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Lott SA, Streel E, Bachman SL, Bode K, Dyer J, Fitzer-Attas C, Goldsack JC, Hake A, Jannati A, Fuertes RS, Fromy P. Digital Health Technologies for Alzheimer's Disease and Related Dementias: Initial Results from a Landscape Analysis and Community Collaborative Effort. J Prev Alzheimers Dis 2024; 11:1480-1489. [PMID: 39350395 PMCID: PMC11436391 DOI: 10.14283/jpad.2024.103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2024]
Abstract
Digital health technologies offer valuable advantages to dementia researchers and clinicians as screening tools, diagnostic aids, and monitoring instruments. To support the use and advancement of these resources, a comprehensive overview of the current technological landscape is essential. A multi-stakeholder working group, convened by the Digital Medicine Society (DiMe), conducted a landscape review to identify digital health technologies for Alzheimer's disease and related dementia populations. We searched studies indexed in PubMed, Embase, and APA PsycInfo to identify manuscripts published between May 2003 to May 2023 reporting analytical validation, clinical validation, or usability/feasibility results for relevant digital health technologies. Additional technologies were identified through community outreach. We collated peer-reviewed manuscripts, poster presentations, or regulatory documents for 106 different technologies for Alzheimer's disease and related dementia assessment covering diverse populations such as Lewy Body, vascular dementias, frontotemporal dementias, and all severities of Alzheimer's disease. Wearable sensors represent 32% of included technologies, non-wearables 61%, and technologies with components of both account for the remaining 7%. Neurocognition is the most prevalent concept of interest, followed by physical activity and sleep. Clinical validation is reported in 69% of evidence, analytical validation in 34%, and usability/feasibility in 20% (not mutually exclusive). These findings provide clinicians and researchers a landscape overview describing the range of technologies for assessing Alzheimer's disease and related dementias. A living library of technologies is presented for the clinical and research communities which will keep findings up-to-date as the field develops.
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Affiliation(s)
- S A Lott
- Sarah Averill Lott, Digital Medicine Society (DiMe), Boston, MA, USA, , 970-408-0780
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Wang Y, Chen T, Wang C, Ogihara A, Ma X, Huang S, Zhou S, Li S, Liu J, Li K. A New Smart 2-Min Mobile Alerting Method for Mild Cognitive Impairment Due to Alzheimer's Disease in the Community. Brain Sci 2023; 13:brainsci13020244. [PMID: 36831787 PMCID: PMC9954272 DOI: 10.3390/brainsci13020244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 01/29/2023] [Accepted: 01/29/2023] [Indexed: 02/04/2023] Open
Abstract
The early identification of mild cognitive impairment (MCI) due to Alzheimer's disease (AD), in an early stage of AD can expand the AD warning window. We propose a new capability index evaluating the spatial execution process (SEP), which can dynamically evaluate the execution process in the space navigation task. The hypothesis is proposed that there are neurobehavioral differences between normal cognitive (NC) elderly and AD patients with MCI reflected in digital biomarkers captured during SEP. According to this, we designed a new smart 2-min mobile alerting method for MCI due to AD, for community screening. Two digital biomarkers, total mission execution distance (METRtotal) and execution distance above the transverse obstacle (EDabove), were selected by step-up regression analysis. For the participants with more than 9 years of education, the alerting efficiency of the combination of the two digital biomarkers for MCI due to AD could reach 0.83. This method has the advantages of fast speed, high alerting efficiency, low cost and high intelligence and thus has a high application value for community screening in developing countries. It also provides a new intelligent alerting approach based on the human-computer interaction (HCI) paradigm for MCI due to AD in community screening.
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Affiliation(s)
- Yujia Wang
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou 310053, China
- Zhejiang-Japan Digital Diagnosis and Treatment and Equipment of Integrated Traditional Chinese Medicine and Western Medicine for Major Brain Diseases Joint Laboratory, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Tong Chen
- Department of Neurology, The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing 100853, China
| | - Chen Wang
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou 310053, China
- Zhejiang-Japan Digital Diagnosis and Treatment and Equipment of Integrated Traditional Chinese Medicine and Western Medicine for Major Brain Diseases Joint Laboratory, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Atsushi Ogihara
- Zhejiang-Japan Digital Diagnosis and Treatment and Equipment of Integrated Traditional Chinese Medicine and Western Medicine for Major Brain Diseases Joint Laboratory, Zhejiang Chinese Medical University, Hangzhou 310053, China
- Department of Health Sciences and Social Welfare, Faculty of Human Sciences, Waseda University, Tokorozawa 359-1162, Japan
| | - Xiaowen Ma
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou 310053, China
- Zhejiang-Japan Digital Diagnosis and Treatment and Equipment of Integrated Traditional Chinese Medicine and Western Medicine for Major Brain Diseases Joint Laboratory, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Shouqiang Huang
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou 310053, China
- Zhejiang-Japan Digital Diagnosis and Treatment and Equipment of Integrated Traditional Chinese Medicine and Western Medicine for Major Brain Diseases Joint Laboratory, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Siyu Zhou
- Zhejiang-Japan Digital Diagnosis and Treatment and Equipment of Integrated Traditional Chinese Medicine and Western Medicine for Major Brain Diseases Joint Laboratory, Zhejiang Chinese Medical University, Hangzhou 310053, China
- School of Public Health, Hangzhou Normal University, Hangzhou 311121, China
| | - Shuwu Li
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou 310053, China
- Zhejiang-Japan Digital Diagnosis and Treatment and Equipment of Integrated Traditional Chinese Medicine and Western Medicine for Major Brain Diseases Joint Laboratory, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Jiakang Liu
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou 310053, China
- Zhejiang-Japan Digital Diagnosis and Treatment and Equipment of Integrated Traditional Chinese Medicine and Western Medicine for Major Brain Diseases Joint Laboratory, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Kai Li
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou 310053, China
- Zhejiang-Japan Digital Diagnosis and Treatment and Equipment of Integrated Traditional Chinese Medicine and Western Medicine for Major Brain Diseases Joint Laboratory, Zhejiang Chinese Medical University, Hangzhou 310053, China
- Correspondence:
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Tarnanas I, Tsolaki M. Making Pre-screening for Alzheimer's Disease (AD) and Postoperative Delirium Among Post-Acute COVID-19 Syndrome (PACS) a National Priority: The Deep Neuro Study. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1424:41-47. [PMID: 37486477 DOI: 10.1007/978-3-031-31982-2_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
SARS-CoV-2 effects on cognition are a vibrant area of active research. Many researchers suggest that COVID-19 patients with severe symptoms leading to hospitalization sustain significant neurodegenerative injury, such as encephalopathy and poor discharge disposition. However, despite some post-acute COVID-19 syndrome (PACS) case series that have described elevated neurodegenerative biomarkers, no studies have been identified that directly compared levels to those in mild cognitive impairment, non-PACS postoperative delirium patients after major non-emergent surgery, or preclinical Alzheimer's disease (AD) patients that have clinical evidence of Alzheimer's without symptoms. According to recent estimates, there may be 416 million people globally on the AD continuum, which include approximately 315 million people with preclinical AD. In light of all the above, a more effective application of digital biomarker and explainable artificial intelligence methodologies that explored amyloid beta, neuronal, axonal, and glial markers in relation to neurological complications in-hospital or later outcomes could significantly assist progress in the field. Easy and scalable subjects' risk stratification is of utmost importance, yet current international collaboration initiatives are still challenging due to the limited explainability and accuracy to identify individuals at risk or in the earliest stages that might be candidates for future clinical trials. In this open letter, we propose the administration of selected digital biomarkers previously discovered and validated in other EU-funded studies to become a routine assessment for non-PACS preoperative cognitive impairment, PACS neurological complications in-hospital, or later PACS and non-PACS improvement in cognition after surgery. The open letter also includes an economic analysis of the implications for such national-level initiatives. Similar collaboration initiatives could have existing pre-diagnostic detection and progression prediction solutions pre-screen the stage before and around diagnosis, enabling new disease manifestation mapping and pushing the field into unchartered territory.
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Affiliation(s)
- Ioannis Tarnanas
- Altoida Inc, Washington, DC, USA.
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland.
- Atlantic Fellow for Equity in Brain Health, Global Brain Health Institute, University of California San Francisco, San Francisco, CA, USA.
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago de Chile, Santiago, Chile.
| | - Magda Tsolaki
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
- 1st University Department of Neurology UH "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
- Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI - AUTh) Balkan Center, Buildings A & B, Aristotle University of Thessaloniki, Thessaloniki, Greece
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Tarnanas I, Tsolaki M. Making pre-screening for Alzheimer's disease (AD) and Postoperative delirium among post-acute COVID-19 syndrome - (PACS) a national priority: The Deep Neuro Study. OPEN RESEARCH EUROPE 2022; 2:98. [PMID: 37767224 PMCID: PMC10521085 DOI: 10.12688/openreseurope.15005.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/16/2022] [Indexed: 09/29/2023]
Abstract
SARS-CoV-2 effects on cognition is a vibrant area of active research. Many researchers suggest that COVID-19 patients with severe symptoms leading to hospitalization, sustain significant neurodegenerative injury, such as encephalopathy and poor discharge disposition. However, despite some post-acute COVID-19 syndrome (PACS) case series that have described elevated neurodegenerative biomarkers, no studies have been identified that directly compared levels to those in mild cognitive impairment, non-PACS postoperative delirium patients after major non-emergent surgery or preclinical Alzheimer's Disease (AD) patients, that have clinical evidence of Alzheimer's without symptoms. According to recent estimates, there may be 416 million people globally on the AD continuum, which include approximately 315 million people with preclinical AD. In light of all the above, a more effective application of digital biomarker and explainable artificial intelligence methodologies that explored amyloid beta, neuronal, axonal, and glial markers in relation to neurological complications in-hospital or later outcomes could significantly assist progress in the field. Easy and scalable subjects' risk stratification is of utmost importance, yet current international collaboration initiatives are still challenging due to the limited explainability and accuracy to identify individuals at risk or in the earliest stages that might be candidates for future clinical trials. In this open letter, we propose the administration of selected digital biomarkers previously discovered and validated in other EU funded studies to become a routine assessment for non-PACS preoperative cognitive impairment, PACS neurological complications in-hospital or later PACS and non-PACS improvement in cognition after surgery. The open letter also includes an economic analysis of the implications for such national level initiatives. Similar collaboration initiatives could have existing prediagnostic detection and progression prediction solutions pre-screen the stage before and around diagnosis, enabling new disease manifestation mapping and pushing the field into unchartered territory.
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Affiliation(s)
- Ioannis Tarnanas
- Altoida Inc, Washington DC, 20003, USA
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
- Atlantic Fellow for Equity in Brain Health, University of California San Francisco, San Francisco, USA
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago de Chile, Chile
| | - Magda Tsolaki
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
- 1st University Department of Neurology UH “AHEPA”, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
- Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI - AUTh) Balkan Center, Aristotle University of Thessaloniki, Buildings A & B, Thessaloniki, Greece
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