Recommendations for clinical implementation of blood-based biomarkers for Alzheimer's disease.

Blood-based biomarkers (BBM) for Alzheimer's disease (AD) are being increasingly used in clinical practice to support an AD diagnosis. In contrast to traditional diagnostic modalities, such as amyloid positron emission tomography and cerebrospinal fluid biomarkers, BBMs offer a more accessible and lower cost alternative for AD biomarker testing. Their unique scalability addresses the anticipated surge in demand for biomarker testing with the emergence of disease-modifying treatments (DMTs) that require confirmation of amyloid pathology. To facilitate the uptake of BBMs in clinical practice, The Global CEO Initiative on Alzheimer's Disease convened a BBM Workgroup to provide recommendations for two clinical implementational pathways for BBMs: one for current use for triaging and another for future use to confirm amyloid pathology. These pathways provide a standardized diagnostic approach with guidance on interpreting BBM test results. Integrating BBMs into clinical practice will simplify the diagnostic process and facilitate timely access to DMTs for eligible patients.

The Alzheimer's Disease Neuroimaging Initiative Neuropathology Core: An update.

INTRODUCTION: Biomarkers for Alzheimer's disease neuropathologic change (ADNC) have been instrumental in developing effective disease-modifying therapeutics. However, to prevent/treat dementia effectively, we require biomarkers for non-AD neuropathologies; for this, neuropathologic examinations and annotated tissue samples are essential. METHODS: We conducted clinicopathologic correlation for the first 100 Alzheimer's Disease Neuroimaging Initiative (ADNI) Neuropathology Core (NPC) cases. RESULTS: Clinical syndromes in this cohort showed 95% sensitivity and 79% specificity for predicting high/intermediate ADNC, a 21% false positive rate, and a ∼44% false negative rate. In addition, 60% with high/intermediate ADNC harbored additional potentially dementing co-pathologies. DISCUSSION: These results suggest that clinical presentation imperfectly predicts ADNC and that accurate prediction of high/intermediate ADNC does not exclude co-pathology that may modify presentation, biomarkers, and therapeutic responses. Therefore, new biomarkers are needed for non-AD neuropathologies. The ADNI NPC supports this mission with well-characterized tissue samples (available through ADNI and the National Institute on Aging) and "gold-standard" diagnostic information (soon to include digital histology). HIGHLIGHTS: The Alzheimer's Disease Neuroimaging Initiative (ADNI) Neuropathology Core (NPC) brain donation cohort now exceeds 200 cases. ADNI NPC data in National Alzheimer's Coordinating Center format are available through the Laboratory of Neuro Imaging. Digitized slide files from the ADNI NPC will be available in 2025. Requests for ADNI brain tissue samples can be submitted online for ADNI/National Institute on Aging evaluation. Clinical diagnoses of Alzheimer's disease (AD)/AD and related dementias (ADRD) do not always predict post mortem neuropathology. Neuropathology is essential for the development of novel AD/ADRD biomarkers.

Considerations for widespread implementation of blood-based biomarkers of Alzheimer's disease.

Diagnosing Alzheimer's disease (AD) poses significant challenges to health care, often resulting in delayed or inadequate patient care. The clinical integration of blood-based biomarkers (BBMs) for AD holds promise in enabling early detection of pathology and timely intervention. However, several critical considerations, such as the lack of consistent guidelines for assessing cognition, limited understanding of BBM test characteristics, insufficient evidence on BBM performance across diverse populations, and the ethical management of test results, must be addressed for widespread clinical implementation of BBMs in the United States. The Global CEO Initiative on Alzheimer's Disease BBM Workgroup convened to address these challenges and provide recommendations that underscore the importance of evidence-based guidelines, improved training for health-care professionals, patient empowerment through informed decision making, and the necessity of community-based studies to understand BBM performance in real-world populations. Multi-stakeholder engagement is essential to implement these recommendations and ensure credible guidance and education are accessible to all stakeholders.

Implementation and validation of face de-identification (de-facing) in ADNI4.

INTRODUCTION: Recent technological advances have increased the risk that de-identified brain images could be re-identified from face imagery. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a leading source of publicly available de-identified brain imaging, who quickly acted to protect participants' privacy. METHODS: An independent expert committee evaluated 11 face-deidentification ("de-facing") methods and selected four for formal testing. RESULTS: Effects of de-facing on brain measurements were comparable across methods and sufficiently small to recommend de-facing in ADNI. The committee ultimately recommended mri_reface for advantages in reliability, and for some practical considerations. ADNI leadership approved the committee's recommendation, beginning in ADNI4. DISCUSSION: ADNI4 de-faces all applicable brain images before subsequent pre-processing, analyses, and public release. Trained analysts inspect de-faced images to confirm complete face removal and complete non-modification of brain. This paper details the history of the algorithm selection process and extensive validation, then describes the production workflows for de-facing in ADNI. HIGHLIGHTS: ADNI is implementing "de-facing" of MRI and PET beginning in ADNI4. "De-facing" alters face imagery in brain images to help protect privacy. Four algorithms were extensively compared for ADNI and mri_reface was chosen. Validation confirms mri_reface is robust and effective for ADNI sequences. Validation confirms mri_reface negligibly affects ADNI brain measurements.

Clinicians' use of Health Information Exchange technologies for medication reconciliation in the U.S. Department of Veterans Affairs: a qualitative analysis.

BACKGROUND: Medication reconciliation is essential for optimizing medication use. In part to promote effective medication reconciliation, the Department of Veterans Affairs (VA) invested substantial resources in health information exchange (HIE) technologies. The objectives of this qualitative study were to characterize VA clinicians' use of HIE tools for medication reconciliation in their clinical practice and to identify facilitators and barriers. METHODS: We recruited inpatient and outpatient prescribers (physicians, nurse practitioners, physician assistants) and pharmacists at four geographically distinct VA medical centers for observations and interviews. Participants were observed as they interacted with HIE or medication reconciliation tools during routine work. Participants were interviewed about clinical decision-making pertaining to medication reconciliation and use of HIE tools, and about barriers and facilitators to use of the tools. Qualitative data were analyzed via inductive and deductive approaches using a priori codes. RESULTS: A total of 63 clinicians participated. Over half (58%) were female, and the mean duration of VA clinical experience was 7 (range 0-32) years. Underlying motivators for clinicians seeking data external to their VA medical center were having new patients, current patients receiving care from an external institution, and clinicians' concerns about possible medication discrepancies among institutions. Facilitators for using HIE software were clinicians' familiarity with the HIE software, clinicians' belief that medication information would be available within HIE, and their confidence in the ability to find HIE medication-related data of interest quickly. Six overarching barriers to HIE software use for medication coordination included visual clutter and information overload within the HIE display; challenges with HIE interface navigation; lack of integration between HIE and other electronic health record interfaces, necessitating multiple logins and application switching; concerns with the dependability of HIE medication information; unfamiliarity with HIE tools; and a lack of HIE data from non-VA facilities. CONCLUSIONS: This study is believed to be the first to qualitatively characterize clinicians' HIE use with respect to medication reconciliation. Results inform recommendations to optimize HIE use for medication management activities. We expect that healthcare organizations and software vendors will be able to apply the findings to develop more effective and usable HIE information displays.

Ethnic differences in the prevalence of amyloid positivity and cognitive trajectories.

INTRODUCTION: We investigated the prevalence of amyloid beta (Aß) positivity (+) and cognitive trajectories in Koreans and non-Hispanic Whites (NHWs). METHODS: We included 5121 Koreans from multiple centers across South Korea and 929 NHWs from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Participants underwent Aß positron emission tomography and were categorized into cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia stages. Age, sex, education, and apolipoprotein E. genotype were adjusted using multivariable logistic regression and stabilized inverse probability of treatment weights based on the propensity scores to mitigate imbalances in these variables. RESULTS: The prevalence of Aß+ was lower in CU Koreans than in CU NHWs (adjusted odds ratio 0.60). Aß+ Koreans showed a faster cognitive decline than Aß+ NHWs in the CU (B = -0.314, p = .004) and MCI stages (B = -0.385, p < .001). DISCUSSION: Ethnic characteristics of Aß biomarkers should be considered in research and clinical application of Aß-targeted therapies in diverse populations. HIGHLIGHTS: Koreans have a lower prevalence of Aß positivity compared to NHWs in the CU stage. The effects of Alzheimer's risk factors on Aß positivity differ between Koreans and NHWs. Aß-positive (Aß+) Koreans show faster cognitive decline than Aß+ NHWs in the CU and MCI stages.

Inefficient Processes and Associated Factors in Primary Care Nursing: System Configuration Analysis.

BACKGROUND: Industrywide, primary care nurses' work is increasing in complexity and team orientation. Mobile health information technologies (HITs) designed to aid nurses with indirect care tasks, including charting, have had mixed success. Failed introductions of HIT may be explained by insufficient integration into nurses' work processes, owing to an incomplete or incorrect understanding of the underlying work systems. Despite this need for context, published evidence has focused more on inpatient settings than on primary care. OBJECTIVE: This study aims to characterize nurses' and health technicians' perceptions of process inefficiencies in the primary care setting and identify related work system factors. METHODS: Guided by the Systems Engineering Initiative for Patient Safety (SEIPS) 2.0 model, we conducted an exploratory work system analysis with a convenience sample of primary care nurses and health technicians. Semistructured contextual interviews were conducted in 2 sets of primary care clinics in the Midwestern United States, one in an urban tertiary care center and the other in a rural community-based outpatient facility. Using directed qualitative content analysis of transcripts, we identified tasks participants perceived as frequent, redundant, or difficult, related processes, and recommendations for improvement. In addition, we conducted configuration analyses to identify associations between process inefficiencies and work system factors. RESULTS: We interviewed a convenience sample of 20 primary care nurses and 2 health technicians, averaging approximately 12 years of experience in their current role. Across sites, participants perceived 2 processes, managing patient calls and clinic walk-in visits, as inefficient. Among work system factors, participants described organizational and technological factors associated with inefficiencies. For example, new organization policies to decrease patient waiting invoked frequent, repetitive, and difficult tasks, including chart review and check-in using tablet computers. Participants reported that issues with policy implementation and technology usability contributed to process inefficiencies. Organizational and technological factors were also perceived among participants as the most adaptable. Suggested technology changes included new tools for walk-in triage and patient self-reporting of symptoms. CONCLUSIONS: In response to changes to organizational policy and technology, without compensative changes elsewhere in their primary care work system, participants reported process adaptations. These adaptations indicate inefficient work processes. Understanding how the implementation of organizational policies affects other factors in the primary care work system may improve the quality of such implementations and, in turn, increase the effectiveness and efficiency of primary care nurse processes. Furthermore, the design and implementation of HIT interventions should consider influential work system factors and their effects on work processes.

Validity and reliability of the Mobile Toolbox Faces and Names memory test.

Validation of the Mobile Toolbox Faces and Names associative memory test is presented. Ninety-two participants self-administered Faces and Names in-person; 956 self-administered Faces and Names remotely but took convergent measures in person; and 123 self-administered Faces and Names remotely twice, 14 days apart. Internal consistency (.76-.79) and test-retest reliability (ICC = .73) were acceptable. Convergent validity with WMS-IV Verbal Paired Associates was satisfactory (immediate .54; delayed .58). The findings suggest the remotely administered Faces and Names is a reliable instrument.

Anxiety in late-life depression is associated with poorer performance across multiple cognitive domains.

OBJECTIVE: Anxiety is a common comorbid feature of late-life depression (LLD) and is associated with poorer global cognitive functioning independent of depression severity. However, little is known about whether comorbid anxiety is associated with a domain-specific pattern of cognitive dysfunction. We therefore examined group differences (LLD with and without comorbid anxiety) in cognitive functioning performance across multiple domains. METHOD: Older adults with major depressive disorder (N = 228, ages 65-91) were evaluated for anxiety and depression severity, and cognitive functioning (learning, memory, language, processing speed, executive functioning, working memory, and visuospatial functioning). Ordinary least squares regression adjusting for age, sex, education, and concurrent depression severity examined anxiety group differences in performance on tests of cognitive functioning. RESULTS: Significant group differences emerged for confrontation naming and visuospatial functioning, as well as for verbal fluency, working memory, and inhibition with lower performance for LLD with comorbid anxiety compared to LLD only, controlling for depression severity. CONCLUSIONS: Performance patterns identified among older adults with LLD and comorbid anxiety resemble neuropsychological profiles typically seen in neurodegenerative diseases of aging. These findings have potential implications for etiological considerations in the interpretation of neuropsychological profiles.

Overview of ADNI MRI.

The magnetic resonance imaging (MRI) Core has been operating since Alzheimer's Disease Neuroimaging Initiative's (ADNI) inception, providing 20 years of data including reliable, multi-platform standardized protocols, carefully curated image data, and quantitative measures provided by expert investigators. The overarching purposes of the MRI Core include: (1) optimizing and standardizing MRI acquisition methods, which have been adopted by many multicenter studies and trials worldwide and (2) providing curated images and numeric summary values from relevant MRI sequences/contrasts to the scientific community. Over time, ADNI MRI has become increasingly complex. To remain technically current, the ADNI MRI protocol has changed substantially over the past two decades. The ADNI 4 protocol contains nine different imaging types (e.g., three dimensional [3D] T1-weighted and fluid-attenuated inversion recovery [FLAIR]). Our view is that the ADNI MRI data are a greatly underutilized resource. The purpose of this paper is to educate the scientific community on ADNI MRI methods and content to promote greater awareness, accessibility, and use. HIGHLIGHTS: The MRI Core provides multi-platform standardized protocols, carefully curated image data, and quantitative analysis by expert groups. The ADNI MRI protocol has undergone major changes over the past two decades to remain technically current. As of April 25, 2024, the following numbers of image series are available: 17,141 3D T1w; 6877 FLAIR; 3140 T2/PD; 6623 GRE; 3237 dMRI; 2846 ASL; 2968 TF-fMRI; and 2861 HighResHippo (see Table 1 for abbreviations). As of April 25, 2024, the following numbers of quantitative analyses are available: FreeSurfer 10,997; BSI 6120; tensor based morphometry (TBM) and TBM-SYN 12,019; WMH 9944; dMRI 1913; ASL 925; TF-fMRI NFQ 2992; and medial temporal subregion volumes 2726 (see Table 4 for abbreviations). ADNI MRI is an underutilized resource that could be more useful to the research community.

Storyteller in ADNI4: Application of an early Alzheimer's disease screening tool using brief, remote, and speech-based testing.

INTRODUCTION: Speech-based testing shows promise for sensitive and scalable objective screening for Alzheimer's disease (AD), but research to date offers limited evidence of generalizability. METHODS: Data were taken from the AMYPRED (Amyloid Prediction in Early Stage Alzheimer's Disease from Acoustic and Linguistic Patterns of Speech) studies (N = 101, N = 46 mild cognitive impairment [MCI]) and Alzheimer's Disease Neuroimaging Initiative 4 (ADNI4) remote digital (N = 426, N = 58 self-reported MCI, mild AD or dementia) and in-clinic (N = 57, N = 13 MCI) cohorts, in which participants provided audio-recorded responses to automated remote story recall tasks in the Storyteller test battery. Text similarity, lexical, temporal, and acoustic speech feature sets were extracted. Models predicting early AD were developed in AMYPRED and tested out of sample in the demographically more diverse cohorts in ADNI4 (> 33% from historically underrepresented populations). RESULTS: Speech models generalized well to unseen data in ADNI4 remote and in-clinic cohorts. The best-performing models evaluated text-based metrics (text similarity, lexical features: area under the curve 0.71-0.84 across cohorts). DISCUSSION: Speech-based predictions of early AD from Storyteller generalize across diverse samples. HIGHLIGHTS: The Storyteller speech-based test is an objective digital prescreener for Alzheimer's Disease Neuroimaging Initiative 4 (ADNI4). Speech-based models predictive of Alzheimer's disease (AD) were developed in the AMYPRED (Amyloid Prediction in Early Stage Alzheimer's Disease from Acoustic and Linguistic Patterns of Speech) sample (N = 101). Models were tested out of sample in ADNI4 in-clinic (N = 57) and remote (N = 426) cohorts. Models showed good generalization out of sample. Models evaluating text matching and lexical features were most predictive of early AD.

The ADNI4 Digital Study: A novel approach to recruitment, screening, and assessment of participants for AD clinical research.

INTRODUCTION: We evaluated preliminary feasibility of a digital, culturally-informed approach to recruit and screen participants for the Alzheimer's Disease Neuroimaging Initiative (ADNI4). METHODS: Participants were recruited using digital advertising and completed digital surveys (e.g., demographics, medical exclusion criteria, 12-item Everyday Cognition Scale [ECog-12]), Novoic Storyteller speech-based cognitive test). Completion rates and assessment performance were compared between underrepresented populations (URPs: individuals from ethnoculturally minoritized or low education backgrounds) and non-URPs. RESULTS: Of 3099 participants who provided contact information, 654 enrolled in the cohort, and 595 completed at least one assessment. Two hundred forty-seven participants were from URPs. Of those enrolled, 465 met ADNI4 inclusion criteria and 237 evidenced possible cognitive impairment from ECog-12 or Storyteller performance. URPs had lower ECog and Storyteller completion rates. Scores varied by ethnocultural group and educational level. DISCUSSION: Preliminary results demonstrate digital recruitment and screening assessment of an older diverse cohort, including those with possible cognitive impairment, are feasible. Improving engagement and achieving educational diversity are key challenges. HIGHLIGHTS: A total of 654 participants enrolled in a digital cohort to facilitate ADNI4 recruitment. Culturally-informed digital ads aided enrollment of underrepresented populations. From those enrolled, 42% were from underrepresented ethnocultural and educational groups. Digital screening tools indicate > 50% of participants likely cognitively impaired. Completion rates and assessment performance vary by ethnocultural group and education.

Design and validation of the ADNI MR protocol.

Phase four of the Alzheimer's Disease Neuroimaging Initiative (ADNI4) magnetic resonance imaging (MRI) protocols aim to maintain longitudinal consistency across two decades of data acquisition, while adopting new technologies. Here we describe and justify the study's design and targeted biomarkers. The ADNI4 MRI protocol includes nine MRI sequences. Some sequences require the latest hardware and software system upgrades and are continuously rolled out as they become available at each site. The main sequence additions/changes in ADNI4 are: (1) compressed sensing (CS) T1-weighting, (2) pseudo-continuous arterial spin labeling (ASL) on all three vendors (GE, Siemens, Philips), (3) multiple-post-labeling-delay ASL, (4) 1 mm3 isotropic 3D fluid-attenuated inversion recovery, and (5) CS 3D T2-weighted. ADNI4 aims to help the neuroimaging community extract valuable imaging biomarkers and provide a database to test the impact of advanced imaging strategies on diagnostic accuracy and disease sensitivity among individuals lying on the cognitively normal to impaired spectrum. HIGHLIGHTS: A summary of MRI protocols for phase four of the Alzheimer's Disease Neuroimaging Initiative (ADNI 4). The design and justification for the ADNI 4 MRI protocols. Compressed sensing and multi-band advances have been applied to improve scan time. ADNI4 protocols aim to streamline safety screening and therapy monitoring. The ADNI4 database will be a valuable test bed for academic research.

Standardized statistical framework for comparison of biomarkers: Techniques from ADNI.

INTRODUCTION: Well-chosen biomarkers have the potential to increase the efficiency of clinical trials and drug discovery and should show good precision as well as clinical validity. METHODS: We suggest measures that operationalize these criteria and describe a general approach that can be used for inference-based comparisons of biomarker performance. The methods are applied to measures obtained from structural magnetic resonance imaging (MRI) from individuals with mild dementia (n = 70) or mild cognitive impairment (MCI; n = 303) enrolled in the Alzheimer's Disease Neuroimaging Initiative. RESULTS: Ventricular volume and hippocampal volume showed the best precision in detecting change over time in both individuals with MCI and with dementia. Differences in clinical validity varied by group. DISCUSSION: The methodology presented provides a standardized framework for comparison of biomarkers across modalities and across different methods used to generate similar measures and will help in the search for the most promising biomarkers. HIGHLIGHTS: A framework for comparison of biomarkers on pre-defined criteria is presented. Criteria for comparison include precision in capturing change and clinical validity. Ventricular volume has high precision in change for both dementia and mild cognitive impairment (MCI) trials. Imaging measures' performance in clinical validity varies more for dementia than for MCI.

A Protocol for the Inclusion of Minoritized Persons in Alzheimer Disease Research From the ADNI3 Diversity Taskforce.

Importance: Black or African American (hereinafter, Black) and Hispanic or Latino/a/x (hereinafter, Latinx) adults are disproportionally affected by Alzheimer disease, but most research studies do not enroll adequate numbers of both of these populations. The Alzheimer's Disease Neuroimaging Initiative-3 (ADNI3) launched a diversity taskforce to pilot a multipronged effort to increase the study inclusion of Black and Latinx older adults. Objective: To describe and evaluate the culturally informed and community-engaged inclusion efforts to increase the screening and enrollment of Black and Latinx older adults in ADNI3. Design, Setting, and Participants: This cross-sectional study used baseline data from a longitudinal, multisite, observational study conducted from January 15, 2021, to July 12, 2022, with no follow-up. The study was conducted at 13 ADNI3 sites in the US. Participants included individuals aged 55 to 90 years without cognitive impairment and those with mild cognitive impairment or Alzheimer disease. Exposures: Efforts included (1) launch of an external advisory board, (2) changes to the study protocol, (3) updates to the digital prescreener, (4) selection and deployment of 13 community-engaged research study sites, (5) development and deployment of local and centralized outreach efforts, and (6) development of a community-science partnership board. Main Outcomes and Measures: Screening and enrollment numbers from centralized and local outreach efforts, digital advertisement metrics, and digital prescreener completion. Results: A total of 91 participants enrolled in the trial via centralized and local outreach efforts, of which 22 (24.2%) identified as Latinx and 55 (60.4%) identified as Black (median [IQR] age, 65.6 [IQR, 61.5-72.5] years; 62 women [68.1%]). This represented a 267.6% increase in the monthly rate of enrollment (before: 1.11 per month; during: 4.08 per month) of underrepresented populations. For the centralized effort, social media advertisements were run between June 1, 2021, and July 31, 2022, which resulted in 2079 completed digital prescreeners, of which 1289 met criteria for subsequent site-level screening. Local efforts were run between June 1, 2021, to July 31, 2022. A total of 151 participants underwent site-level screening (100 from local efforts, 41 from centralized efforts, 10 from other sources). Conclusions and Relevance: In this cross-sectional study of pilot inclusion efforts, a culturally informed, community-engaged approach increased the inclusion of Black and Latinx participants in an Alzheimer disease cohort study.

Mobile toolbox (MTB) remote measures of executive function and processing speed: development and validation.

OBJECTIVE: The ability to remotely monitor cognitive skills is increasing with the ubiquity of smartphones. The Mobile Toolbox (MTB) is a new measurement system that includes measures assessing Executive Functioning (EF) and Processing Speed (PS): Arrow Matching, Shape-Color Sorting, and Number-Symbol Match. The purpose of this study was to assess their psychometric properties. METHOD: MTB measures were developed for smartphone administration based on constructs measured in the NIH Toolbox® (NIHTB). Psychometric properties of the resulting measures were evaluated in three studies with participants ages 18 to 90. In Study 1 (N = 92), participants completed MTB measures in the lab and were administered both equivalent NIH TB measures and other external measures of similar cognitive constructs. In Study 2 (N = 1,021), participants completed the equivalent NIHTB measures in the lab and then took the MTB measures on their own, remotely. In Study 3 (N = 168), participants completed MTB measures twice remotely, two weeks apart. RESULTS: All three measures exhibited very high internal consistency and strong test-retest reliability, as well as moderately high correlations with comparable NIHTB tests and moderate correlations with external measures of similar constructs. Phone operating system (iOS vs. Android) had a significant impact on performance for Arrow Matching and Shape-Color Sorting, but no impact on either validity or reliability. CONCLUSIONS: Results support the reliability and convergent validity of MTB EF and PS measures for use across the adult lifespan in remote, self-administered designs.

Accuracy, thoroughness, and quality of outpatient primary care documentation in the U.S. Department of Veterans Affairs.

BACKGROUND: Electronic health records (EHRs) can accelerate documentation and may enhance details of notes, or complicate documentation and introduce errors. Comprehensive assessment of documentation quality requires comparing documentation to what transpires during the clinical encounter itself. We assessed outpatient primary care notes and corresponding recorded encounters to determine accuracy, thoroughness, and several additional key measures of documentation quality. METHODS: Patients and primary care clinicians across five midwestern primary care clinics of the US Department of Veterans Affairs were recruited into a prospective observational study. Clinical encounters were video-recorded and transcribed verbatim. Using the Physician Documentation Quality Instrument (PDQI-9) added to other measures, reviewers scored quality of the documentation by comparing transcripts to corresponding encounter notes. PDQI-9 items were scored from 1 to 5, with higher scores indicating higher quality. RESULTS: Encounters (N = 49) among 11 clinicians were analyzed. Most issues that patients initiated in discussion were omitted from notes, and nearly half of notes referred to information or observations that could not be verified. Four notes lacked concluding assessments and plans; nine lacked information about when patients should return. Except for thoroughness, PDQI-9 items that were assessed achieved quality scores exceeding 4 of 5 points. CONCLUSIONS: Among outpatient primary care electronic records examined, most issues that patients initiated in discussion were absent from notes, and nearly half of notes referred to information or observations absent from transcripts. EHRs may contribute to certain kinds of errors. Approaches to improving documentation should consider the roles of the EHR, patient, and clinician together.

Evolution of white matter hyperintensity segmentation methods and implementation over the past two decades; an incomplete shift towards deep learning.

This systematic review examines the prevalence, underlying mechanisms, cohort characteristics, evaluation criteria, and cohort types in white matter hyperintensity (WMH) pipeline and implementation literature spanning the last two decades. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we categorized WMH segmentation tools based on their methodologies from January 1, 2000, to November 18, 2022. Inclusion criteria involved articles using openly available techniques with detailed descriptions, focusing on WMH as a primary outcome. Our analysis identified 1007 visual rating scales, 118 pipeline development articles, and 509 implementation articles. These studies predominantly explored aging, dementia, psychiatric disorders, and small vessel disease, with aging and dementia being the most prevalent cohorts. Deep learning emerged as the most frequently developed segmentation technique, indicative of a heightened scrutiny in new technique development over the past two decades. We illustrate observed patterns and discrepancies between published and implemented WMH techniques. Despite increasingly sophisticated quantitative segmentation options, visual rating scales persist, with the SPM technique being the most utilized among quantitative methods and potentially serving as a reference standard for newer techniques. Our findings highlight the need for future standards in WMH segmentation, and we provide recommendations based on these observations.

Structural brain differences in the Alzheimer's disease continuum: Insights into the heterogeneity from a large multi-site neuroimaging consortium.

INTRODUCTION: Neurodegenerative diseases require collaborative, multi-site research to comprehensively grasp their complex and diverse pathological progression, yet there is caution in aggregating global data due to data heterogeneity. The current study investigates brain structure across stages of Alzheimer's disease (AD), and how relationships vary across sources of heterogeneity. METHODS: Using 6 international datasets(n>27,000), associations of structural neuroimaging markers were investigated in relation to the AD continuum via meta-analysis. We investigated whether associations varied across elements of MRI acquisition, study design and populations. RESULTS: Modest differences in associations were found dependent on how data were acquired, however patterns were similar. Preliminary results suggest neuroimaging marker-AD relationships differ across ethnic groups. DISCUSSION: Diversity in data offers unique insights into the neural substrate of AD, however harmonised processing and transparency of data collection is needed. Global collaborations should embrace inherent heterogeneity that exists within the data and quantify its contribution to research findings at the meta-analytical stage.

Association of CSF α-Synuclein Seed Amplification Assay Positivity with Disease Progression and Cognitive Decline: A Longitudinal Alzheimer's Disease Neuroimaging Initiative Study.

INTRODUCTION: CSF α-synuclein seed amplification assay (SAA) is a sensitive and specific tool for detecting Lewy body (LB) co-pathology in AD. METHODS: 1637 cross-sectional and 407 longitudinal CSF samples from ADNI were tested with SAA. We examined longitudinal dynamics of Aß, α-synuclein seeds, and p-tau181, along with global and domain-specific cognition in stable SAA+, stable SAA-, and those who converted to SAA+ from SAA-. RESULTS: SAA+ individuals had faster cognitive decline than SAA-, notably in MCI, and presented with earlier symptom onset. SAA+ conversion was associated with CSF Aß42-positivity but did not impact progression of either Aß42 or p-tau181 status. Aß42, p-tau181, and α-syn SAA were all strong predictors of clinical progression, particularly Aß42. In vitro α-syn SAA kinetic parameters were associated with participant demographics, clinical profiles, and cognitive decline. DISCUSSION: These results highlight the interplay between Aß and α-synuclein and their association with disease progression.