Tau-PET in early cortical Alzheimer brain regions in relation to mild behavioral impairment in older adults with either normal cognition or mild cognitive impairment

Mild Behavioral Impairment (MBI) leverages later-life emergent and persistent neuropsychiatric symptoms (NPS) to identify a high-risk group for incident dementia. Phosphorylated tau (p-tau) is a hallmark biological manifestation of Alzheimer disease (AD). We investigated associations between MBI and tau accumulation in early-stage AD cortical regions. In 442 Alzheimer's Disease Neuroimaging Initiative participants with normal cognition or mild cognitive impairment, MBI status was determined alongside corresponding p-tau and Aβ. Two meta-regions of interest were generated to represent Braak I and III neuropathological stages. Multivariable linear regression modelled the association between MBI as independent variable and tau tracer uptake as dependent variable. Among Aβ positive individuals, MBI was associated with tau uptake in Braak I (β=0.45(0.15), p<.01) and Braak III (β=0.24(0.07), p<.01) regions. In Aβ negative individuals, MBI was not associated with tau in the Braak I region (p=0.11) with a negative association in Braak III (p=.01). These findings suggest MBI may be a sequela of neurodegeneration, and can be implemented as a cost-effective framework to help improve screening efficiency for AD.

Canadian Network for Mood and Anxiety Treatments (CANMAT) 2023 Update on Clinical Guidelines for Management of Major Depressive Disorder in Adults: Réseau canadien pour les traitements de l'humeur et de l'anxiété (CANMAT) 2023 : Mise à jour des lignes directrices cliniques pour la prise en charge du trouble dépressif majeur chez les adultes

BACKGROUND

The Canadian Network for Mood and Anxiety Treatments (CANMAT) last published clinical guidelines for the management of major depressive disorder (MDD) in 2016. Owing to advances in the field, an update was needed to incorporate new evidence and provide new and revised recommendations for the assessment and management of MDD in adults.

METHODS

CANMAT convened a guidelines editorial group comprised of academic clinicians and patient partners. A systematic literature review was conducted, focusing on systematic reviews and meta-analyses published since the 2016 guidelines. Recommendations were organized by lines of treatment, which were informed by CANMAT-defined levels of evidence and supplemented by clinical support (consisting of expert consensus on safety, tolerability, and feasibility). Drafts were revised based on review by patient partners, expert peer review, and a defined expert consensus process.

RESULTS

The updated guidelines comprise eight primary topics, in a question-and-answer format, that map a patient care journey from assessment to selection of evidence-based treatments, prevention of recurrence, and strategies for inadequate response. The guidelines adopt a personalized care approach that emphasizes shared decision-making that reflects the values, preferences, and treatment history of the patient with MDD. Tables provide new and updated recommendations for psychological, pharmacological, lifestyle, complementary and alternative medicine, digital health, and neuromodulation treatments. Caveats and limitations of the evidence are highlighted.

CONCLUSIONS

The CANMAT 2023 updated guidelines provide evidence-informed recommendations for the management of MDD, in a clinician-friendly format. These updated guidelines emphasize a collaborative, personalized, and systematic management approach that will help optimize outcomes for adults with MDD.

A systematic review/meta-analysis of prevalence and incidence rates illustrates systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research

We investigate Alzheimer's disease and related dementia (ADRD) prevalence, incidence rate, and risk factors in individuals racialized as Asian and/or Asian-American and assess sample representation. Prevalence, incidence rate, risk factors, and heterogeneity of samples were assessed. Random-effects meta-analysis was conducted, generating pooled estimates. Of 920 records across 14 databases, 45 studies were included. Individuals racialized as Asian and/or Asian-American were mainly from Eastern and Southern Asia, had higher education, and constituted a smaller sample relative to non-Hispanic white cohorts. The average prevalence was 10.9%, ranging from 0.4% to 46%. The average incidence rate was 20.03 (12.01-33.8) per 1000 person-years with a range of 75.19-13.59 (12.89-14.33). Risk factors included physiological, genetic, psychological, behavioral, and social factors. This review underscores the systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research and the need for inclusive approaches accounting for culture, language, and immigration status. HIGHLIGHTS: There is considerable heterogeneity in the prevalence of ADRD among studies of Asian-Americans. There is limited data on group-specific risk factors for ADRD among Asian-Americans. The average prevalence of (ADRD) among Asian-Americans was found to be 7.4%, with a wide range from 0.5% to 46%.

Guideline Recommendations on Behavioral and Psychological Symptoms of Dementia: A Systematic Review

OBJECTIVE

To synthesize recommendations on assessing and managing behavioral and psychological symptoms of dementia (BPSDs) in existing clinical practice guidelines on dementia care to learn from and adapt recommendations to a Canadian context and language for describing BPSDs.

DESIGN

Systematic review.

SETTING AND PARTICIPANTS

Moderate to high-quality clinical practice guidelines on dementia care that made 1 or more recommendations on BPSD assessment or management.

METHODS

We searched MEDLINE, Embase, JBI EBM, PsycINFO, AgeLine, and gray literature for clinical practice guidelines on dementia care making recommendations on BPSD, published between January 1, 2011, and October 13, 2022. Two independent reviewers conducted study screening and data abstraction. Four independent reviewers completed quality appraisal using the Appraisal of Guidelines for Research and Evaluation (AGREE) II tool; included guidelines had a mean overall AGREE II score ≥4.

RESULTS

Our systematic review identified 23 moderate to high-quality clinical practice guidelines (264 recommendations). The mean overall quality score on the AGREE II tool ranged from 4 to 6.5. Recommendations were clearly presented (mean clarity of presentation score 73.5%), but guideline applicability was not consistently addressed (mean applicability score 39.3%). BPSD was the most prevalent term describing neuropsychiatric symptoms (number of guidelines [n] = 14). People with lived experience contributed to 6 guidelines (26.1%). Ten guidelines (43.5%) described 1 or more health equity considerations. Guidelines made recommendations for assessing and managing agitation (n = 12), aggression (n = 10), psychosis (n = 11), depression (n = 9), anxiety (n = 5), apathy (n = 6), inappropriate sexual behavior (n = 3), nighttime behavior (n = 5), and eating disturbances (n = 3). There was substantial variability in recommendation statements, evidence quality assigned to each statement, and strength of recommendations.

CONCLUSIONS AND IMPLICATIONS

There are several moderate to high-quality clinical practice guidelines making recommendations on BPSD assessment and management, but variability in recommendation statements across guidelines and insufficient consideration of guideline applicability may hamper guideline dissemination and implementation in clinical practice.

Visual Functions Are Associated with Biomarker Changes in Alzheimer's Disease

Background

While various biomarkers of Alzheimer's disease (AD) have been associated with general cognitive function, their association to visual-perceptive function across the AD spectrum warrant more attention due to its significant impact on quality of life. Thus, this study explores how AD biomarkers are associated with decline in this cognitive domain.

Objective

To explore associations between various fluid and imaging biomarkers and visual-based cognitive assessments in participants across the AD spectrum.

Methods

Data from participants (N = 1,460) in the Alzheimer's Disease Neuroimaging Initiative were analyzed, including fluid and imaging biomarkers. Along with the Mini-Mental State Examination (MMSE), three specific visual-based cognitive tests were investigated: Trail Making Test (TMT) A and TMT B, and the Boston Naming Test (BNT). Locally estimated scatterplot smoothing curves and Pearson correlation coefficients were used to examine associations.

Results

MMSE showed the strongest correlations with most biomarkers, followed by TMT-B. The p-tau181/Aβ1-42 ratio, along with the volume of the hippocampus and entorhinal cortex, had the strongest associations among the biomarkers.

Conclusions

Several biomarkers are associated with visual processing across the disease spectrum, emphasizing their potential in assessing disease severity and contributing to progression models of visual function and cognition.

White Matter Microstructural Underpinnings of Mild Behavioral Impairment in Parkinson's Disease

BACKGROUND

Patients with Parkinson's disease (PD) experience changes in behavior, personality, and cognition that can manifest even in the initial stages of the disease. Previous studies have suggested that mild behavioral impairment (MBI) should be considered an early marker of cognitive decline. However, the precise neurostructural underpinnings of MBI in early- to mid-stage PD remain poorly understood.

OBJECTIVE

The aim was to explore the changes in white matter microstructure linked to MBI and mild cognitive impairment (MCI) in early- to mid-stage PD using diffusion magnetic resonance imaging (dMRI).

METHODS

A total of 91 PD patients and 36 healthy participants were recruited and underwent anatomical MRI and dMRI, a comprehensive neuropsychological battery, and the completion of the Mild Behavioral Impairment-Checklist. Metrics of white matter integrity included tissue fractional anisotropy (FAt) and radial diffusivity (RDt), free water (FW), and fixel-based apparent fiber density (AFD).

RESULTS

The connection between the left amygdala and the putamen was disrupted when comparing PD patients with MBI (PD-MBI) to PD-non-MBI, as evidenced by increased RDt (η2 = 0.09, P = 0.004) and both decreased AFD (η2 = 0.05, P = 0.048) and FAt (η2 = 0.12, P = 0.014). Compared to controls, PD patients with both MBI and MCI demonstrated increased FW for the connection between the left orbitofrontal gyrus (OrG) and the hippocampus (η2 = 0.22, P = 0.008), augmented RDt between the right OrG and the amygdala (η2 = 0.14, P = 0.008), and increased RDt (η2 = 0.25, P = 0.028) with decreased AFD (η2 = 0.10, P = 0.046) between the right OrG and the caudate nucleus.

CONCLUSION

MBI is associated with abnormal microstructure of connections involving the orbitofrontal cortex, putamen, and amygdala. To our knowledge, this is the first assessment of the white matter microstructure in PD-MBI using dMRI. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Barriers and facilitators to care for agitation and/or aggression among persons living with dementia in long-term care

BACKGROUND

Agitation and/or aggression affect up to 60% of persons living with dementia in long-term care (LTC). It can be treated via non-pharmacological and pharmacological interventions, but the former are underused in clinical practice. In the literature, there is currently a lack of understanding of the challenges to caring for agitation and/or aggression among persons living with dementia in LTC. This study assesses what barriers and facilitators across the spectrum of care exist for agitation and/or aggression among people with dementia in LTC across stakeholder groups.

METHODS

This was a qualitative study that used semi-structured interviews among persons involved in the care and/or planning of care for people with dementia in LTC. Participants were recruited via purposive and snowball sampling, with the assistance of four owner-operator models. Interviews were guided by the Theoretical Domains Framework and transcribed and analyzed using Framework Analysis.

RESULTS

Eighteen interviews were conducted across 5 stakeholder groups. Key identified barriers were a lack of agitation and/or aggression diagnostic measures, limited training for managing agitation and/or aggression in LTC, an overuse of physical and chemical restraints, and an underuse of non-pharmacological interventions. Facilitators included using an interdisciplinary team to deliver care and having competent and trained healthcare providers to administer non-pharmacological interventions.

CONCLUSIONS

This study advances care for persons living with dementia in LTC by drawing attention to unique and systemic barriers present across local and national Canadian LTC facilities. Findings will support future implementation research endeavours to eliminate these identified barriers across the spectrum of care, thus improving care outcomes among people with dementia in LTC.

Prevalence of AmpC beta-lactamase and extended spectrum beta-lactamase co-producer in Escherichia coli and Klebsiella species in a teaching hospital

INTRODUCTION

Beta-lactamase producing bacterial infection has been on surge due to selection pressure and injudicious antibiotics usage. Organisms that co-produced more than one beta lactamase enzyme posed diagnostic challenges which may result in inadequate treatment. To date, there is no standardised guideline offering phenotypic detection of AmpC β-lactamase. The purpose of this study was to determine the prevalence of ESBLs, AmpC β-lactamase and co-producer organisms in a teaching hospital.

MATERIALS AND METHODS

Three hundred and four isolates of E. coli and Klebsiella sp. had been selected via convenient sampling. These isolates were identified using conventional laboratory methods and their antimicrobial susceptibilities were determined using disc diffusion method. Those isolates were then proceeded with ESBL confirmatory test, cloxacillin-containing Muller Hinton confirmatory test, modified double disk synergy test and AmpC disk test.

RESULTS

Out of 304 isolates, 159 isolates were E. coli and 145 were Klebsiella sp. The prevalence of organisms which co-produced AmpC β-lactamase and ESBL enzymes were 3.0%. Besides that, 39 cefoxitin resistant and three cefoxitin susceptible isolates (13.8%) were proven to produce AmpC β-lactamase through AmpC disk test. Through the CLSI confirmatory test, 252 (82.9%) isolates were identified as ESBLs producers and the prevalence increased slightly when cloxacillin-containing Muller Hinton were used. Only three ESBLs positive organisms were positive for modified double disk synergy test.

CONCLUSION

Distinguishing between AmpC β-lactamase and ESBL-producing organisms has epidemiological significance as well as therapeutic importance. Moreover, AmpC β-lactamase and ESBLs co-producing organisms can lead to false negative ESBL confirmatory test. Therefore, knowing the local prevalence can guide the clinician in navigating the treatment.

Reduction and prevention of agitation in persons with neurocognitive disorders: an international psychogeriatric association consensus algorithm

OBJECTIVES

To develop an agitation reduction and prevention algorithm is intended to guide implementation of the definition of agitation developed by the International Psychogeriatric Association (IPA).

DESIGN

Review of literature on treatment guidelines and recommended algorithms; algorithm development through reiterative integration of research information and expert opinion.

SETTING

IPA Agitation Workgroup.

PARTICIPANTS

IPA panel of international experts on agitation.

INTERVENTION

Integration of available information into a comprehensive algorithm.

MEASUREMENTS

None.

RESULTS

The IPA Agitation Work Group recommends the Investigate, Plan, and Act (IPA) approach to agitation reduction and prevention. A thorough investigation of the behavior is followed by planning and acting with an emphasis on shared decision-making; the success of the plan is evaluated and adjusted as needed. The process is repeated until agitation is reduced to an acceptable level and prevention of recurrence is optimized. Psychosocial interventions are part of every plan and are continued throughout the process. Pharmacologic interventions are organized into panels of choices for nocturnal/circadian agitation; mild-moderate agitation or agitation with prominent mood features; moderate-severe agitation; and severe agitation with threatened harm to the patient or others. Therapeutic alternatives are presented for each panel. The occurrence of agitation in a variety of venues-home, nursing home, emergency department, hospice-and adjustments to the therapeutic approach are presented.

CONCLUSIONS

The IPA definition of agitation is operationalized into an agitation management algorithm that emphasizes the integration of psychosocial and pharmacologic interventions, reiterative assessment of response to treatment, adjustment of therapeutic approaches to reflect the clinical situation, and shared decision-making.

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.

Neuropsychiatric symptoms and brain morphology in patients with mild cognitive impairment, cerebrovascular disease and Parkinson disease: A cross sectional and longitudinal study

OBJECTIVES

Neuropsychiatric symptoms (NPS) increase risk of developing dementia and are linked to various neurodegenerative conditions, including mild cognitive impairment (MCI due to Alzheimer's disease [AD]), cerebrovascular disease (CVD), and Parkinson's disease (PD). We explored the structural neural correlates of NPS cross-sectionally and longitudinally across various neurodegenerative diagnoses.

METHODS

The study included individuals with MCI due to AD, (n = 74), CVD (n = 143), and PD (n = 137) at baseline, and at 2-years follow-up (MCI due to AD, n = 37, CVD n = 103, and PD n = 84). We assessed the severity of NPS using the Neuropsychiatric Inventory Questionnaire. For brain structure we included cortical thickness and subcortical volume of predefined regions of interest associated with corticolimbic and frontal-executive circuits.

RESULTS

Cross-sectional analysis revealed significant negative correlations between appetite with both circuits in the MCI and CVD groups, while apathy was associated with these circuits in both the MCI and PD groups. Longitudinally, changes in apathy scores in the MCI group were negatively linked to the changes of the frontal-executive circuit. In the CVD group, changes in agitation and nighttime behavior were negatively associated with the corticolimbic and frontal-executive circuits, respectively. In the PD group, changes in disinhibition and apathy were positively associated with the corticolimbic and frontal-executive circuits, respectively.

CONCLUSIONS

The observed correlations suggest that underlying pathological changes in the brain may contribute to alterations in neural activity associated with MBI. Notably, the difference between cross-sectional and longitudinal results indicates the necessity of conducting longitudinal studies for reproducible findings and drawing robust inferences.

Understanding the Barriers to and Facilitators of Anxiety Management in Residents of Long-Term Care

Older adults, 65 years of age and older, living in long-term care (LTC) commonly experience anxiety. This study aimed to understand care providers' perspectives on the barriers to and facilitators of managing anxiety in residents of LTC. Ten semi-structured interviews with care providers in LTC were completed. Framework analysis methods were used to code, thematically analyze, designate codes as barriers or facilitators, and map the codes to the Theoretical Domains Framework. Themes were categorized as acting at the resident, provider, or system level, and were labelled as either barriers to or facilitators of anxiety care. Key barriers to anxiety care at each level were resident cognitive impairment or co-morbidities; lack of staff education, staff treatment uptake and implementation; as well as the care delivery environment and access to resources. There is a need to prioritize measurement-based care for anxiety, have increased access to non-pharmacological treatments, and have a care delivery environment that supports anxiety management to improve the care for anxiety that is delivered to residents.

Behavioral Impairments and Increased Risk of Cortical Atrophy Risk Scores Among World Trade Center Responders

Objective: World Trade Center (WTC) responders are susceptible to both cognitive and neuropsychiatric impairments, particularly chronic posttraumatic stress disorder. The present study examined self-reported behavioral impairments in a sample of 732 WTC responders, 199 of whom were determined to have high risk of WTC-related cortical atrophy by an artificial neural network. Results: We found that responders at increased risk of cortical atrophy showed behavioral impairment across five domains: motivation, mood, disinhibition, empathy, and psychosis (14.6% vs 3.9% in the low-risk group; P = 3.90 × 10-7). Factor analysis models revealed that responders at high risk of cortical atrophy tended to have deficits generalized across all aspects of behavioral impairment with focal dysfunction in sensory psychosis. We additionally describe how relationships are modulated by exposure severity and pharmacological treatments. Discussion: Our findings suggest a potential link between sensory deficits and the development of cortical atrophy in WTC responders and may indicate symptoms consistent with a clinical portrait of parietal dominant Alzheimer's disease or a related dementia (ADRD). Results underscore the importance of investigating neuropsychiatric symptomatology in clinical evaluations of possible ADRD.

Adjunctive Brexpiprazole for Patient Life Engagement in Major Depressive Disorder: A Canadian, Phase 4, Open-Label, Interventional Study: Brexpiprazole d'appoint pour l'engagement dans la vie des patients souffrant de trouble dépressif majeur: une étude interventionnelle canadienne ouverte de phase 4

OBJECTIVES

To characterize the effects of adjunctive brexpiprazole on patient life engagement and depressive symptoms in patients with major depressive disorder (MDD) using patient-reported outcomes.

METHODS

An 8-week, Phase 4, open-label, interventional study was conducted at 15 Canadian trial sites between April 2021 and May 2022. Adult outpatients with MDD (at least moderately severe) and inadequate response to 1-2 antidepressants continued their current antidepressant and received oral adjunctive brexpiprazole 0.5-2 mg/day. Co-primary endpoints were change from baseline to Week 8 in Inventory of Depressive Symptomatology Self-Report (IDS-SR) 10-item Life Engagement subscale score, and IDS-SR 30-item total score. Safety was assessed by standard variables.

RESULTS

Of 122 enrolled patients, 120 (98.4%) were treated (mean [SD] dose: 1.2 [0.4] mg/day) and analyzed, and 111 (91.0%) completed the study. Statistically significant least squares mean improvements to Week 8 were observed on IDS-SR10 Life Engagement subscale score (baseline mean [SD]: 16.1 [4.7]; change [95% confidence interval]: -8.11 [-9.34, -6.88]; p < 0.001) and IDS-SR total score (baseline mean [SD]: 41.3 [9.8]; change [95% confidence interval]: -17.38 [-20.08, -14.68]; p < 0.001). Improvements were observed from Week 2, onwards. Treatment-emergent adverse events with incidence ≥5% were fatigue (n = 13, 10.8%), headache (n = 13, 10.8%), insomnia (n = 12, 10.0%), nausea (n = 9, 7.5%), tremor (n = 8, 6.7%), and weight increase (n = 7, 5.8%). Six patients (5.0%) discontinued due to adverse events. Mean (SD) change in body weight from baseline to last visit was +1.9 (3.4) kg.

CONCLUSIONS

Using an exploratory patient-reported outcome measure, patients with MDD and inadequate response to antidepressants who received open-label adjunctive brexpiprazole showed early and clinically meaningful improvement in patient life engagement, which should be further assessed in a prospective randomized controlled trial. Patient-rated depressive symptoms (on the validated 30-item IDS-SR) also improved. Adjunctive brexpiprazole was well tolerated, and no new safety signals were observed.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT04830215.

Exploiting macro- and micro-structural brain changes for improved Parkinson's disease classification from MRI data

Parkinson's disease (PD) is the second most common neurodegenerative disease. Accurate PD diagnosis is crucial for effective treatment and prognosis but can be challenging, especially at early disease stages. This study aimed to develop and evaluate an explainable deep learning model for PD classification from multimodal neuroimaging data. The model was trained using one of the largest collections of T1-weighted and diffusion-tensor magnetic resonance imaging (MRI) datasets. A total of 1264 datasets from eight different studies were collected, including 611 PD patients and 653 healthy controls (HC). These datasets were pre-processed and non-linearly registered to the MNI PD25 atlas. Six imaging maps describing the macro- and micro-structural integrity of brain tissues complemented with age and sex parameters were used to train a convolutional neural network (CNN) to classify PD/HC subjects. Explainability of the model's decision-making was achieved using SmoothGrad saliency maps, highlighting important brain regions. The CNN was trained using a 75%/10%/15% train/validation/test split stratified by diagnosis, sex, age, and study, achieving a ROC-AUC of 0.89, accuracy of 80.8%, specificity of 82.4%, and sensitivity of 79.1% on the test set. Saliency maps revealed that diffusion tensor imaging data, especially fractional anisotropy, was more important for the classification than T1-weighted data, highlighting subcortical regions such as the brainstem, thalamus, amygdala, hippocampus, and cortical areas. The proposed model, trained on a large multimodal MRI database, can classify PD patients and HC subjects with high accuracy and clinically reasonable explanations, suggesting that micro-structural brain changes play an essential role in the disease course.

Tau-PET in early cortical Alzheimer brain regions in relation to mild behavioral impairment in older adults with either normal cognition or mild cognitive impairment

Mild Behavioral Impairment (MBI) leverages later-life emergent and persistent neuropsychiatric symptoms (NPS) to identify a high-risk group for incident dementia. Phosphorylated tau (p-tau) is a hallmark biological manifestation of Alzheimer disease (AD). We investigated associations between MBI and tau accumulation in early-stage AD cortical regions. In 442 Alzheimer's Disease Neuroimaging Initiative participants with normal cognition or mild cognitive impairment, MBI status was determined alongside corresponding p-tau and Aβ. Two meta-regions of interest were generated to represent Braak I and III neuropathological stages. Multivariable linear regression modelled the association between MBI as independent variable and tau tracer uptake as dependent variable. Among Aβ positive individuals, MBI was associated with tau uptake in Braak I (β =0.45(0.15), p<.01) and Braak III (β =0.24(0.07), p<.01) regions. In Aβ negative individuals, MBI was not associated with tau in the Braak I region (p=.11) with a negative association in Braak III (p=.01). These findings suggest MBI may be a sequela of neurodegeneration, and can be implemented as a cost-effective framework to help improve screening efficiency for AD.

A multi-center distributed learning approach for Parkinson's disease classification using the traveling model paradigm

Distributed learning is a promising alternative to central learning for machine learning (ML) model training, overcoming data-sharing problems in healthcare. Previous studies exploring federated learning (FL) or the traveling model (TM) setup for medical image-based disease classification often relied on large databases with a limited number of centers or simulated artificial centers, raising doubts about real-world applicability. This study develops and evaluates a convolution neural network (CNN) for Parkinson's disease classification using data acquired by 83 diverse real centers around the world, mostly contributing small training samples. Our approach specifically makes use of the TM setup, which has proven effective in scenarios with limited data availability but has never been used for image-based disease classification. Our findings reveal that TM is effective for training CNN models, even in complex real-world scenarios with variable data distributions. After sufficient training cycles, the TM-trained CNN matches or slightly surpasses the performance of the centrally trained counterpart (AUROC of 83% vs. 80%). Our study highlights, for the first time, the effectiveness of TM in 3D medical image classification, especially in scenarios with limited training samples and heterogeneous distributed data. These insights are relevant for situations where ML models are supposed to be trained using data from small or remote medical centers, and rare diseases with sparse cases. The simplicity of this approach enables a broad application to many deep learning tasks, enhancing its clinical utility across various contexts and medical facilities.

Comparative methods for quantifying plasma biomarkers in Alzheimer's disease: Implications for the next frontier in cerebral amyloid angiopathy diagnostics

Plasma amyloid beta (Aβ) and tau are emerging as accessible biomarkers for Alzheimer's disease (AD). However, many assays exist with variable test performances, highlighting the need for a comparative assessment to identify the most valid assays for future use in AD and to apply to other settings in which the same biomarkers may be useful, namely, cerebral amyloid angiopathy (CAA). CAA is a progressive cerebrovascular disease characterized by deposition of Aβ40 and Aβ42 in cortical and leptomeningeal vessels. Novel immunotherapies for AD can induce amyloid-related imaging abnormalities resembling CAA-related inflammation. Few studies have evaluated plasma biomarkers in CAA. Identifying a CAA signature could facilitate diagnosis, prognosis, and a safer selection of patients with AD for emerging immunotherapies. This review evaluates studies that compare the diagnostic test performance of plasma biomarker techniques in AD and cerebrovascular and plasma biomarker profiles of CAA; it also discusses novel hypotheses and future avenues for plasma biomarker research in CAA.

Mild behavioral impairment in early Alzheimer's disease and its association with APOE and BDNF risk genetic polymorphisms

BACKGROUND

Mild behavioral impairment (MBI) has been commonly reported in early Alzheimer's disease (AD) but rarely using biomarker-defined samples. It is also unclear whether genetic polymorphisms influence MBI in such individuals. We thus aimed to examine the association between the cognitive status of participants (amnestic mild cognitive impairment (aMCI-AD) vs cognitively normal (CN) older adults) and MBI severity. Within aMCI-AD, we further examined the association between APOE and BDNF risk genetic polymorphisms and MBI severity.

METHODS

We included 62 aMCI-AD participants and 50 CN older adults from the Czech Brain Aging Study. The participants underwent neurological, comprehensive neuropsychological examination, APOE and BDNF genotyping, and magnetic resonance imaging. MBI was diagnosed with the Mild Behavioral Impairment Checklist (MBI-C), and the diagnosis was based on the MBI-C total score ≥ 7. Additionally, self-report instruments for anxiety (the Beck Anxiety Inventory) and depressive symptoms (the Geriatric Depression Scale-15) were administered. The participants were stratified based on the presence of at least one risk allele in genes for APOE (i.e., e4 carriers and non-carriers) and BDNF (i.e., Met carriers and non-carriers). We used linear regressions to examine the associations.

RESULTS

MBI was present in 48.4% of the aMCI-AD individuals. Compared to the CN, aMCI-AD was associated with more affective, apathy, and impulse dyscontrol but not social inappropriateness or psychotic symptoms. Furthermore, aMCI-AD was related to more depressive but not anxiety symptoms on self-report measures. Within the aMCI-AD, there were no associations between APOE e4 and BDNF Met and MBI-C severity. However, a positive association between Met carriership and self-reported anxiety appeared.

CONCLUSIONS

MBI is frequent in aMCI-AD and related to more severe affective, apathy, and impulse dyscontrol symptoms. APOE and BDNF polymorphisms were not associated with MBI severity separately; however, their combined effect warrants further investigation.

Impact of Mild Behavioral Impairment on Longitudinal Changes in Cognition

BACKGROUND

To examine cross-sectional differences and longitudinal changes in cognitive performance based on the presence of mild behavioral impairment (MBI) among older adults who are cognitively healthy or have mild cognitive impairment (MCI).

METHODS

Secondary data analysis of participants (n = 17 291) who were cognitively healthy (n = 11 771) or diagnosed with MCI (n = 5 520) from the National Alzheimer's Coordinating Center database. Overall, 24.7% of the sample met the criteria for MBI. Cognition was examined through a neuropsychological battery that assessed attention, episodic memory, executive function, language, visuospatial ability, and processing speed.

RESULTS

Older adults with MBI, regardless of whether they were cognitively healthy or diagnosed with MCI, performed significantly worse at baseline on tasks for attention, episodic memory, executive function, language, and processing speed and exhibited greater longitudinal declines on tasks of attention, episodic memory, language, and processing speed. Cognitively healthy older adults with MBI performed significantly worse than those who were cognitively healthy without MBI on tasks of visuospatial ability at baseline and on tasks of processing speed across time. Older adults with MCI and MBI performed significantly worse than those with only MCI on executive function at baseline and visuospatial ability and processing speed tasks across time.

CONCLUSIONS

This study found evidence that MBI is related to poorer cognitive performance cross-sectionally and longitudinally. Additionally, those with MBI and MCI performed worse across multiple tasks of cognition both cross-sectionally and across time. These results provide support for MBI being uniquely associated with different aspects of cognition.

Presenilin Gene Mutation-associated Psychosis: Phenotypic Characteristics and Clinical Implications

Although psychotic symptoms have been described in association with rare presenilin ( PSEN ) gene mutations underlying early-onset Alzheimer disease (AD), no contemporary reviews on this topic exist. The purpose of this review is to characterize the psychiatric phenotype (specifically with respect to psychosis) of PSEN1 and PSEN2 variant-associated AD. A PubMed search was completed in July 2023. Only articles that described individuals harboring a PSEN1 or PSEN2 mutation who experienced symptoms of psychosis were included in the review. Thirty-three articles describing 52 individuals were included in the review, as well as one other study that provided limited information pertaining to an additional 21 cases. While visual hallucinations were the most common psychotic symptom, followed by persecutory delusions, auditory hallucinations occurred in ~17% of individuals. In ~33% of the reviewed cases psychotic symptoms were present at or near disease onset, and 9 of these individuals experienced auditory hallucinations and/or delusions in the absence of visual hallucinations (~17% of all cases). In many cases, symptoms developed at a relatively young age. As presenilin gene variant-associated psychosis may resemble a primary psychotic disorder, clinicians should be vigilant with respect to screening for signs/symptoms suggestive of neurodegeneration in first-episode psychosis.

CTAD Task Force Paper: Neuropsychiatric Symptoms in AD: Clinical Trials Targeting Mild Behavioral Impairment: A Report from the International CTAD Task Force

The International CTAD Task Force (TF) addressed challenges related to designing clinical trials for agitation in dementia, presenting accomplishments from the two previous TFs on neuropsychiatric symptoms (NPS). In addition, this TF proposed a paradigm shift in NPS assessment and management, presenting Mild Behavioral Impairment (MBI) as a clinical syndrome. MBI is marked by later-life emergent and persistent NPS in dementia-free older persons (ranging from cognitively unimpaired to subjective cognitive decline to mild cognitive impairment), which facilitates earlier detection and better prognostication of Alzheimer's disease (AD). The TF has made the following recommendations for incorporation of NPS into AD preventative trials: (1) clinical trials targeting improvement in MBI symptoms should be undertaken; (2) treatment trials for MBI should be disease specific and confirm the diagnosis of participants using biomarkers; trials should include measures sensitive to cognitive changes in preclinical AD, which can serve as outcome measures, in addition to changes in biomarker levels; (3) as a first step, pharmacotherapeutic trials should address the full MBI complex as well as the specific symptoms/domains that constitute MBI; (4) clinical trials using problem-adaptation psychotherapy to target affective MBI should be considered; and (5) MBI should be considered in AD trials of disease modifying therapies. The well-validated and widely-used MBI Checklist (MBI-C) is an appropriate symptom rating scale for these studies, as it was developed specifically to identify and measure MBI in dementia-free persons. Other scales such as the Neuropsychiatric Inventory (NPI) may be used, although administration at two timepoints may be necessary to operationalize the MBI criterion of symptom persistence.

Relationship between Loneliness and Mild Behavioral Impairment: Validation of the Japanese Version of the MBI Checklist and a Cross-Sectional Study

Background

Mild behavioral impairment (MBI) and loneliness are associated with cognitive decline and an increased risk of dementia.

Objective

Our aim was to examine the validity of the Japanese version of the MBI checklist (MBI-C) and investigate the relationship between loneliness and MBI.

Methods

The participants in this cross-sectional study included 5 cognitively normal persons and 75 persons with mild cognitive impairment. MBI-C and the revised University of California at Los Angeles loneliness scale (LS) were used to assess MBI and loneliness, respectively. Diagnostic performance of MBI-C was examined using receiver operating characteristic analysis. The relationship between MBI-C and LS was examined using multiple linear regression in 67 subjects who were assessed with both scales, with MBI-C total or domain score as the dependent variable and LS as the independent variable, adjusted for age, gender, living situation, presence of visual and hearing impairment, and Mini-Mental State Examination score.

Results

Per the Youden index, in this mostly MCI sample, the optimal MBI-C cut-off score was 5.5 with sensitivity 0.917 and specificity 0.949. In multiple linear regression analysis, LS score was detected as a significant predictor of MBI-C total scores, and MBI-C decreased motivation, affective dysregulation, and abnormal thought and perception scores.

Conclusions

The caregiver-rated Japanese MBI-C has excellent diagnostic performance. Loneliness is associated with a greater MBI burden, especially in the decreased motivation, affective dysregulation, and abnormal thought and perception domains. Interventions for loneliness in older people may have the potential to improve MBI.

Health System Change for Alzheimer's Disease-Modifying Therapies in Canada: Beginning the Discussion

Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for 60%-70% of patients with dementia, and it is estimated that over one million Canadians will be living with dementia by 2030. Disease-modifying therapies (DMTs) targeting the underlying pathophysiology of AD are currently in development. Several models have demonstrated that the potential arrival of Alzheimer's DMTs will most likely overwhelm the already-constrained Canadian healthcare system. Canada does not have a strategy to address the extensive requirements of using DMTs, including providing an early diagnosis of AD, confirming DMT eligibility via amyloid biomarkers, and conducting ongoing treatment monitoring. Thus, a multidisciplinary group of experts involved in AD care in Canada gathered to review (1) the current barriers to diagnosis and management of AD; (2) how existing clinic models, including those used in multiple sclerosis (MS), could be applied to address key barriers in AD; and (3) how to design and implement optimal care pathways in the future. The actions outlined in this review will help clinicians and healthcare systems improve readiness to integrate the use of disease-modifying therapies in Alzheimer's disease, if such therapies are approved in Canada.

Longitudinal Associations Between Mild Behavioral Impairment, Sleep Disturbance, and Progression to Dementia

Background

Clinical guidelines recommend incorporating non-cognitive markers like mild behavioral impairment (MBI) and sleep disturbance (SD) into dementia screening to improve detection.

Objective

We investigated the longitudinal associations between MBI, SD, and incident dementia.

Methods

Participant data were from the National Alzheimer's Coordinating Center in the United States. MBI was derived from the Neuropsychiatric Inventory Questionnaire (NPI-Q) using a published algorithm. SD was determined using the NPI-Q nighttime behaviors item. Cox proportional hazard regressions with time-dependant variables for MBI, SD, and cognitive diagnosis were used to model associations between baseline 1) MBI and incident SD (n = 11,277); 2) SD and incident MBI (n = 10,535); 3) MBI with concurrent SD and incident dementia (n = 13,544); and 4) MBI without concurrent SD and incident dementia (n = 11,921). Models were adjusted for first-visit age, sex, education, cognitive diagnosis, race, and for multiple comparisons using the Benjamini-Hochberg method.

Results

The rate of developing SD was 3.1-fold higher in older adults with MBI at baseline compared to those without MBI (95% CI: 2.8-3.3). The rate of developing MBI was 1.5-fold higher in older adults with baseline SD than those without SD (95% CI: 1.3-1.8). The rate of developing dementia was 2.2-fold greater in older adults with both MBI and SD, as opposed to SD alone (95% CI:1.9-2.6).

Conclusions

There is a bidirectional relationship between MBI and SD. Older adults with SD develop dementia at higher rates when co-occurring with MBI. Future studies should explore the mechanisms underlying these relationships, and dementia screening may be improved by assessing for both MBI and SD.

Simulation of neuroplasticity in a CNN-based in-silico model of neurodegeneration of the visual system

The aim of this work was to enhance the biological feasibility of a deep convolutional neural network-based in-silico model of neurodegeneration of the visual system by equipping it with a mechanism to simulate neuroplasticity. Therefore, deep convolutional networks of multiple sizes were trained for object recognition tasks and progressively lesioned to simulate neurodegeneration of the visual cortex. More specifically, the injured parts of the network remained injured while we investigated how the added retraining steps were able to recover some of the model's object recognition baseline performance. The results showed with retraining, model object recognition abilities are subject to a smoother and more gradual decline with increasing injury levels than without retraining and, therefore, more similar to the longitudinal cognition impairments of patients diagnosed with Alzheimer's disease (AD). Moreover, with retraining, the injured model exhibits internal activation patterns similar to those of the healthy baseline model when compared to the injured model without retraining. Furthermore, we conducted this analysis on a network that had been extensively pruned, resulting in an optimized number of parameters or synapses. Our findings show that this network exhibited remarkably similar capability to recover task performance with decreasingly viable pathways through the network. In conclusion, adding a retraining step to the in-silico setup that simulates neuroplasticity improves the model's biological feasibility considerably and could prove valuable to test different rehabilitation approaches in-silico.

The impact of mild behavioral impairment on the prognosis of geriatric depression: preliminary results

Our study aimed to examine how the presence of Mild Behavioral Impairment (MBI) symptoms influenced the outcome of late-life depression (LLD). Twenty-nine elderly (≥ 60 years) depressive patients, including eleven (37.9%) with MBI, were recruited and followed-up on average for 33.41 ± 8.24 weeks. Psychiatric symptoms severity and global functioning were assessed, respectively, using the Brief Psychiatric Rating Scale (BPRS) and the Global Assessment of Functioning (GAF) scale. BPRS total score significantly decreased from baseline to follow-up (P < 0.001, d = 1.33). The presence of MBI had no significant effect on mood and cognitive symptoms improvement. On the contrary, while a significant increase in GAF score was observed in patients without MBI (P = 0.001, d = 1.01), no significant improvement of global functioning was detected in those with MBI (P = 0.154, d = 0.34) after 6-month follow-up. The presence of MBI in patients with LLD may negatively affect long-term outcome, slowing or preventing functional improvement.

Cognitive profile of people with mild behavioral impairment in Brain Health Registry participants

OBJECTIVES

Dementia assessment includes cognitive and behavioral testing with informant verification. Conventional testing is resource-intensive, with uneven access. Online unsupervised assessments could reduce barriers to risk assessment. The aim of this study was to assess the relationship between informant-rated behavioral changes and participant-completed neuropsychological test performance in older adults, both measured remotely via an online unsupervised platform, the Brain Health Registry (BHR).

DESIGN

Observational cohort study.

SETTING

Community-dwelling older adults participating in the online BHR. Informant reports were obtained using the BHR Study Partner Portal.

PARTICIPANTS

The final sample included 499 participant-informant dyads.

MEASUREMENTS

Participants completed online unsupervised neuropsychological assessment including Forward Memory Span, Reverse Memory Span, Trail Making B, and Go/No-Go tests. Informants completed the Mild Behavioral Impairment Checklist (MBI-C) via the BHR Study Partner portal. Cognitive performance was evaluated in MBI+/- individuals, as was the association between cognitive scores and MBI symptom severity.

RESULTS

Mean age of the 499 participants was 67, of which 308/499 were females (61%). MBI + status was associated with significantly lower memory and executive function test scores, measured using Forward and Reverse Memory Span, Trail Making Errors and Trail Making Speed. Further, significant associations were found between poorer objectively measured cognitive performance, in the domains of memory and executive function, and MBI symptom severity.

CONCLUSION

These findings support the feasibility of remote, informant-reported behavioral assessment utilizing the MBI-C, supporting its validity by demonstrating a relationship to online unsupervised neuropsychological test performance, using a previously validated platform capable of assessing early dementia risk markers.

Latest Canadian Consensus Conference on the Diagnosis and Treatment of Dementia: What's in It for Primary Care?

In 2020, the fifth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCCDTD5) published up-to-date recommendations for the clinical management of persons living with dementia (PLWD) and their caregivers. During the CCCDTD5 meetings, a list of recommendations for dementia care was compiled. With the aid of family physicians and the Canadian Consortium on Neurodegeneration in Aging, we selected the most relevant CCCDTD5 recommendations for primary care and tailored and summarized them in the present manuscript to facilitate their reference and use. These recommendations focus on (a) risk reduction, (b) screening and diagnosis, (c) deprescription of dementia medications, and (d) non-pharmacological interventions. The development of recommendations for the ongoing management of dementia is an iterative process as new evidence on interventions for dementia is published. These recommendations are important in the primary care setting as the entry point for PLWD into the health system.

Persistence of neuropsychiatric symptoms and dementia prognostication: A comparison of three operational case definitions of mild behavioral impairment

INTRODUCTION

We compared three operational case definitions of mild behavioral impairment (MBI) in the context of MBI prevalence estimates and dementia risk modeling.

METHODS

Participants were dementia-free older adults (n = 13701) from the National Alzheimer's Coordinating Center. Operational case definitions of MBI were generated based on neuropsychiatric symptoms at one (OV), two-consecutive (TCV), or more than two-thirds (TTV) of dementia-free study visits. Definitions were compared in prevalence and in Cox regressions using MBI to predict incident dementia.

RESULTS

OV MBI was the most prevalent (54.4%), followed by TCV (32.3%) and TTV (26.7%) MBI. However, OV MBI had the lowest rate of incident dementia (hazard ratio [HR] = 2.54, 95% confidence interval [CI]: 2.33-2.78) and generated poorer model metrics than TCV MBI (HR = 4.06, 95% CI: 3.74-4.40) and TTV MBI (HR = 5.77, 95% CI: 5.32-6.26).

DISCUSSION

Case ascertainment with longer timeframe MBI operational case definitions may more accurately define groups at risk of dementia in datasets lacking tools designed to detect MBI.Highlights: Mild behavioral impairment (MBI) can identify older adults at risk of dementia.Neuropsychiatric symptom (NPS) assessment tools can be proxy measures for MBI.Hazard for dementia was highest for MBI defined by NPS presence at more than two-thirds of visits.

Temporal associations between treated and untreated hearing loss and mild behavioral impairment in older adults without dementia

INTRODUCTION

Hearing loss (HL) and mild behavioral impairment (MBI) are non-cognitive markers of dementia. This study investigated the relationship between hearing and MBI and explored the influence of hearing aid use on the treatment of hearing loss, both cross-sectionally and longitudinally.

METHODS

Data were analyzed from National Alzheimer's Coordinating Center participants, age ≥50, dementia-free at baseline, collected between 2005 and 2022. Three self-report questions were used to generate a three-level categorical hearing variable: No-HL, Untreated-HL, and Treated-HL. MBI status was derived from the informant-rated Neuropsychiatric Inventory Questionnaire (NPI-Q) using a published algorithm. At baseline (n = 7080), logistic regression was used to examine the association between hearing status (predictor) and the presence of global and domain-specific MBI (outcome), adjusting for age, sex, cognitive diagnosis, and apolipoprotein E4 (APOE4). Cox proportional hazard models with time-dependent covariates were used to examine the effect of (1) hearing status as exposure on the rate of incident MBI (n = 5889); and (2) MBI as exposure on the rate of incident HL in those with no HL at baseline (n = 6252).

RESULTS

Cross-sectionally, participants with Untreated-HL were more likely to exhibit global MBI (adjusted odds ratio (aOR) = 1.66, 95% CI: 1.24-2.21) and individual MBI domains of social inappropriateness (aOR = 1.95, 95% CI: 1.06-3.39), affective dysregulation (aOR = 1.71, 95% CI: 1.21-2.38), and impulse dyscontrol (aOR = 1.71, 95% CI: 1.21-2.38), compared to those with No-HL. Participants with Treated-HL (i.e., hearing aid use) did not differ from No-HL for odds of global or most MBI domains, except for impulse dyscontrol (aOR = 1.38, 95% CI: 1.05-1.81). Longitudinally, we found relationships between Treated-HL and incident MBI (adjusted hazard ratio (aHR) = 1.29, 95% CI: 1.01-1.63) and between MBI and incident Untreated-HL (aHR = 1.51, 95% CI: 1.19-1.94).

DISCUSSION

Our cross-sectional results support that hearing aid use is associated with lower odds of concurrent global MBI in dementia-free participants. Longitudinally, relationships were found between MBI and HL. The severity of HL was not assessed, however, and may require further exploration.

Highlights

Hearing Loss (HL) and mild behavioral impairment (MBI) are markers of dementiaCross-sectionally: Untreated-HL was associated with global MBI burden, butHL treated with hearing aids was notWe found associations between MBI and incident Untreated-HL.

Expert elicitation of risk factors for progression to dementia in individuals with mild cognitive impairment

INTRODUCTION

This study assesses experts' beliefs about important predictors of developing dementia in persons with mild cognitive impairment (MCI).

METHODS

Structured expert elicitation, a methodology to quantify expert knowledge, was used to elicit the most important risk factors for developing dementia. We recruited 11 experts (6 neurologists, 3 geriatricians, and 2 psychiatrists). Ten experts fully participated in introductory meetings, two rounds of surveys, and discussion meetings. The data from these ten experts were utilized for this study.

RESULTS

The expert elicitation identified age, CSF analysis, fluorodeoxyglucose-positron emission tomography (FDG-PET) findings, hippocampal atrophy, MoCA (or MMSE) score, parkinsonism, apathy, psychosis, informant report of cognitive symptoms, and global atrophy as the ten most important predictors of progressing to dementia in persons with MCI.

DISCUSSION

Several dementia predictors are not routinely collected in existing registries, observational studies, or usual care. This might partially explain the low uptake of existing published dementia risk scores in clinical practice.

Characterizing mild cognitive impairment to predict incident dementia in adults with bipolar disorder: What should the benchmark be?

Objective: Although mild cognitive impairment (MCI) is generally considered a risk state for dementia, its prevalence and association with dementia are impacted by the number of tests and cut-points used to assess cognition and define "impairment," and sources of norms. Here, we investigate how these methodological variations impact estimates of incident dementia in adults with bipolar disorder (BD), a vulnerable population with pre-existing cognitive deficits and increased dementia risk. Method: Neuropsychological data from 148 adults with BD and 13,610 healthy controls (HC) were drawn from the National Alzheimer's Coordinating Center. BD participants' scores were standardized against published norms and again using regression-based norms generated from HC within the same catchment area as individual BD patients ("site-specific norms"), varying the number of within-domain tests (one vs. two) and the cut-points (-1 vs. -1.5 SD) used to operationalize MCI. Results: Site-specific norms were more sensitive to incident dementia (88.6%-94.3%) than published norms (74.3%-88.6%), but only when using a "single test" definition of impairment. Specificity (22.1%-74.3%), accuracy (37.8%-68.9%), and positive predictive values (26.1%-38.3%) were overall poor. Applying a "single test" definition of impairment resulted in better negative predictive values using site-specific (92.3%-93.3%) than published norms (83.6%-86.2%), and a substantial increase in relative risk of incident dementia relative to published norms. Conclusions: Neuropsychologists should define "impairment" as scores below -1.0 or -1.5 SD on at least two within-domain measures when using published norms to interpret cognitive performance in adults with BD.

Mild Behavioral Impairment in Psychogeriatric Patients: Clinical Features and Psychopathology Severity

The Mild Behavioral Impairment (MBI) concept was developed to determine whether late-onset persistent neuropsychiatric symptoms (NPSs) may be early manifestations of cognitive decline. Our study aims to investigate the prevalence and differentiating features of MBI with respect to major neurocognitive disorders (MNDs) and primary psychiatric disorders (PPDs). A total of 144 elderly patients who were referred to our psychogeriatric outpatient service were recruited. The severity of mental illness was evaluated by means of the Clinical Global Impression Severity scale, the severity of psychopathology was evaluated by means of the Brief Psychiatric Rating Scale (BPRS), and overall functioning was evaluated by means of the Global Assessment of Functioning scale. The sample included 73 (50.6%) patients with PPDs, 40 (27.8%) patients with MBI, and 31 (21.5%) patients with MNDs. Patients with MNDs reported the greatest severity of mental illness, the highest BPRS Total, Psychosis, Activation, and Negative Symptom scores, and the lowest functioning. Patients with MBI and PPDs had comparable levels of severity of mental illness and overall functioning, but MBI patients reported higher BPRS Total and Negative Symptom scores than PPD patients. Patients with MBI frequently reported specific clinical features, including a higher severity of apathy and motor retardation. These features merit further investigation since they may help the differential diagnosis between MBI and PPDs.

Machine learning-based prediction of longitudinal cognitive decline in early Parkinson's disease using multimodal features

Patients with Parkinson's Disease (PD) often suffer from cognitive decline. Accurate prediction of cognitive decline is essential for early treatment of at-risk patients. The aim of this study was to develop and evaluate a multimodal machine learning model for the prediction of continuous cognitive decline in patients with early PD. We included 213 PD patients from the Parkinson's Progression Markers Initiative (PPMI) database. Machine learning was used to predict change in Montreal Cognitive Assessment (MoCA) score using the difference between baseline and 4-years follow-up data as outcome. Input features were categorized into four sets: clinical test scores, cerebrospinal fluid (CSF) biomarkers, brain volumes, and genetic variants. All combinations of input feature sets were added to a basic model, which consisted of demographics and baseline cognition. An iterative scheme using RReliefF-based feature ranking and support vector regression in combination with tenfold cross validation was used to determine the optimal number of predictive features and to evaluate model performance for each combination of input feature sets. Our best performing model consisted of a combination of the basic model, clinical test scores and CSF-based biomarkers. This model had 12 features, which included baseline cognition, CSF phosphorylated tau, CSF total tau, CSF amyloid-beta1-42, geriatric depression scale (GDS) scores, and anxiety scores. Interestingly, many of the predictive features in our model have previously been associated with Alzheimer's disease, showing the importance of assessing Alzheimer's disease pathology in patients with Parkinson's disease.

Facilitators and Barriers Influencing Antipsychotic Medication Prescribing and Deprescribing Practices in Critically Ill Adult Patients: a Qualitative Study

BACKGROUND

Antipsychotic medications do not alter the incidence or duration of delirium, but these medications are frequently prescribed and continued at transitions of care in critically ill patients when they may no longer be necessary or appropriate.

OBJECTIVE

The purpose of this study was to identify and describe relevant domains and constructs that influence antipsychotic medication prescribing and deprescribing practices among physicians, nurses, and pharmacists that care for critically ill adult patients during and following critical illness.

DESIGN

We conducted qualitative semi-structured interviews with critical care and ward healthcare professionals including physicians, nurses, and pharmacists to understand antipsychotic prescribing and deprescribing practices for critically ill adult patients during and following critical illness.

PARTICIPANTS

Twenty-one interviews were conducted with 11 physicians, five nurses, and five pharmacists from predominantly academic centres in Alberta, Canada, between July 6 and October 29, 2021.

MAIN MEASURES

We used deductive thematic analysis using the Theoretical Domains Framework (TDF) to identify and describe constructs within relevant domains.

KEY RESULTS

Seven TDF domains were identified as relevant from the analysis: Social/Professional role and identity; Beliefs about capabilities; Reinforcement; Motivations and goals; Memory, attention, and decision processes; Environmental context and resources; and Beliefs about consequences. Participants reported antipsychotic prescribing for multiple indications beyond delirium and agitation including patient and staff safety, sleep management, and environmental factors such as staff availability and workload. Participants identified potential antipsychotic deprescribing strategies to reduce ongoing antipsychotic medication prescriptions for critically ill patients including direct communication tools between prescribers at transitions of care.

CONCLUSIONS

Critical care and ward healthcare professionals report several factors influencing established antipsychotic medication prescribing practices. These factors aim to maintain patient and staff safety to facilitate the provision of care to patients with delirium and agitation limiting adherence to current guideline recommendations.

Optimizing detection of Alzheimer's disease in mild cognitive impairment: a 4-year biomarker study of mild behavioral impairment in ADNI and MEMENTO

BACKGROUND

Disease-modifying drug use necessitates better Alzheimer disease (AD) detection. Mild cognitive impairment (MCI) leverages cognitive decline to identify the risk group; similarly, mild behavioral impairment (MBI) leverages behavioral change. Adding MBI to MCI improves dementia prognostication over conventional approaches of incorporating neuropsychiatric symptoms (NPS). Here, to determine if adding MBI would better identify AD, we interrogated associations between MBI in MCI, and cerebrospinal fluid biomarkers [β-amyloid (Aβ), phosphorylated-tau (p-tau), and total-tau (tau)-ATN], cross-sectionally and longitudinally.

METHODS

Data were from two independent referral-based cohorts, ADNI (mean[SD] follow-up 3.14[1.07] years) and MEMENTO (4.25[1.40] years), collected 2003-2021. Exposure was based on three-group stratification: 1) NPS meeting MBI criteria; 2) conventionally measured NPS (NPSnotMBI); and 3) noNPS. Cohorts were analyzed separately for: 1) cross-sectional associations between NPS status and ATN biomarkers (linear regressions); 2) 4-year longitudinal repeated-measures associations of MBI and NPSnotMBI with ATN biomarkers (hierarchical linear mixed-effects models-LMEs); and 3) rates of incident dementia (Cox proportional hazards regressions).

RESULTS

Of 510 MCI participants, 352 were from ADNI (43.5% females; mean [SD] age, 71.68 [7.40] years), and 158 from MEMENTO (46.2% females; 68.98 [8.18] years). In ADNI, MBI was associated with lower Aβ42 (standardized β [95%CI], -5.52% [-10.48-(-0.29)%]; p = 0.039), and Aβ42/40 (p = 0.01); higher p-tau (9.67% [3.96-15.70%]; p = 0.001), t-tau (7.71% [2.70-12.97%]; p = 0.002), p-tau/Aβ42 (p < 0.001), and t-tau/Aβ42 (p = 0.001). NPSnotMBI was associated only with lower Aβ42/40 (p = 0.045). LMEs revealed a similar 4-year AD-specific biomarker profile for MBI, with NPSnotMBI associated only with higher t-tau. MBI had a greater rate of incident dementia (HR [95%CI], 3.50 [1.99-6.17; p < 0.001). NPSnotMBI did not differ from noNPS (HR 0.96 [0.49-1.89]; p = 0.916). In MEMENTO, MBI demonstrated a similar magnitude and direction of effect for all biomarkers, but with a greater reduction in Aβ40. HR for incident dementia was 3.93 (p = 0.004) in MBI, and 1.83 (p = 0.266) in NPSnotMBI. Of MBI progressors to dementia, 81% developed AD dementia.

CONCLUSIONS

These findings support a biological basis for NPS that meet MBI criteria, the continued inclusion of MBI in NIA-AA ATN clinical staging, and the utility of MBI criteria to improve identification of patients for enrollment in disease-modifying drug trials or for clinical care.

Effects of race, baseline cognition, and APOE on the association of affective dysregulation with incident dementia: A longitudinal study of dementia-free older adults

BACKGROUND

Affective symptoms are dementia risk factors. Mild behavioral impairment (MBI) is a neurobehavioral syndrome that refines incorporation of psychiatric symptomatology into dementia prognostication by stipulating symptoms must emerge de novo in later life and persist for ≥6 months. Here, we investigated the longitudinal association of MBI-affective dysregulation with incident dementia.

METHODS

National Alzheimer Coordinating Centre participants with normal cognition (NC) or mild cognitive impairment (MCI) were included. MBI-affective dysregulation was operationalized as Neuropsychiatric Inventory Questionnaire-measured depression, anxiety, and elation at two consecutive visits. Comparators had no neuropsychiatric symptoms (no NPS) in advance of dementia. Cox proportional hazard models were implemented to assess the risk of dementia, adjusted for age, sex, years of education, race, cognitive diagnosis, and APOE-ε4 status, with interaction terms as appropriate.

RESULTS

The final sample included 3698 no-NPS (age:72.8; 62.7 % female), and 1286 MBI-affective dysregulation participants (age:75; 54.5 % female). MBI-affective dysregulation had lower dementia-free survival (p < 0.0001) and greater incidence of dementia (HR = 1.76, CI:1.48-2.08, p < 0.001) versus no NPS. Interaction analyses revealed that MBI-affective dysregulation was associated with higher dementia incidence in Black participants than White (HR = 1.70, CI:1.00-2.87, p = 0.046), NC than MCI (HR = 1.73, CI:1.21-2.48, p = 0.0028), and APOE-ε4 noncarriers than carriers (HR = 1.47, CI:1.06-2.02, p = 0.0195). Of MBI-affective dysregulation converters to dementia, 85.5 % developed Alzheimer's disease, which increased to 91.4 % in those with amnestic MCI.

LIMITATIONS

MBI-affective dysregulation was not stratified by symptom to further examine dementia risk.

CONCLUSIONS

Emergent and persistent affective dysregulation in dementia-free older adults is associated with substantial risk for dementia and should be considered in clinical assessments.

[Mild behavioral impairment checklist : English-German translation and feasibility study assessing its use in clinical practice]

BACKGROUND

The mild behavioral impairment (MBI) syndrome is defined by the emergence in later life of persistent neuropsychiatric symptoms. The MBI checklist (MBI-C) can be used for systematic detection and documentation of such symptoms.

OBJECTIVE

Development of a German version of the MBI‑C and assessment of its application in a clinical setting.

MATERIAL AND METHODS

The MBI‑C was translated from English into German in collaboration with the main author of the original version, and its practical application was then tested on a study population (n = 21) in a gerontopsychiatric inpatient clinic. Patient compliance, understanding of questions, time effort, evaluation procedure and possible discrepancy between patient and family member evaluations were assessed.

RESULTS

The German translation of the original MBI‑C obtained certification as an official version and can be downloaded at https://mbitest.org . All 34 questions were fully completed by the study population, the level of understanding of questions was good, with the mean time effort being 16 min. In some cases, significant differences between patients' and family members' responses were found.

DISCUSSION

The presence of MBI may indicate the development of an otherwise presymptomatic neurodegenerative dementia syndrome. Hence, the MBI‑C could aid in the early detection of neurodegenerative dementia. By means of the translated version of the MBI‑C presented in this study, this hypothesis can now be tested in German-speaking countries.

Elicited clinician knowledge did not improve dementia risk prediction in individuals with mild cognitive impairment

OBJECTIVES

This study aims to develop and validate a Bayesian risk prediction model that combines research cohort data with elicited expert knowledge to predict dementia progression in people with mild cognitive impairment (MCI).

STUDY DESIGN AND SETTING

This is a prognostic risk prediction modeling study based on cohort data (Alzheimer's disease neuroimaging initiative [ADNI]; n = 365) of research participants with MCI and elicited expert data. Bayesian Cox models were used to combine expert knowledge and ADNI data to predict dementia progression in people with MCI. Posterior distributions were obtained based on Gibbs sampler and the predictive performance was evaluated using ten-fold cross-validation via c-index, integrated calibration index (ICI), and integrated brier score (IBS).

RESULTS

365 people with MCI were included, mean age was 73 years (SD = 7.5), and 39% developed dementia within 3 years. When expert knowledge was incorporated, the c-index, ICI, and IBS values were 0.74 (95% CI 0.70-0.79), 0.06 (95% CI 0.05-0.08), and 0.17 (95% CI 0.14-0.19), respectively. These were similar to the model without expert knowledge data.

CONCLUSION

The addition of expert knowledge did not improve model accuracy in this ADNI sample to predict dementia progression in individuals with MCI.

Explainable classification of Parkinson's disease using deep learning trained on a large multi-center database of T1-weighted MRI datasets

INTRODUCTION

Parkinson's disease (PD) is a severe neurodegenerative disease that affects millions of people. Early diagnosis is important to facilitate prompt interventions to slow down disease progression. However, accurate PD diagnosis can be challenging, especially in the early disease stages. The aim of this work was to develop and evaluate a robust explainable deep learning model for PD classification trained from one of the largest collections of T1-weighted magnetic resonance imaging datasets.

MATERIALS AND METHODS

A total of 2,041 T1-weighted MRI datasets from 13 different studies were collected, including 1,024 datasets from PD patients and 1,017 datasets from age- and sex-matched healthy controls (HC). The datasets were skull stripped, resampled to isotropic resolution, bias field corrected, and non-linearly registered to the MNI PD25 atlas. The Jacobian maps derived from the deformation fields together with basic clinical parameters were used to train a state-of-the-art convolutional neural network (CNN) to classify PD and HC subjects. Saliency maps were generated to display the brain regions contributing the most to the classification task as a means of explainable artificial intelligence.

RESULTS

The CNN model was trained using an 85%/5%/10% train/validation/test split stratified by diagnosis, sex, and study. The model achieved an accuracy of 79.3%, precision of 80.2%, specificity of 81.3%, sensitivity of 77.7%, and AUC-ROC of 0.87 on the test set while performing similarly on an independent test set. Saliency maps computed for the test set data highlighted frontotemporal regions, the orbital-frontal cortex, and multiple deep gray matter structures as most important.

CONCLUSION

The developed CNN model, trained on a large heterogenous database, was able to differentiate PD patients from HC subjects with high accuracy with clinically feasible classification explanations. Future research should aim to investigate the combination of multiple imaging modalities with deep learning and on validating these results in a prospective trial as a clinical decision support system.

Effects of adjunctive brexpiprazole on patient life engagement in major depressive disorder: Post hoc analysis of Inventory of Depressive Symptomatology Self-Report data

BACKGROUND

Patient-reported outcomes can capture domains that are meaningful to patients, such as life engagement in major depressive disorder (MDD), which reflects life fulfillment, well-being, and participation in valued and meaningful activities. This analysis investigated the effects of brexpiprazole adjunct to antidepressant treatment (ADT) on patient life engagement over the short and long term, using the 10-item Inventory of Depressive Symptomatology Self-Report (IDS-SR₁₀) Life Engagement subscale.

METHODS

Short-term data were pooled from three 6-week, randomized, double-blind studies of ADT + brexpiprazole 2-3 mg/day versus ADT + placebo in adult outpatients with MDD (DSM-IV-TR criteria) and inadequate response to ADTs. Long-term data were from a 26-52-week, open-label extension study of ADT + brexpiprazole 0.5-3 mg/day.

RESULTS

Over 6 weeks, ADT + brexpiprazole (n = 579) showed greater improvement in IDS-SR₁₀ Life Engagement subscale score than ADT + placebo (n = 583), with a least squares mean difference of -1.19 (95% confidence limits: -1.78, -0.59; p = 0.0001; Cohen's d effect size: 0.23). Greater improvement for ADT + brexpiprazole versus ADT + placebo (p < 0.05) was also observed on eight life engagement items, with effect sizes ranging from 0.12 to 0.24. In the long-term study, mean (standard deviation) IDS-SR₁₀ Life Engagement subscale score changed by -2.4 (4.9) points to Week 26 (n = 2047), and -3.7 (5.3) points to Week 52 (n = 768), with mean improvements on all ten items.

CONCLUSIONS

Beyond its efficacy on depressive symptoms, adjunctive brexpiprazole may improve patient life engagement, thereby helping patients with MDD to achieve personally meaningful functional outcomes.

Late-life onset psychotic symptoms and incident cognitive impairment in people without dementia: Modification by genetic risk for Alzheimer's disease

Introduction

Late-life onset psychosis is associated with faster progression to dementia in cognitively normal people, but little is known about its relationship with cognitive impairment in advance of dementia.

Methods

Clinical and genetic data from 2750 people ≥50 years of age without dementia were analyzed. Incident cognitive impairment was operationalized using the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) and psychosis was rated using the Mild Behavioral Impairment Checklist (henceforth MBI-psychosis). The whole sample was analyzed before stratification on apolipoprotein E (APOE) ε4 status.

Results

In Cox proportional hazards models, MBI-psychosis had a higher hazard for cognitive impairment relative to the No Psychosis group (hazard ratio [HR]: 3.6, 95% confidence interval [CI]: 2.2-6, p < 0.0001). The hazard for MBI-psychosis was higher in APOE ε4 carriers and there was an interaction between the two (HR for interaction: 3.4, 95% CI: 1.2-9.8, p = 0.02).

Discussion

Psychosis assessment in the MBI framework is associated with incident cognitive impairment in advance of dementia. These symptoms may be particularly important in the context of APOE genotype.

Validating the Mild Behavioral Impairment Checklist in a Cognitive Clinic: Comparisons With the Neuropsychiatric Inventory Questionnaire

OBJECTIVE

To compare the utility of the Mild Behavioral Impairment-Checklist (MBI-C) and Neuropsychiatric Inventory Questionnaire (NPI-Q) to capture NPS in subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia.

METHODS

In this cross-sectional memory clinic study, linear regression models compared MBI-C (n = 474) and NPI-Q (n = 1040) scores in relation to Montreal Cognitive Assessment (MoCA) score.

RESULTS

MBI prevalence was 37% in subjective cognitive decline, 54% in mild cognitive impairment, and 62% in dementia. Worse diagnostic status was associated with higher MBI-C and NPI-Q score (P < .001), lower MoCA (P < .001), and greater age (P < .001). Higher MBI-C (β -.09; 95% CI -.13, -.05) and NPI-Q (β -.17; 95% CI -.23, -.10) scores were associated with lower MoCA scores, with psychosis most strongly associated (β -1.11; 95% CI -1.56, -.65 vs β -1.14; 95% CI -1.55, -.73).

CONCLUSIONS

The MBI-C captures global and domain-specific NPS across cognitive stages. Both the MBI-C and NPI-Q have utility in characterizing NPS.

Preliminary Validation Study of the French-Quebec Version of the Mild Behavioral Impairment Checklist

BACKGROUND

Alzheimer disease dementia may be preceded by cognitive stages during which behavioral and psychological changes can occur. More precisely, behavioral symptoms may be observed during the subjective cognitive decline (SCD) or the mild cognitive impairment (MCI) stages; these symptoms can be measured using the Mild Behavioral Impairment Checklist (MBI-C).

OBJECTIVE

To validate the French-Quebec version of the MBI-C in individuals ages 60-85 years.

METHOD

The sample included 60 participants (20 MCI, 20 SCD, 20 cognitively healthy) and their informants. To assess the discriminant validity of the MBI-C, a Kruskal-Wallis analysis with a multiple comparisons test was performed on the MBI-C Total score. To determine convergent validity, Spearman correlations were calculated between the MBI-C subscales and a set of validation tools. Finally, test-retest reliability was assessed with Spearman correlations of MBI-C scores between two test sessions.

RESULTS

All of the analyses indicated satisfactory psychometric properties for the French-Quebec version of the MBI-C.

CONCLUSION

This validation study reveals that the MBI-C can be used successfully in dementia risk assessments. From now on, the use of a validated MBI-C will be possible in the French-Quebec population.

Plasma Phosphorylated Tau at Threonine 181 and Neuropsychiatric Symptoms in Preclinical and Prodromal Alzheimer Disease

BACKGROUND AND OBJECTIVES

Plasma phosphorylated tau at threonine 181 (p-tau181), a well-validated marker of Alzheimer disease (AD) pathologic change, could be a more efficient way to diagnose AD than invasive or expensive biomarkers requiring CSF or PET. In some individuals, neuropsychiatric symptoms (NPS) are the earliest manifestation of AD, observed in advance of clear cognitive decline. However, the few studies assessing AD biomarkers in association with NPS have often had imprecision in capturing behavioral symptoms that represent sequelae of neurodegenerative disease. Thus, the mild behavioral impairment (MBI) construct was developed, framing NPS in a way to improve the precision of risk estimates for disease. MBI core criteria stipulate that NPS emerge de novo in later life and persist for at least 6 months. Here, cross-sectionally and longitudinally, we investigated associations of MBI with p-tau181, neuropsychological test performance, and incident AD.

METHODS

Cognitively unimpaired and mild cognitive impairment (MCI) Alzheimer's Disease Neuroimaging Initiative participants were selected. MBI status was derived from the Neuropsychiatric Inventory (NPI) using a published algorithm. NPI total scores at baseline and year 1 visits were used to operationalize MBI (score >0 at both visits), NPS not meeting the MBI criteria (NPS-not-MBI, score >0 at only 1 visit), and no NPS (score = 0 at both visits). Linear regressions were fitted for cross-sectional analyses; multilevel linear mixed-effects and Cox proportional hazards models were implemented to examine the longitudinal associations of MBI with changes in p-tau181 and cognition and incident dementia.

RESULTS

The sample included 571 participants (age 72.2 years, 46.8% female, 64.8% MCI). Cross-sectionally (β = 8.1%, 95% CI 1.4%-15.2%, p = 0.02), MBI was associated with higher plasma p-tau181 levels compared with no NPS; NPS-not-MBI was not. Longitudinally, MBI was associated with higher p-tau181 (β = 0.014%, 95% CI 0.003-0.026, p = 0.02), in addition to a decline in memory and executive function. Survival analyses demonstrated a 3.92-fold greater dementia incidence in MBI, with no significant differences between NPS-not-MBI and no NPS.

DISCUSSION

These findings extend the evidence base that MBI is associated with elevated risk of cognitive decline and dementia and a sequela of emerging Alzheimer-related proteinopathies. MBI offers a substantial improvement over current approaches that explore behavior as a proxy marker for Alzheimer-related proteinopathies, with both clinical and AD trial enrichment implications.

Assessment of patient life engagement in major depressive disorder using items from the Inventory of Depressive Symptomatology Self-Report (IDS-SR)

BACKGROUND

Patient-reported outcomes can measure domains that are personally meaningful, such as life engagement, which reflects motivation, pleasure, and well-being. This study explored whether certain items from the Inventory of Depressive Symptomatology Self-Report (IDS-SR) can capture patient life engagement in major depressive disorder (MDD).

METHODS

IDS-SR life engagement items were identified by a) a panel of expert psychiatrists (n = 4), b) patient interviews (n = 20), and c) a principal component analysis (PCA) to explore clustering of items. Psychometric analyses were performed on potential subscales, and a minimal clinically important difference (MCID) was estimated by anchor- and distribution-based methods. IDS-SR data were obtained from three randomized controlled trials of adjunctive brexpiprazole in MDD.

RESULTS

Expert psychiatrists selected 10 items by consensus from the IDS-SR that might capture patient life engagement (Cronbach's alpha, 0.82; item-total correlations, 0.36-0.58). Patient interviews identified 13 items as moderately to very relevant to life engagement (Cronbach's alpha, 0.85; item-total correlations, 0.35-0.61). The PCA revealed a cluster that included all 10 items selected by psychiatrists and 11 items identified by patients. Expert psychiatrists intentionally distinguished life engagement and core depressive symptoms, although patient insights and the PCA indicated that these aspects of MDD are strongly linked. The 10-item IDS-SR life engagement subscale had an MCID of 3-5 points.

CONCLUSIONS

Different approaches consistently identified a subset of 10 IDS-SR items that can measure life engagement in MDD, which may be suitable to group into an IDS-SR life engagement subscale.

Comparison of the accuracy of the 7-item HADS Depression subscale and 14-item total HADS for screening for major depression: A systematic review and individual participant data meta-analysis

The seven-item Hospital Anxiety and Depression Scale Depression subscale (HADS-D) and the total score of the 14-item HADS (HADS-T) are both used for major depression screening. Compared to the HADS-D, the HADS-T includes anxiety items and requires more time to complete. We compared the screening accuracy of the HADS-D and HADS-T for major depression detection. We conducted an individual participant data meta-analysis and fit bivariate random effects models to assess diagnostic accuracy among participants with both HADS-D and HADS-T scores. We identified optimal cutoffs, estimated sensitivity and specificity with 95% confidence intervals, and compared screening accuracy across paired cutoffs via two-stage and individual-level models. We used a 0.05 equivalence margin to assess equivalency in sensitivity and specificity. 20,700 participants (2,285 major depression cases) from 98 studies were included. Cutoffs of ≥7 for the HADS-D (sensitivity 0.79 [0.75, 0.83], specificity 0.78 [0.75, 0.80]) and ≥15 for the HADS-T (sensitivity 0.79 [0.76, 0.82], specificity 0.81 [0.78, 0.83]) minimized the distance to the top-left corner of the receiver operating characteristic curve. Across all sets of paired cutoffs evaluated, differences of sensitivity between HADS-T and HADS-D ranged from -0.05 to 0.01 (0.00 at paired optimal cutoffs), and differences of specificity were within 0.03 for all cutoffs (0.02-0.03). The pattern was similar among outpatients, although the HADS-T was slightly (not nonequivalently) more specific among inpatients. The accuracy of HADS-T was equivalent to the HADS-D for detecting major depression. In most settings, the shorter HADS-D would be preferred. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Distinguishing apathy from depression: A review differentiating the behavioral, neuroanatomic, and treatment-related aspects of apathy from depression in neurocognitive disorders

OBJECTIVES

This narrative review describes the clinical features of apathy and depression in individuals with neurocognitive disorders (NCDs), with the goal of differentiating the two syndromes on the basis of clinical presentation, diagnostic criteria, neuropathological features, and contrasting responses to treatments.

METHODS

Literature was identified using PubMed, with search terms to capture medical conditions of interest; additional references were also included based on our collective experience and knowledge of the literature.

RESULTS

Evidence from current literature supports the distinction between the two disorders; apathy and depression occur with varying prevalence in individuals with NCDs, pose different risks of progression to dementia, and have distinct, if overlapping, neurobiological underpinnings. Although apathy is a distinct neuropsychiatric syndrome, distinguishing apathy from depression can be challenging, as both conditions may occur concurrently and share several overlapping features. Apathy is associated with unfavorable outcomes, especially those with neurodegenerative etiologies (e.g., Alzheimer's disease) and is associated with an increased burden for both patients and caregivers. Diagnosing apathy is important not only to serve as the basis for appropriate treatment, but also for the development of novel targeted interventions for this condition. Although there are currently no approved pharmacologic treatments for apathy, the research described in this review supports apathy as a distinct neuropsychiatric condition that warrants specific treatments aimed at alleviating patient disability.

CONCLUSIONS

Despite differences between these disorders, both apathy and depression pose significant challenges to patients, their families, and caregivers; better diagnostics are needed to develop more tailored treatment and support.