Hanneke Frederica Maria Rhodius-Meester

Background: The concepts of ‘ personalized medicine ’ and ‘ patient-orchestrated care ’ in Alzheimer's disease (AD) lack standard conceptualization, which presents challenges for collaborative and interdisciplinary care. Objective: We explored the interpretations and perspectives of professionals involved in interdisciplinary work on a large-scale project, “ABOARD”, with the aim to implement personalized medicine and patient-orchestrated care in AD. Methods: Semi-structured interviews were conducted with 30 professionals and audio-recorded. Two researchers independently coded the data inductively, followed by a thematic analysis. Results: According to professionals across different disciplinary backgrounds (mean age 45.7 years; 53.3% female), personalized medicine pertains to the relevant options that an individual has, informed by biomedical and psychosocial factors, whereas patient-orchestrated care captures factors relevant to the decision-making process. Professionals differed in their views on patient-orchestrated care regarding its desirability and feasibility. The concepts were viewed as similar by professionals, as both involve personal preferences while ultimately assigning responsibility to the clinician. However, implementation challenges persist, and no thematic differences were found between clinicians and other AD-related professionals. Conclusions: AD professionals have shared interpretations and perspectives on implementation of personalized medicine but differed in their views on patient-orchestrated care. Personal preferences are seen as part of personalized medicine , but not yet reflected in definitions in the AD field and beyond. Critical discussions on the challenges and existing doubts are necessary for both personalized medicine and patient-orchestrated care . Multi-level implementation changes are needed for both concepts, which warrants stakeholder involvement as well as support and resources from the entire AD field.

Background: The increasing dementia prevalence and potential introduction of disease‐modifying therapies (DMTs) highlight the need for efficient diagnostic pathways. Clear recommendations to guide the choice of diagnostic tests are lacking and may vary depending on different clinical scenarios. We used a data‐driven approach to identify efficient and effective stepwise diagnostic testing for three clinical scenarios: 1) syndrome diagnosis, 2) etiological diagnosis, 3) potential eligibility for DMT.Method: We used data from two memory clinic cohorts (ADC, PredictND), including 504 patients with dementia (302 Alzheimer’s disease, 107 frontotemporal dementia, 35 vascular dementia, 60 dementia with Lewy bodies), 191 patients with mild cognitive impairment, and 188 cognitively healthy controls (CN). Tests included digital cognitive screening (cCOG), neuropsychological and functional assessment (NP), MRI with automated quantification, and CSF biomarkers. Sequential testing followed a predetermined order (Figure 1). Subsequent tests were conducted if the diagnosis remained uncertain. Diagnostic certainty was ascertained through a data‐driven clinical decision support system (CDSS) that generated a disease state index probability score (DSI, 0‐1), indicating the probability of each diagnosis. Diagnosis was confirmed if the DSI exceeded a predefined threshold, set based on sensitivity/specificity cutoffs relevant for each clinical scenario and step. We assessed correct diagnoses and the need for additional testing at each step.Result: For syndrome diagnosis, stepwise testing (cCOG, NP, MRI) accurately identified 71% of the patients, with NP needed in 42%, and MRI in 31%. For etiological diagnosis, starting with cognitive testing to rule out dementia resulted in the need for MRI in 84% of cases, including 91% of dementia patients and 25% CN. Subsequent MRI reduced CSF required to 29%, ultimately diagnosing 81% of patients with 71% accuracy. In determining DMT eligibility, stepwise testing (cCOG, NP, MRI) correctly identified 91% of potential eligible patients for confirmatory CSF testing, while only 51% of ineligible patients.Conclusion: Depending on the setting, alternative diagnostic pathways are accurate and efficient. As such, a data‐driven tool can assist clinicians in selecting tests of added value across different clinical contexts. This becomes especially important with DMT availability, where the need for more efficient diagnostic pathways is crucial to maintain accessibility and affordability of diagnoses.

Background: The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. Methods: We included 286 subjects (135 controls, 108 Alzheimer’s disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [¹⁸F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. Results: The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). Conclusion: Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup.

Cognitive testing is an essential part of clinical diagnostics and clinical trials in Alzheimer’s disease. Digital cognitive tests hold a great opportunity to provide more versatile and cost-efficient patient pathways through flexible testing including at home. In this work, we describe a web-based cognitive test, cCOG, that can be used in screening, differential diagnosis, and monitoring the progression of neurodegenerative diseases. Key words Cognitive testing Alzheimer’s disease Neurodegenerative diseases Digital biomarkers

Objectives: Vascular cognitive impairment is the second most common type of cognitive impairment. Care needs of community-dwelling people with vascular cognitive impairment and their caregivers have not been thoroughly studied. Therefore, we aimed to explore care needs of people with vascular cognitive impairment and their family caregivers. Design: A qualitative interview study. Setting and participants: Participants were purposefully sampled community-dwelling people with vascular cognitive impairment and their family caregivers. Methods: Interviews were audiotaped and transcribed verbatim. Analysis and data collection followed an iterative process, until data saturation was achieved. We conducted 18 interviews (nine people with vascular cognitive impairment and nine caregivers), concerning 13 unique people with vascular cognitive impairment. We analyzed the data using inductive thematic analysis following the Braun & Clark method. The study was reported in accordance with the COREQ criteria. Findings: Five themes were identified in the care needs reported by people with vascular cognitive impairment and family caregivers: (1) Specific information need with subtheme (1A) No memory problem, no dementia? (2) Being respected as a person, (3) Differing concerns about the future, (4) The roles of the caregiver and (5) Decisiveness from professional healthcare. Conclusions and implications: The care needs of people with vascular cognitive impairment and their caregivers were affected by (a lack of knowledge about) the characteristic symptoms of this condition. Participants equated cognitive impairment or dementia to memory loss (“Alzheimerization”), although memory loss was not their biggest challenge. People with vascular cognitive impairment and caregivers preferred resolute and decisive healthcare professionals. These professionals activate the person with vascular cognitive impairment who lacks initiative and diminishe role conflict of the caregiver. Care for people with vascular cognitive impairment and their caregivers could be improved by providing tailored information, promoting awareness of neuropsychiatric symptoms, particularly apathy, and by healthcare professionals providing more guidance in decision-making.

Introduction: Clear communication of diagnostic test results and dementia diagnosis is challenging yet important to empower patients and care partners. A personalized diagnostic report could support the communication of dementia diagnostics and aid patients’ understanding of diagnosis. In this study, we aimed to design a diagnostic report in co‐creation with patients and care partners.Methods: We used a mixed‐methods approach, combining surveys with focus groups in iteration. Phase 1 consisted of an international survey assessing needs among patients (n= 50) and care partners (n= 46), and phase 2 consisted of focus group meetings (n= 3) to co‐create the content and to hands‐on co‐design the layout of the diagnostic report with patients (n= 7) and care partners (n= 7). Phase 3 validated results from phase 2 in a survey among patients (n= 28) and care partners (n= 12), and phase 4 comprised final feedback by dementia (care) experts (n= 5). Descriptive statistics were used to report quantitative results and directed content analysis was used to analyze qualitative data.Results: Most patients (39/50, 78%) and care partners (38/46, 83%) positively valued a diagnostic report to summarize test results. The report should be brief, straightforward, and comprise results of the diagnostic tests, including brain imaging and information on future expectations. Despite a clear preference for visual display of test results, several visualization options were deemed best and were equally comprehended.Discussion: In this study, we developed a prototype of a personalized patient report through an iterative design process and learned that co‐creation is highly valuable to meet the specific needs of end‐users.

Objective: Orthostatic hypotension (OH) is a common condition associated with an increased mortality risk. This study investigates this association specifically in geriatric outpatients and additionally ocuses on the duration and magnitude of OH. Design and method: In this observational prospective cohort study with geriatric outpatients from the Amsterdam Ageing cohort, we differentiated OH in Early OH (EOH) and delayed/prolonged OH (DPOH). The magnitude of drop in both systolic and diastolic blood pressure (BP) after either 1 or 3 minutes was quantified. Mortality data was obtained from the Dutch municipal register. Cox proportional hazard models were used to determine the association between OH and mortality, adjusted for sex and age (model 1), additionally adjusted for OH-inducing drugs and SBP (model 2) and the presence of cardiovascular disease and diabetes (model 3). Stratified analyses in patients with geriatric deficits were performed. Results: We included 1240 patients (mean age 79.4 ± 6.9years, 52.6% females). Prevalence of OH was 443 (34.9%); 148 (11.9%) patients had EOH and 285 (23.0%) DPOH. DPOH was associated with a higher mortality risk (HR,95%CI: 1.69(1.28–2.22)) whereas EOH was not associated with mortality risk. This association did not differ in patients with geriatric deficits. Furthermore, the magnitude of drop in both systolic and diastolic BP was associated with a higher mortality risk (see figure for results of SBP). Conclusions: The presence of DPOH and the magnitude of both systolic and diastolic OH are related to an increased mortality risk in geriatric outpatients. Whether the duration of OH and magnitude of the drop in blood pressure is causally related to mortality risk or whether it is a sign of decreased resilience remains to be elucidated.

Background: The disease trajectory of patients with young onset dementia differs from older patients, as do healthcare requirements. To improve specialized care, more insight in young onset dementia is crucial. The aim of PRECODE‐GP is therefore 1) to conduct an (annual) inventory of the diagnostic workup in all memory clinics in the Netherlands, and 2) to set up a prospective nationwide database including newly diagnosed younger patients with dementia.Methods: PRECODE‐GP is part of the PRECODE project, a collaboration between four Dutch Alzheimer centers, Knowledgecenter Dementia at Young Age, Nivel and Alzheimer Nederland. Governance is embedded in the Dutch Memory Clinic Network. Memory clinics are asked annually to fill out a survey on their current diagnostic workup. Eligible patients (<70 years; any type of dementia) are identified by local specialists and recruited via an informed consent procedure providing consent for future linkage to other datasets. Demographics, test results and (etiological) diagnosis are collected in an online database.Results: PRECODE‐GP was initiated in July 2019 and has been approved in 36 memory clinics, approval procedure is ongoing in additional 10 clinics. Based on the annual survey (filled out by 21 clinics), standard imaging of the brain occurs in almost half of memory clinics and neuropsychological examination in one third. CSF is performed when deemed necessary by the clinician. A median 250(141‐396) new patients visited the memory clinics yearly, of whom 111(74‐180)(48%) were diagnosed with dementia and 12(4‐36)(6%) were <70 years. To date, 201 young onset dementia patients (age 62±8, 51% female, MMSE 22±5) are included in our prospective database, diagnosed with 140(69%) Alzheimer’s dementia (AD), 29(14%) frontotemporal dementia (FTD), 14(7%) dementia with Lewy Bodies (DLB) and 18(9%) other dementia types. Patients with FTD were youngest (61±6 years), subjects with DLB were most often male (79%), in AD MMSE was lowest (21±5).Conclusion: We took the first step to include patients with young onset dementia via all Dutch memory clinics. As a next step, we plan to link data to existing registries, to gain valuable knowledge on disease trajectories. All needed to improve quality of life for patients with young onset dementia.

Background: Computer tools based on artificial intelligence could aid clinicians in memory clinics in several ways, such as by supporting diagnostic decision-making, web-based cognitive testing, and the communication of diagnosis and prognosis. Objective: This study aims to identify the preferences as well as the main barriers and facilitators related to using computer tools in memory clinics for all end users, that is, clinicians, patients, and care partners. Methods: Between July and October 2020, we sent out invitations to a web-based survey to clinicians using the European Alzheimer’s Disease Centers network and the Dutch Memory Clinic network, and 109 clinicians participated (mean age 45 years, SD 10; 53/109, 48.6% female). A second survey was created for patients and care partners. They were invited via Alzheimer Europe, Alzheimer’s Society United Kingdom, Amsterdam Dementia Cohort, and Amsterdam Aging Cohort. A total of 50 patients with subjective cognitive decline, mild cognitive impairment, or dementia (mean age 73 years, SD 8; 17/34, 34% female) and 46 care partners (mean age 65 years, SD 12; 25/54, 54% female) participated in this survey. Results: Most clinicians reported a willingness to use diagnostic (88/109, 80.7%) and prognostic (83/109, 76.1%) computer tools. User-friendliness (71/109, 65.1%); Likert scale mean 4.5, SD 0.7), and increasing diagnostic accuracy (76/109, 69.7%; mean 4.3, SD 0.7) were reported as the main factors stimulating the adoption of a tool. Tools should also save time and provide clear information on reliability and validity. Inadequate integration with electronic patient records (46/109, 42.2%; mean 3.8, SD 1.0) and fear of losing important clinical information (48/109, 44%; mean 3.7, SD 1.2) were most frequently indicated as barriers. Patients and care partners were equally positive about the use of computer tools by clinicians, both for diagnosis (69/96, 72%) and prognosis (73/96, 76%). In addition, most of them thought favorably regarding the possibility of using the tools themselves. Conclusions: This study showed that computer tools in memory clinics are positively valued by most end users. For further development and implementation, it is essential to overcome the technical and practical barriers of a tool while paying utmost attention to its reliability and validity.