baseline to 505 patients with dementia (PwD) and BPSD enrolled in the international observational RECage study.

RESULTS

The three-factor structure has not been confirmed by the CFA, whilst the EFA was carried out respectively on 25 items disregarding 4 items with a prevalence ≤5% and then on 20 items disregarding 9 items with a prevalence ≤10%. The four-factor structure explaining 56% of the variance comprised Physically Aggressive behavior, Verbally Aggressive behavior, Physically non-aggressive behavior, and Physically and verbally aggressive behavior.

CONCLUSIONS

A new grouping of all items according to a clinical criterion is proposed, allowing for a more sensible evaluation of the symptoms leading to better differentiation.

Characterizing PRN Use of Psychotropic Medications for Acute Agitation in Canadian Long-Term Care Residents with Dementia Before and During COVID-19

Background

Agitation is a disabling neuropsychiatric symptom of dementia. Pro re nata (PRN) injections of psychotropics can be administered for severe acute agitation, but little is known about the frequency of their actual use.

Objective

Characterize actual use of injectable PRN psychotropics for severe acute agitation in Canadian long-term care (LTC) residents with dementia and compare use before and during the COVID-19 pandemic.

Methods

Residents from two Canadian LTC facilities with orders for PRN haloperidol, olanzapine, or lorazepam between January 1, 2018- May 1, 2019 (i.e., pre-COVID-19) and January 1, 2020- May 1, 2021 (i.e., COVID-19) were identified. Electronic medical records were reviewed to document PRN injections of psychotropic medications and collect data on reason and demographic characteristics. Descriptive statistics were used to characterize frequency, dose, and indications of use, and multivariate regression models were used to compare use between time periods.

Results

Of the 250 residents, 45 of 103 (44%) people in the pre-COVID-19 period and 85 of 147 (58%) people in the COVID-19 period with standing orders for PRN psychotropics received ≥1 injections. Haloperidol was the most frequently used agent in both time periods (74% (155/209 injections) pre-COVID-19; 81% (323/398 injections) during COVID-19). Residents in the COVID-19 period were almost two times more likely to receive injections compared with those in the pre-COVID-19 period (odds ratio = 1.96; 95% CI = 1.15-3.34; p = 0.01).

Conclusion

Our results suggest that use of PRN injections increased in LTC during the pandemic and contribute to the mounting evidence that agitation worsened during that time.

The reporting of neuropsychiatric symptoms in electronic health records of individuals with Alzheimer's disease: a natural language processing study

BACKGROUND

Neuropsychiatric symptoms (NPS) are prevalent in the early clinical stages of Alzheimer's disease (AD) according to proxy-based instruments. Little is known about which NPS clinicians report and whether their judgment aligns with proxy-based instruments. We used natural language processing (NLP) to classify NPS in electronic health records (EHRs) to estimate the reporting of NPS in symptomatic AD at the memory clinic according to clinicians. Next, we compared NPS as reported in EHRs and NPS reported by caregivers on the Neuropsychiatric Inventory (NPI).

METHODS

Two academic memory clinic cohorts were used: the Amsterdam UMC (n = 3001) and the Erasmus MC (n = 646). Patients included in these cohorts had MCI, AD dementia, or mixed AD/VaD dementia. Ten trained clinicians annotated 13 types of NPS in a randomly selected training set of n = 500 EHRs from the Amsterdam UMC cohort and in a test set of n = 250 EHRs from the Erasmus MC cohort. For each NPS, a generalized linear classifier was trained and internally and externally validated. Prevalence estimates of NPS were adjusted for the imperfect sensitivity and specificity of each classifier. Intra-individual comparison of the NPS classified in EHRs and NPS reported on the NPI were conducted in a subsample (59%).

RESULTS

Internal validation performance of the classifiers was excellent (AUC range: 0.81-0.91), but external validation performance decreased (AUC range: 0.51-0.93). NPS were prevalent in EHRs from the Amsterdam UMC, especially apathy (adjusted prevalence = 69.4%), anxiety (adjusted prevalence = 53.7%), aberrant motor behavior (adjusted prevalence = 47.5%), irritability (adjusted prevalence = 42.6%), and depression (adjusted prevalence = 38.5%). The ranking of NPS was similar for EHRs from the Erasmus MC, although not all classifiers obtained valid prevalence estimates due to low specificity. In both cohorts, there was minimal agreement between NPS classified in the EHRs and NPS reported on the NPI (all kappa coefficients < 0.28), with substantially more reports of NPS in EHRs than on NPI assessments.

CONCLUSIONS

NLP classifiers performed well in detecting a wide range of NPS in EHRs of patients with symptomatic AD visiting the memory clinic and showed that clinicians frequently reported NPS in these EHRs. Clinicians generally reported more NPS in EHRs than caregivers reported on the NPI.

Cholinergic Antagonists and Behavioral Disturbances in Neurodegenerative Diseases

Cholinergic antagonists interfere with synaptic transmission in the central nervous system and are involved in pathological processes in patients with neurocognitive disorders (NCD), such as behavioral and psychological symptoms of dementia (BPSD). In this commentary, we will briefly review the current knowledge on the impact of cholinergic burden on BPSD in persons with NCD, including the main pathophysiological mechanisms. Given the lack of clear consensus regarding symptomatic management of BPSD, special attention must be paid to this preventable, iatrogenic condition in patients with NCD, and de-prescription of cholinergic antagonists should be considered in patients with BPSD.

A 2023 update on the advancements in the treatment of agitation in Alzheimer's disease

INTRODUCTION

Neuropsychiatric symptoms (NPS) in Alzheimer's Disease (AD) are associated with negative outcomes for patients and their care partners. Agitation is one of the most common and distressing NPS, yet we lack safe and effective treatment options. While nonpharmacologic interventions are considered first line treatment, these may not be effective or appropriate for every patient. Our current approaches to the pharmacologic treatment of agitation in AD consist of the off-label use of antipsychotics, sedative/hypnotics, anxiolytics, mood-stabilizing anticonvulsants, acetylcholinesterase inhibitors, NMDA receptor antagonists, and antidepressants. Despite their prevalent use, they have questionable efficacy and significant safety concerns.

AREAS COVERED

Advances in the understanding of neurobiological mechanisms of agitation have fueled recent clinical trials. This article is an update to our 2017 review. A comprehensive search of ClinicalTrials.gov was completed from January 2017 to June 2022 using the search terms "Alzheimer's Disease" and "Agitation". A subsequent scoping review was completed in PubMed and Google Scholar. Several agents were identified for promise in treating agitation, including: brexpiprazole, cannabinoids, dexmedetomidine, dextromethorphan, escitalopram, masupirdine, and prazosin.

EXPERT OPINION

Clinical trials remain underway utilizing both novel and repurposed agents to address symptoms of agitation in AD. With increasing understanding of the neurobiological mechanisms that fuel the development of agitation in AD, the use of enhanced trial design and conduct, advanced statistical approaches, and accelerated pathways for regulatory approval, we are advancing closer to having safe and efficacious treatment options for agitation in AD.

Can Patients with Dementia Be Identified in Primary Care Electronic Medical Records Using Natural Language Processing?

Dementia and mild cognitive impairment can be underrecognized in primary care practice and research. Free-text fields in electronic medical records (EMRs) are a rich source of information which might support increased detection and enable a better understanding of populations at risk of dementia. We used natural language processing (NLP) to identify dementia-related features in EMRs and compared the performance of supervised machine learning models to classify patients with dementia. We assembled a cohort of primary care patients aged 66 + years in Ontario, Canada, from EMR notes collected until December 2016: 526 with dementia and 44,148 without dementia. We identified dementia-related features by applying published lists, clinician input, and NLP with word embeddings to free-text progress and consult notes and organized features into thematic groups. Using machine learning models, we compared the performance of features to detect dementia, overall and during time periods relative to dementia case ascertainment in health administrative databases. Over 900 dementia-related features were identified and grouped into eight themes (including symptoms, social, function, cognition). Using notes from all time periods, LASSO had the best performance (F1 score: 77.2%, sensitivity: 71.5%, specificity: 99.8%). Model performance was poor when notes written before case ascertainment were included (F1 score: 14.4%, sensitivity: 8.3%, specificity 99.9%) but improved as later notes were added. While similar models may eventually improve recognition of cognitive issues and dementia in primary care EMRs, our findings suggest that further research is needed to identify which additional EMR components might be useful to promote early detection of dementia.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41666-023-00125-6.

Assess the documentation of cognitive tests and biomarkers in electronic health records via natural language processing for Alzheimer's disease and related dementias

BACKGROUND

Cognitive tests and biomarkers are the key information to assess the severity and track the progression of Alzheimer's' disease (AD) and AD-related dementias (AD/ADRD), yet, both are often only documented in clinical narratives of patients' electronic health records (EHRs). In this work, we aim to (1) assess the documentation of cognitive tests and biomarkers in EHRs that can be used as real-world endpoints, and (2) identify, extract, and harmonize the different commonly used cognitive tests from clinical narratives using natural language processing (NLP) methods into categorical AD/ADRD severity.

METHODS

We developed a rule-based NLP pipeline to extract the cognitive tests and biomarkers from clinical narratives in AD/ADRD patients' EHRs. We aggregated the extracted results to the patient level and harmonized the cognitive test scores into severity categories using cutoffs determined based on both relevant literature and domain knowledge of AD/ADRD clinicians.

RESULTS

We identified an AD/ADRD cohort of 48,912 patients from the University of Florida (UF) Health system and identified 7 measurements (6 cognitive tests and 1 biomarker) that are frequently documented in our data. Our NLP pipeline achieved an overall F1-score of 0.9059 across the 7 measurements. Among the 6 cognitive tests, we were able to harmonize 4 cognitive test scores into severity categories, and the population characteristics of patients with different severity were described. We also identified several factors related to the availability of their documentation in EHRs.

CONCLUSION

This study demonstrates that our NLP pipelines can extract cognitive tests and biomarkers of AD/ADRD accurately for downstream studies. Although, the documentation of cognitive tests and biomarkers in EHRs appears to be low, RWD is still an important resource for AD/ADRD research. Nevertheless, providing standardized approach to document cognitive tests and biomarkers in EHRS are also warranted.

Dementia-related agitation: a 6-year nationwide characterization and analysis of hospitalization outcomes

OBJECTIVES

To characterize all hospitalizations held in mainland Portugal (2010-2015) with dementia-related agitation based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) coding, and to investigate whether there is a relationship between agitation and hospitalization outcomes.

METHODS

A retrospective observational study was conducted using an administrative dataset containing data from all mainland Portuguese public hospitals. Only hospitalization episodes for patients aged over 65 years who have received a dementia diagnosis ascertained by an ICD-9-CM code of dementia with behavioral disturbance (294.11 and 294.21) and dementia without behavioral disturbance (294.10 and 294.20) were selected. Episodes were further grouped according to the presence of an agitation code. For each episode, demographic data and hospitalization outcomes, including length of stay (LoS), in-hospital mortality, discharge destination and all-cause hospital readmissions, were sourced from the dataset. Comparative analyses were performed and multivariable logistic methods were used to estimate the adjusted associations between agitation (exposure) and outcomes.

RESULTS

Overall, 53,156 episodes were selected, of which 6,586 had an agitation code. These were mostly related to male, younger inpatients (mean 81.19 vs. 83.29 years, p < 0.001), had a higher comorbidity burden, stayed longer at the hospital (median 9.00 vs. 8.00 days, p < 0.001) and frequently ended being transferred to another facility with inpatient care. Agitation was shown to independently increase LoS (aOR = 1.385; 95%CI:1.314-1.461), but not the risk of a fatal outcome (aOR = 0.648; 95%CI:0.600-0.700).

CONCLUSION

These results support the importance of detecting and managing agitation early on admission, since its prompt management may prevent lengthy disruptive hospitalizations.

Promising candidates from drug clinical trials: Implications for clinical treatment of Alzheimer's disease in China

Alzheimer's disease is the most common neurodegenerative disease. Prior to 2017, National Medical Products Administration approved only four drugs to treat Alzheimer's disease, including three cholinesterase inhibitors and one N-methyl-D-aspartate receptor antagonist. We queried ClinicalTrials.gov to better understand Alzheimer's drug development over the past 5 years and found 16 promising candidates that have entered late-stage trials and analyzed their impact on clinical treatment of Alzheimer's disease in China. The 16 compounds selected include disease-modifying therapies and symptomatic therapies. The research and development pipeline now focuses on disease-modifying therapies such as gantenerumab, aducanumab, ALZ-801, ALZT-OP1, donanemab, lecanemab, simufilam, NE3107, semaglutide, and GV-971, which could put an end to the situation where Alzheimer's patients in China have no effective treatment alternatives. The reuse of drugs or combinations currently under investigation for the psychiatric treatment of Alzheimer's disease, including AXS-05, AVP-786, nabilone, brexpiprazole, methylphenidate, and pimavanserin, could provide physicians with additional treatment options. Although most of these drugs have not been explored in China yet, due to the current development trend in this field in China, it is expected that China will be involved in research on these drugs in the future.

Neighborhood characteristics and dementia symptomology among community-dwelling older adults with Alzheimer's disease

Background

Neuropsychiatric symptoms (NPSs) lead to myriad poor health outcomes among individuals with Alzheimer's disease (AD). Prior studies have observed associations between the various aspects of the home environment and NPSs, but macro-level environmental stressors (e.g., neighborhood income) may also disrupt the neuronal microenvironment and exacerbate NPSs. Yet, to our knowledge, no studies have investigated the relationship between the neighborhood environment and NPSs.

Methods

Using 2010 data among older adults with AD collected from a sample of the South Carolina Alzheimer's Disease Registry, we estimated cross-sectional associations between neighborhood characteristics and NPSs in the overall population and by race/ethnicity. Neighborhood measures (within a 1/2-mile radius of residence) came from the American Community Survey and Rural Urban Commuting Area Code. We categorized median household income into tertiles: < $30,500, $30,500-40,000, and > $40,000, and rurality as: rural, small urban, and large urban. Residential instability was defined as the percent of residents who moved within the past year. NPSs were defined using the Neuropsychiatric Inventory Questionnaire that included the composite measure of all 12 domains. Adjusting for age, sex/gender, race/ethnicity, and caregiver educational attainment, we used negative binomial regression to estimate prevalence ratios (PR) and 95% confidence intervals (CI) for NPSs by neighborhood characteristics.

Results

Among 212 eligible participants, mean age was 82 ± 8.7 years, 72% were women, and 55% non-Hispanic (NH)-Black. Individuals with AD living in < $30,500 vs. > $40,000 income neighborhoods had a 53% (PR = 1.53; 95% CI = 1.06-2.23) higher prevalence of NPSs while individuals living in rural vs. large urban neighborhoods had a 36% lower prevalence of NPSs (PR = 0.64; 95% CI = 0.45-0.90), after adjustment. We did not observe an association between residential instability and NPSs (PR = 0.92; 95% CI = 0.86-1.00); however, our estimates suggested differences by race/ethnicity where NH-White older adults living in residential instable areas had lower NPSs (PR = 0.89; 95% CI = 0.82-0.96) compared to NH-Black older adults (PR = 0.96; 95% CI = 0.86-1.07).

Discussion

Across racial/ethnic groups, individuals with AD had more symptomology when living in lower income areas. Pending replication, intervention efforts should consider resource allocation to high-need neighborhoods (e.g., lower income), and studies should investigate underlying mechanisms for this relationship.

Sensory-based interventions for the immediate de-escalation of agitation in people with dementia: A systematic review

Objectives: Sensory-based interventions are commonly used to reduce the occurrence of agitation in people with dementia over extended periods. However, the evidence regarding their immediate de-escalation effects is unclear. The objectives of this systematic review are to (a) identify which sensory-based interventions have been used for de-escalating agitation and (b) examine the immediate effects of these interventions on de-escalating agitation in people with dementia.Methods: A systematic review was performed in accordance with PRISMA guidelines. Data sources were identified by searching Embase, Medline, PsycINFO, and CINAHL for publications up to 2 March 2022. The de-escalating agitation effect had to be measured during the intervention or within 15 min after commencing the treatment. Only randomized controlled trials or quasi-experimental studies published in English were included.Results: Nine studies met the inclusion criteria: two randomized controlled trials, one cross-over study, and six quasi-experimental studies. All were conducted in Western countries, involving a total of 246 participants. Music-related interventions were investigated in seven studies, and a positive effect on de-escalating agitation was found, with no side-effects. All of the studies had methodological limitations, including a single group design, blinding, an insufficient sample size, and imprecisely reported results.Conclusion: There is a profound dearth of rigorous studies examining the immediate agitation de-escalating effects of sensory-based interventions on people with dementia. However, the limited evidence on music-related interventions is encouraging. More rigorous research is recommended to confirm the effects.

Simulated Electroconvulsive Therapy: A Novel Approach to a Control Group in Clinical Trials

OBJECTIVES

Agitation is the most common behavioral symptom of Alzheimer disease (AD) affecting approximately 40% to 60% of the AD population, yet there are no Food and Drug Administration-approved therapies for the myriad of behavioral or psychological symptoms of dementia. There is growing evidence from naturalistic studies that electroconvulsive therapy (ECT) is a safe and effective treatment for agitation in AD patients who are refractory to pharmacotherapy and behavioral interventions. Despite the existing evidence, ECT remains underused because of stigma, lack of education, and concerns regarding adverse cognitive effects. Randomized controlled clinical trials of ECT are an opportunity to provide high-quality evidence of ECT as a safe and efficacious treatment for agitation in the AD population. We describe the methods for the Electroconvulsive Therapy in Alzheimer's Dementia study, which uses a novel, simulated ECT (S-ECT) control group to conduct a single-blind efficacy study of ECT for the treatment of agitation and aggression in individuals with moderate to severe AD.

METHODS

We discuss the rationale, study design, methodology, ethical and practical challenges, and management strategies in using an S-ECT group as the comparator arm in this randomized controlled trial of ECT in AD-related treatment refractory agitation and aggression.

CONCLUSIONS

Validation of the safety and efficacy of ECT in patients with advanced AD with refractory agitation and aggression is necessary. This can be accomplished through creative formulation of S-ECT groups that effectively maintain the blind while providing scientific integrity.

Longitudinal assessment of aggression and circadian rhythms in the APPswe mouse model of Alzheimer`s disease

Agitation, which comprises verbal or physical aggression and hyperactivity, is one of the most frequent neuropsychiatric symptoms observed in patients with Alzheimer's disease (AD). It often co-occurs with dysregulated circadian rhythms. Current medications are associated with serious adverse effects, and novel therapeutics are therefore needed. Rodent models can be instrumental to provide a first signal for potential efficacy of novel drug candidates. Longitudinal data assessing the face validity of such models for AD-related agitation are largely missing. We employed telemeterized APPswe mice, a frequently used AD transgenic mouse line overexpressing the human beta-amyloid precursor protein (APP) with the Swedish KM670/671NL mutation, to study the occurrence and progression of changes in reactive aggressive behavior as well as the circadian profile of locomotor activity and body temperature. Analysis was conducted between 5 and 11 months of age, at regular 2-months intervals. The aggressivity of all mice was highest at 5 months and waned with increasing age. APPswe mice were more aggressive than WT at 5 and 7 months of age. The locomotor activity and body temperature of WT mice declined with increasing age, while that of APPswe mice remained rather constant. This genotype difference was solely evident during the active, dark phase. APPswe mice did not display a phase shift of their circadian rhythms. We conclude that the APPswe mouse line can recapitulate some of the behavioral disturbances observed in AD, including an agitation-relevant phenotype characterized by active phase hyperactivity and aggressivity. It does not recapitulate the nighttime disturbances (also characterized by hyperactivity) and the shift of circadian rhythms observed in AD patients. Therefore, the APPswe strain could be used at specific ages to model a subset of agitation-relevant behavioral problems and to test the modulatory effects of drugs.

Agitation Prevalence in People With Dementia in Australian Residential Aged Care Facilities: Findings From Machine Learning of Electronic Health Records

Using a suite of artificial intelligence technologies, the current study sought to determine the prevalence of agitated behaviors in people with dementia in residential aged care facilities (RACFs) in Australia. Computerized natural language processing allowed extraction of agitation instances from the free-text nursing progress notes, a component of electronic health records in RACFs. In total, 59 observable agitated behaviors were found. No difference was found in dementia prevalence between female and male clients (44.1%), across metropolitan and regional facilities (42.1% [SD = 17.9%]), or for agitation prevalence in dementia (76.5% [SD = 18.4%]). The top 10 behaviors were resisting, wandering, speaking in excessively loud voice, pacing, restlessness, pushing, shouting, complaining, frustration, and using profane language. Four to 17 agitated behaviors coexisted in 53% of people with dementia agitation, indicating high caregiver burden in these RACFs. Improving workforce training and redesigning care models are urgent for sustainability of dementia care in RACFs. [Journal of Gerontological Nursing, 48(4), 57-64.].

No benefit from mirtazapine for treating agitation in dementia

Review of: Banerjee S, High J, Stirling S, et al Study of mirtazapine for agitated behaviours in dementia (SYMBAD): a randomised, double-blind, placebo-controlled trial. Lancet 2021;398:1487-97.

Cognitive Function Characterization Using Electronic Health Records Notes

Cognitive impairment is a defining feature of neurological disorders such as Alzheimer's disease (AD), one of the leading causes of disability and mortality in the elderly population. Assessing cognitive impairment is important for diagnostic, clinical management, and research purposes. The Folstein Mini-Mental State Examination (MMSE) is the most common screening measure of cognitive function, yet this score is not consistently available in the electronic health records. We conducted a pilot study to extract frequently used concepts characterizing cognitive function from the clinical notes of AD patients in an Aging and Dementia clinical practice. Then we developed a model to infer the severity of cognitive impairment and created a subspecialized taxonomy for concepts associated with MMSE scores. We evaluated the taxonomy and the severity prediction model and presented example use cases of this model.

Use of Real-World Evidence to Drive Drug Development Strategy and Inform Clinical Trial Design

Interest in real-world data (RWD) and real-world evidence (RWE) to expedite and enrich the development of new biopharmaceutical products has proliferated in recent years, spurred by the 21st Century Cures Act in the United States and similar policy efforts in other countries, willingness by regulators to consider RWE in their decisions, demands from third-party payers, and growing concerns about the limitations of traditional clinical trials. Although much of the recent literature on RWE has focused on potential regulatory uses (e.g., product approvals in oncology or rare diseases based on single-arm trials with external control arms), this article reviews how biopharmaceutical companies can leverage RWE to inform internal decisions made throughout the product development process. Specifically, this article will review use of RWD to guide pipeline and portfolio strategy; use of novel sources of RWD to inform product development, use of RWD to inform clinical development, use of advanced analytics to harness "big" RWD, and considerations when using RWD to inform internal decisions. Topics discussed will include the use of molecular, clinicogenomic, medical imaging, radiomic, and patient-derived xenograft data to augment traditional sources of RWE, the use of RWD to inform clinical trial eligibility criteria, enrich trial population based on predicted response, select endpoints, estimate sample size, understand disease progression, and enhance diversity of participants, the growing use of data tokenization and advanced analytical techniques based on artificial intelligence in RWE, as well as the importance of data quality and methodological transparency in RWE.

Wrist accelerometry for monitoring dementia agitation behaviour in clinical settings: A scoping review

Agitated behaviour among elderly people with dementia is a challenge in clinical management. Wrist accelerometry could be a versatile tool for making objective, quantitative, and long-term assessments. The objective of this review was to summarise the clinical application of wrist accelerometry to agitation assessments and ways of analysing the data. Two authors independently searched the electronic databases CINAHL, PubMed, PsycInfo, EMBASE, and Web of Science. Nine (n = 9) articles were eligible for a review. Our review found a significant association between the activity levels (frequency and entropy) measured by accelerometers and the benchmark instrument of agitated behaviour. However, the performance of wrist accelerometry in identifying the occurrence of agitation episodes was unsatisfactory. Elderly people with dementia have also been monitored in existing studies by investigating the at-risk time for their agitation episodes (daytime and evening). Consideration may be given in future studies on wrist accelerometry to unifying the parameters of interest and the cut-off and measurement periods, and to using a sampling window to standardise the protocol for assessing agitated behaviour through wrist accelerometry.

Investigation of the effects of interventions made according to the Progressively Lowered Stress Threshold Model on the care outcomes of Alzheimer patients and their families: a randomized clinical trial

BACKGROUND

One of the non-pharmacological methods used to reduce behavioural problems of Alzheimer's patients and the negative emotions accordingly experienced by caregivers consists of interventions performed according to the Progressively Lowered Stress Threshold (PLST) model.

METHODS

This randomized controlled study aimed to determine the effect of interventions performed according to PLST on the care burden, care satisfaction, and life satisfaction of caregivers of middle and advanced stage Alzheimer's disease patients, and on the neuropsychiatric symptoms and agitation levels of these patients. The research was conducted with a total of 29 caregivers divided into intervention (15) and control (14) groups. Data were collected using an Introductory Information Form, plus the Standardised Mini-Mental State Examination, Neuropsychiatric Inventory, Cohen-Mansfield Agitation Inventory, Carer's Assessment of Satisfaction Index, and Life Satisfaction Scale. Three home visits were made to the caregivers by the researchers in the first, second, and twelfth weeks of the intervention. During the home visits, face-to-face training was given as necessary to the individual caring for problems identified in the nursing care plan according to PLST.

RESULTS

As a result of the PLST training, there was a decrease in the behavioural problems of Alzheimer's patients, along with a decrease in the care burden of the caregivers and an increase in their care satisfaction. When the scale total scores of the individuals in the intervention and control groups were compared, it was found that only caregivers' care satisfaction increased at a statistically significant level (P < 0.05).

CONCLUSION

At the end of the training given according to PLST, it was found that behavioural problems of Alzheimer's patients and the care burden of caregivers had decreased, and the care satisfaction of caregivers increased. It is recommended that Alzheimer's patients and their caregivers be given training and interventions according to PLST.

Association Between Patient Survival and Clinician Variability in Treatment Rates for Aortic Valve Stenosis

Background Patients with symptomatic severe aortic stenosis (ssAS) have a high mortality risk and compromised quality of life. Surgical/transcatheter aortic valve replacement (AVR) is a Class I recommendation, but it is unclear if this recommendation is uniformly applied. We determined the impact of managing cardiologists on the likelihood of ssAS treatment. Methods and Results Using natural language processing of Optum electronic health records, we identified 26 438 patients with newly diagnosed ssAS (2011-2016). Multilevel, multivariable Fine-Gray competing risk models clustered by cardiologists were used to determine the impact of cardiologists on the likelihood of 1-year AVR treatment. Within 1 year of diagnosis, 35.6% of patients with ssAS received an AVR; however, rates varied widely among managing cardiologists (0%, lowest quartile; 100%, highest quartile [median, 29.6%; 25th-75th percentiles, 13.3%-47.0%]). The odds of receiving AVR varied >2-fold depending on the cardiologist (median odds ratio for AVR, 2.25; 95% CI, 2.14-2.36). Compared with patients with ssAS of cardiologists with the highest treatment rates, those treated by cardiologists with the lowest AVR rates experienced significantly higher 1-year mortality (lowest quartile, adjusted hazard ratio, 1.22, 95% CI, 1.13-1.33). Conclusions Overall AVR rates for ssAS were low, highlighting a potential challenge for ssAS management in the United States. Cardiologist AVR use varied substantially; patients treated by cardiologists with lower AVR rates had higher mortality rates than those treated by cardiologists with higher AVR rates.

Sex disparities in patients with symptomatic severe aortic stenosis

BACKGROUND

We evaluated whether there is equitable distribution across sexes of treatment and outcomes for aortic valve replacement (AVR), via surgical (SAVR) or transcatheter (TAVR) methods, in symptomatic severe aortic stenosis (ssAS) patients.

METHODS

Using de-identified data, we identified 43,822 patients with ssAS (2008-2016). Multivariate competing risk models were used to determine the likelihood of any AVR, while accounting for the competing risk of death. Association between sex and 1-year mortality, stratified by AVR status, was evaluated using multivariate Cox regression models with AVR as a time-dependent variable.

RESULTS

Among patients with ssAS, 20,986 (47.9%) were female. Females were older (median age 81 vs. 78, P<0.001), more likely to have body mass index <20 (8.5% vs. 3.5%), and home oxygen use (4.4% vs. 3.4%, P<0001 for all). Overall, 12,129 (27.7%) patients underwent AVR for ssAS. Females were less likely to undergo AVR compared with males (24.1% vs. 31.0%, adjusted hazard ratio [HR] 0.80, 95% confidence interval [CI] 0.77-0.83), but when treated, were more likely to undergo TAVR (37.9% vs. 30.9%, adjusted HR 1.21, 95% CI 1.15-1.27). Untreated females and males had similarly high rates of mortality at 1 year (31.1% vs. 31.3%, adjusted HR 0.98, 95% CI 0.94-1.03). Among those undergoing AVR, females had significantly higher mortality (10.2% vs. 9.4%, adjusted HR 1.24, 95% CI 1.10-1.41), driven by increased SAVR-associated mortality (9.0% vs. 7.6%, adjusted HR 1.43, 95% CI 1.21-1.69).

CONCLUSIONS

Treatment rates for ssAS patients remain suboptimal with disparities in female treatment.

Navigating the Cancer Screening Decision for Patients with Dementia

PURPOSE OF REVIEW

The risks of developing cancer and dementia both increase with age, giving rise to the complex question of whether continued cancer screening for older dementia patients is appropriate. This paper offers a practice-based clinical approach to determine an answer to this challenging question.

RECENT FINDINGS

There is no consensus on the prevalence of cancer and dementia as co-diagnoses. Persons with dementia are screened less often compared to those without dementia. There is significant literature focusing on screening in the geriatric population, but there is little evidence to support decision-making for screening for older patients with dementia. Given this lack of evidence, individualized decisions should be made in collaboration with patients and family caregivers. Four considerations to help guide this process include prognosis, behavioral constraints, cognitive capacity, and goals for care. Future research will be challenging due to variability of factors that inform screening decisions and the vulnerable nature of this patient population.

The application of an information support robot to reduce agitation in an older adult with Alzheimer's disease living alone in a community dwelling: a case study

OBJECTIVE/BACKGROUND

Agitation is a common behaviour of Alzheimer's Disease (AD). Although healing robots have previously been used for alleviating agitation for people with dementia in hospitals and other healthcare facilities, its effects remain unclear whether an information-support robot capable of disseminating information with user needs may have similar effects when it is applied in community dwellings. This study was to investigate the effects of information-support robots for reducing agitation in older people with AD residing alone in community-dwellings.

METHODS

One participant with AD who lived alone in a community-dwelling was recruited. Participant's frequencies, durations, and time courses of four patterns of agitation at home at baseline and during intervention were analysed. In this study, agitation was defined as: (a) restlessness going to the corridor (RLtoC), (b) restlessness going to the toilet (RLtoT), (c) restlessness going to the entrance (RLtoE), and (d) restlessness going to multiple places (RLtoMP). In the intervention phase, the information-support robot disseminated daily schedule or date information to the participant.

RESULTS

RLtoC and RLtoMP were significantly reduced in frequency during the intervention. The durations of each episode of RLtoT and RLtoMP in the intervention were slightly reduced than those at the baseline. There were no differences in time courses of episodes of RLtoC and RLtoMP after the intervention.

CONCLUSION

This case study showed that information-support robot was useful to alleviate agitation of an older adult with AD living alone in a community-dwelling. Further study is warranted.

Alzheimer's disease

In this Seminar, we highlight the main developments in the field of Alzheimer's disease. The most recent data indicate that, by 2050, the prevalence of dementia will double in Europe and triple worldwide, and that estimate is 3 times higher when based on a biological (rather than clinical) definition of Alzheimer's disease. The earliest phase of Alzheimer's disease (cellular phase) happens in parallel with accumulating amyloid β, inducing the spread of tau pathology. The risk of Alzheimer's disease is 60-80% dependent on heritable factors, with more than 40 Alzheimer's disease-associated genetic risk loci already identified, of which the APOE alleles have the strongest association with the disease. Novel biomarkers include PET scans and plasma assays for amyloid β and phosphorylated tau, which show great promise for clinical and research use. Multidomain lifestyle-based prevention trials suggest cognitive benefits in participants with increased risk of dementia. Lifestyle factors do not directly affect Alzheimer's disease pathology, but can still contribute to a positive outcome in individuals with Alzheimer's disease. Promising pharmacological treatments are poised at advanced stages of clinical trials and include anti-amyloid β, anti-tau, and anti-inflammatory strategies.

Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review

Background

Electronic medical records (EMRs) contain large amounts of rich clinical information. Developing EMR-based case definitions, also known as EMR phenotyping, is an active area of research that has implications for epidemiology, clinical care, and health services research.

Objective

This review aims to describe and assess the present landscape of EMR-based case phenotyping for the Charlson conditions.

Methods

A scoping review of EMR-based algorithms for defining the Charlson comorbidity index conditions was completed. This study covered articles published between January 2000 and April 2020, both inclusive. Embase (Excerpta Medica database) and MEDLINE (Medical Literature Analysis and Retrieval System Online) were searched using keywords developed in the following 3 domains: terms related to EMR, terms related to case finding, and disease-specific terms. The manuscript follows the Preferred Reporting Items for Systematic reviews and Meta-analyses extension for Scoping Reviews (PRISMA) guidelines.

Results

A total of 274 articles representing 299 algorithms were assessed and summarized. Most studies were undertaken in the United States (181/299, 60.5%), followed by the United Kingdom (42/299, 14.0%) and Canada (15/299, 5.0%). These algorithms were mostly developed either in primary care (103/299, 34.4%) or inpatient (168/299, 56.2%) settings. Diabetes, congestive heart failure, myocardial infarction, and rheumatology had the highest number of developed algorithms. Data-driven and clinical rule–based approaches have been identified. EMR-based phenotype and algorithm development reflect the data access allowed by respective health systems, and algorithms vary in their performance.

Conclusions

Recognizing similarities and differences in health systems, data collection strategies, extraction, data release protocols, and existing clinical pathways is critical to algorithm development strategies. Several strategies to assist with phenotype-based case definitions have been proposed.

Distribution of agitation and related symptoms among hospitalized patients using a scalable natural language processing method

BACKGROUND

Agitation is a common feature of many neuropsychiatric disorders.

OBJECTIVE

Understanding the prevalence, implications, and characteristics of agitation among hospitalized populations can facilitate more precise recognition of disability arising from neuropsychiatric diseases.

METHODS

We developed two agitation phenotypes using an expansion of expert curated term lists. These phenotypes were used to characterize five years of psychiatric admissions. The relationship of agitation symptoms and length of stay was examined.

RESULTS

Among 4548 psychiatric admissions, 1134 (24.9%) included documentation of agitation based on the primary agitation phenotype. These symptoms were greater among individuals with public insurance, and those with mania and psychosis compared to major depressive disorder. Greater symptoms were associated with longer hospital stay, with ~0.9 day increase in stay for every 10% increase in agitation phenotype.

CONCLUSION

Agitation was common at hospital admission and associated with diagnosis and longer length of stay. Characterizing agitation-related symptoms through natural language processing may provide new tools for understanding agitated behaviors and their relationship to delirium.

Evaluation of the neuroprotective effect of taurine in Alzheimer's disease using functional molecular imaging

Alzheimer's disease (AD) is a chronic neurodegenerative disorder and the leading cause of dementia, but therapeutic treatment options are limited. Taurine has been reported to have neuroprotective properties against dementia, including AD. The present study aimed to investigate the treatment effect of taurine in AD mice by functional molecular imaging. To elucidate glutamate alterations by taurine, taurine was administered to 5xFAD transgenic mice from 2 months of age, known to apear amyloid deposition. Then, we performed glutamate positron emission tomography (PET) imaging studies for three groups (wild-type, AD, and taurine-treated AD, n = 5 in each group). As a result, brain uptake in the taurine-treated AD group was 31-40% higher than that in the AD group (cortex: 40%, p < 0.05; striatum: 32%, p < 0.01; hippocampus: 36%, p < 0.01; thalamus: 31%, p > 0.05) and 3-14% lower than that in the WT group (cortex: 10%, p > 0.05; striatum: 15%, p > 0.05; hippocampus: 14%, p > 0.05; thalamus: 3%, p > 0.05). However, we did not observe differences in Aβ pathology between the taurine-treated AD and AD groups in immunohistochemistry experiments. Our results reveal that although taurine treatment did not completely recover the glutamate system, it significantly increased metabolic glutamate receptor type 5 brain uptake. Therefore, taurine has therapeutic potential against AD.

Racial Differences in the Use of Aortic Valve Replacement for Treatment of Symptomatic Severe Aortic Valve Stenosis in the Transcatheter Aortic Valve Replacement Era

Background Aortic valve replacement (AVR) is a life-saving treatment for patients with symptomatic severe aortic valve stenosis. We sought to determine whether transcatheter AVR has resulted in a more equitable treatment rate by race in the United States. Methods and Results A total of 32 853 patients with symptomatic severe aortic valve stenosis were retrospectively identified via Optum's deidentified electronic health records database (2007-2017). AVR rates in non-Hispanic Black and White patients were assessed in the year after diagnosis. Multivariate Fine-Gray hazards models were used to evaluate the likelihood of AVR by race, with adjustment for patient factors and the managing cardiologist. Time-trend and 1-year symptomatic severe aortic valve stenosis survival analyses were also performed. From 2011 to 2016, the rate of AVR increased from 20.1% to 37.1%. Overall, Black individuals were less likely than Whites to receive AVR (22.9% versus 31.0%; unadjusted hazard ratio [HR], 0.70; 95% CI, 0.62-0.79; fully adjusted HR, 0.76; 95% CI, 0.67-0.85). Yet, during 2015 to 2016, AVR racial differences were attenuated (29.5% versus 35.2%; adjusted HR, 0.86; 95% CI, 0.74-1.02) because of greater uptake of transcatheter AVR in Blacks than Whites (53.4% of AVRs versus 47.3%; P=0.128). Untreated patients had significantly higher 1-year mortality than those treated (adjusted HR, 0.57; 95% CI, 0.53-0.61), which was consistent by race (interaction P value=0.52). Conclusions Although transcatheter AVR has increased the use of AVR in the United States, treatment rates remain low. Black patients with symptomatic severe aortic valve stenosis were less likely than White patients to receive AVR, yet these differences have recently narrowed.

How to do things with (thousands of) words: Computational approaches to discourse analysis in Alzheimer's disease

Natural Language Processing (NLP) is an ever-growing field of computational science that aims to model natural human language. Combined with advances in machine learning, which learns patterns in data, it offers practical capabilities including automated language analysis. These approaches have garnered interest from clinical researchers seeking to understand the breakdown of language due to pathological changes in the brain, offering fast, replicable and objective methods. The study of Alzheimer's disease (AD), and preclinical Mild Cognitive Impairment (MCI), suggests that changes in discourse (connected speech or writing) may be key to early detection of disease. There is currently no disease-modifying treatment for AD, the leading cause of dementia in people over the age of 65, but detection of those at risk of developing the disease could help with the identification and testing of medications which can take effect before the underlying pathology has irreversibly spread. We outline important components of natural language, as well as NLP tools and approaches with which they can be extracted, analysed and used for disease identification and risk prediction. We review literature using these tools to model discourse across the spectrum of AD, including the contribution of machine learning approaches and Automatic Speech Recognition (ASR). We conclude that NLP and machine learning techniques are starting to greatly enhance research in the field, with measurable and quantifiable language components showing promise for early detection of disease, but there remain research and practical challenges for clinical implementation of these approaches. Challenges discussed include the availability of large and diverse datasets, ethics of data collection and sharing, diagnostic specificity and clinical acceptability.

Real-time Positioning Among Nursing Home Residents Living With Dementia: A Case Study

Dementia contributes to the development of pressure injuries (PrIs).

PURPOSE

This study describes the real-time body positions of 2 nursing home (NH) residents, residing in the United States and living with dementia, to inform development of PrI prevention strategies tailored to individual risk profiles.

METHODS

As part of a larger study, eligible residents were fitted with a triaxial accelerometer sensor placed on the anterior chest to monitor body positions 24-hours daily through a 4-week monitoring period. The current study used an observational, prospective design during routine repositioning events for 2 residents. A convenience sample of 2 residents from a single NH wing who were considered moderately at risk for PrI development (Braden Scale score 13-14) with a Brief Interview for Mental Status score in the severely impaired range were selected based on nursing staff recommendation.

RESULTS

Sensor data showed that both residents, although "chairfast" according to the Braden Scale, spent <5% in an upright position and the great majority of time reclining at an angle <50%. One (1) resident demonstrated a persistent side preference.

CONCLUSIONS

Wearable sensors are not a long-term solution for protecting those with dementia from PrI formation but do provide a crude picture of overall body positions throughout the 24-hour day that may inform individualized PrI prevention strategies. Studies including large samples of NH residents living with dementia are warranted.

Using clinical registries, administrative data and electronic medical records to improve medication safety and effectiveness in dementia

PURPOSE OF REVIEW

Clinical registries, routinely collected administrative data and electronic medical records (EMRs) provide new opportunities to investigate medication safety and effectiveness. This review outlines the strengths and limitations of these data, and highlights recent research related to safe and effective medication use in dementia.

RECENT FINDINGS

Clinical registries, administrative data and EMRs facilitate observational research among people often excluded from randomized controlled trials (RCTs). Larger sample sizes and longer follow-up times permit research into less common adverse events not apparent in RCTs. The validity of diagnoses recorded in administrative data and EMRs remains variable, although positive predictive values are typically high and sensitivity is low. Dispensing records are a rich source of data for estimating medication exposure. Recent research has investigated medications and prescribing patterns as risk factors for incident dementia, strategies to alleviate behavioural symptoms and the management of comorbidity. Common study protocols and common data models are examples of distributed network approaches increasingly used to conduct large and generalizable multi-database studies across different countries.

SUMMARY

Greater availability of electronic health data provides important opportunities to address evidence-practice gaps in relation to medication use and safety in people with dementia.

Validation of Random Forest Machine Learning Models to Predict Dementia-Related Neuropsychiatric Symptoms in Real-World Data

BACKGROUND

Neuropsychiatric symptoms (NPS) are the leading cause of the social burden of dementia but their role is underestimated.

OBJECTIVE

The objective of the study was to validate predictive models to separately identify psychotic and depressive symptoms in patients diagnosed with dementia using clinical databases representing the whole population to inform decision-makers.

METHODS

First, we searched the electronic health records of 4,003 patients with dementia to identify NPS. Second, machine learning (random forest) algorithms were applied to build separate predictive models for psychotic and depressive symptom clusters in the training set (N = 3,003). Third, calibration and discrimination were assessed in the test set (N = 1,000) to assess the performance of the models.

RESULTS

Neuropsychiatric symptoms were noted in the electronic health record of 58% of patients. The area under the receiver operating curve reached 0.80 for the psychotic cluster model and 0.74 for the depressive cluster model. The Kappa index and accuracy also showed better discrimination in the psychotic model. Calibration plots indicated that both types of model had less predictive accuracy when the probability of neuropsychiatric symptoms was <25%. The most important variables in the psychotic cluster model were use of risperidone, level of sedation, use of quetiapine and haloperidol and the number of antipsychotics prescribed. In the depressive cluster model, the most important variables were number of antidepressants prescribed, escitalopram use, level of sedation, and age.

CONCLUSION

Given their relatively good performance, the predictive models can be used to estimate prevalence of NPS in population databases.

Comparative efficacy of non-pharmacological interventions on agitation in people with dementia: A systematic review and Bayesian network meta-analysis

BACKGROUND

Agitation in people with dementia is common and distressing and can lead to increased caregiver burden. However, medications often have adverse reactions and limited effectiveness. Thus, non-pharmacological interventions are being increasingly implemented.

OBJECTIVES

To compare and rank the efficacy of different non-pharmacological interventions in the management of agitation in people with dementia.

DESIGN

Bayesian network meta-analysis.

METHODS

A comprehensive electronic literature search was performed in five English databases and three Chinese databases to identify relevant randomized controlled trials (RCTs) that were published up to January 2019. A random-effects model was selected to conduct traditional meta-analysis to directly examine the efficacy of different non-pharmacological interventions. The consistency model was selected to conduct a network meta-analysis to evaluate the relative effects and rank probability of different non-pharmacological interventions.

RESULTS

A total of 65 RCTs were included in this network meta-analysis involving 11 different non-pharmacological interventions. Network meta-analysis showed that massage therapy, animal-assisted intervention, and personally tailored intervention were associated with more substantial reductions in agitation compared with other interventions and controls.

CONCLUSIONS

Our study confirmed the effectiveness of non-pharmacological interventions for ameliorating agitation in people with dementia and recommended several interventions for clinical practice. Healthcare professionals should be encouraged to apply promising non-pharmacological interventions (e.g. massage therapy, animal-assisted intervention and personally tailored intervention) for people with dementia during routine care.

Behavioral and Psychiatric Symptoms of Dementia and Rate of Decline in Alzheimer's Disease

Alzheimer’s disease causes both cognitive and non-cognitive symptoms. There is increasing evidence that the presentation and course of Alzheimer’s disease is highly heterogenous. This heterogeneity presents challenges to patients, their families, and clinicians due to the difficulty in prognosticating future symptoms and functional impairment. Behavioral and psychiatric symptoms are emerging as a significant contributor to this clinical heterogeneity. These symptoms have been linked to multiple areas of neurodegeneration, which may suggest that they are representative of network-wide dysfunction in the brain. However, current diagnostic criteria for Alzheimer’s disease focus exclusively on the cognitive aspects of disease. Behavioral and psychiatric symptoms have been found in multiple studies to be related to disease severity and to contribute to disease progression over time. A better understanding of how behavioral and psychiatric symptoms relate to cognitive aspects of Alzheimer’s disease would help to refine the models of disease and hopefully lead to improved ability to develop therapeutic options for this devastating disease.

Treatment Options for Agitation in Dementia

PURPOSE OF REVIEW

The goal of the current review is to provide an update on the management of agitation in persons with dementia with a focus on pharmacological management of persons with Alzheimer's disease.

RECENT FINDINGS

As consistently effective and safe pharmacologic interventions are still lacking, identifying and addressing medical and environmental precipitants remain a priority. Acetylcholinesterase inhibitors and memantine should be initiated to enhance cognition, and if present, management of insomnia or sundowning with trazodone is indicated. If agitation persists, treatment with citalopram can be initiated with attention paid to potential prolongation of the QT interval. Treatment with low doses of atypical antipsychotics such as risperidone or quetiapine can be effective after appropriate consideration of and disclosure of potential adverse effects. In light of the lack of consistently effective treatments for agitation in dementia, there have been renewed efforts to define the condition and improve the design of trials of medications to treat it. Considering the heterogeneity of patients and their comorbidities as well as the specific nature of their "agitation", there is no "one-size fits all" approach to agitation in AD. However, many options exist that can be prudently pursued for this common problem in this delicate population.

Early recognition and treatment of neuropsychiatric symptoms to improve quality of life in early Alzheimer's disease: protocol of the BEAT-IT study

BACKGROUND

Neuropsychiatric symptoms (NPS) are very common in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia and are associated with various disadvantageous clinical outcomes including a negative impact on quality of life, caregiver burden, and accelerated disease progression. Despite growing evidence of the efficacy of (non)pharmacological interventions to reduce these symptoms, NPS remain underrecognized and undertreated in memory clinics. The BEhavioural symptoms in Alzheimer's disease Towards early Identification and Treatment (BEAT-IT) study is developed to (1) investigate the neurobiological etiology of NPS in AD and (2) study the effectiveness of the Describe, Investigate, Create, Evaluate (DICE) approach to structure and standardize the current care of NPS in AD. By means of the DICE method, we aim to improve the quality of life of AD patients with NPS and their caregivers who visit the memory clinic. This paper describes the protocol for the intervention study that incorporates the latter aim.

METHODS

We aim to enroll a total of 150 community-dwelling patients with MCI or AD and their caregivers in two waves. First, we will recruit a control group who will receive care as usual. Next, the second wave of participants will undergo the DICE method. This approach consists of the following steps: (1) describe the context in which NPS occur, (2) investigate the possible causes, (3) create and implement a treatment plan, and (4) evaluate whether these interventions are effective. Primary outcomes are the quality of life of patients and their caregivers. Secondary outcomes include NPS change, caregiver burden, caregivers' confidence managing NPS, psychotropic medication use, the experiences of patients and caregivers who underwent the DICE method, and the cost-effectiveness of the intervention.

CONCLUSIONS

This paper describes the protocol of an intervention study that is part of the BEAT-IT study and aims to improve current recognition and treatment of NPS in AD by structuring and standardizing the detection and treatment of NPS in AD using the DICE approach.

TRIAL REGISTRATION

The trial was registered on the Netherlands Trial Registry ( NTR7459 ); registered 6 September 2018.

Using electronic health records to estimate the prevalence of agitation in Alzheimer disease/dementia

BACKGROUND

Agitation is a common neuropsychiatric symptom of Alzheimer disease (AD). Data are scarce regarding agitation prevalence among community-dwelling patients with AD.

OBJECTIVE

To estimate agitation prevalence in a sample of US patients with AD/dementia overall and by AD/dementia disease severity, using data from electronic health records (EHR).

METHODS

This retrospective database study examined community-dwelling patients with ≥1 EHR record indicating AD/dementia from January 2008 to June 2015 and no evidence of non-Alzheimer dementia during the 12-month preindex and postindex periods. Agitation was identified using diagnosis codes for dementia with behavioral disturbance and EHR abstracted notes records indicating agitation symptoms compiled from the International Psychogeriatric Association provisional consensus definition.

RESULTS

Of 320 886 eligible patients (mean age, 76.4 y, 64.7% female), 143 160 (44.6%) had evidence of agitation during the observation period. Less than 5% of patients with agitation had a diagnosis code for behavioral disturbance. The most prevalent symptom categories among patients with agitation, preindex and postindex, were agitation (31.4% and 41.3%), falling (22.6% and 21.7%), and restlessness (18.3% and 23.3%). Among the 78 827 patients (24.6%) with known AD/dementia severity, agitation prevalence was 61.3%. Agitation during the observation period was most prevalent for moderate-to-severe and severe AD/dementia (74.6% and 68.3%, respectively) and lowest for mild AD/dementia (56.4%).

CONCLUSIONS

Agitation prevalence was 44.6% overall and 61.3% among patients with staged AD/dementia. Behavioral disturbance appeared to be underdiagnosed. While agitation has previously been shown to be highly prevalent in the long-term care setting, this study indicates that it is also common among community-dwelling patients.