Dementia diagnosis relationships to age, education, exercise, and medications

2013 ◽  
Author(s):  
Joy Ladwig ◽  
Jeralee Salmon
Keyword(s):  
Dementia Diagnosis

A Brave New World for Dementia Diagnosis

PsycCRITIQUES ◽  
2007 ◽  
Vol 52 (35) ◽  
Author(s):  
F. Richard Ferraro
Keyword(s):  
New World ◽  
Dementia Diagnosis ◽  
Brave New World

Jazz, dementia, and moments of meeting

2020 ◽  
Vol 10 (1) ◽  
pp. 87-92
Author(s):  
Kate White
Keyword(s):  
Personal Account ◽  
Dementia Diagnosis ◽  
Emotional Connection ◽  
The Gift ◽  
Creative Force ◽  
Family Living

Playful jazz improvisations and singing continue in creating the gift of emotional connection in a family living with Alzheimer’s. Sharing their poignant reflections provides a personal account of the centrality of music in reaching each other at a feeling level throughout the course of their lives. The recognition of music as a powerful and creative force for all of us, particularly when there is a dementia diagnosis, is explored.

Mining Social Media Data to Study the Consequences of Dementia Diagnosis on Caregivers and Relatives (Preprint)

2018 ◽  
Author(s):  
Anika Oellrich ◽  
George Gkotsis ◽  
Richard James Butler Dobson ◽  
Tim JP Hubbard ◽  
Rina Dutta
Keyword(s):  
Social Media ◽  
Family Relationships ◽  
Text Processing ◽  
Automated Analysis ◽  
Health Concern ◽  
Dementia Diagnosis ◽  
Data Set ◽  
Social Media Data ◽  
Real Time Processing ◽  
Media Data

BACKGROUND Dementia is a growing public health concern with approximately 50 million people affected worldwide in 2017 and this number is expected to reach more than 131 million by 2050. The toll on caregivers and relatives cannot be underestimated as dementia changes family relationships, leaves people socially isolated, and affects the finances of all those involved. OBJECTIVE The aim of this study was to explore using automated analysis (i) the age and gender of people who post to the social media forum Reddit about dementia diagnoses, (ii) the affected person and their diagnosis, (iii) relevant subreddits authors are posting to, (iv) the types of messages posted and (v) the content of these posts. METHODS We analysed Reddit posts concerning dementia diagnoses. We used a previously developed text analysis pipeline to determine attributes of the posts as well as their authors to characterise online communications about dementia diagnoses. The posts were also examined by manual curation for the diagnosis provided and the person affected. Furthermore, we investigated the communities these people engage in and assessed the contents of the posts with an automated topic gathering technique. RESULTS Our results indicate that the majority of posters in our data set are women, and it is mostly close relatives such as parents and grandparents that are mentioned. Both the communities frequented and topics gathered reflect not only the sufferer's diagnosis but also potential outcomes, e.g. hardships experienced by the caregiver. The trends observed from this dataset are consistent with findings based on qualitative review, validating the robustness of social media automated text processing. CONCLUSIONS This work demonstrates the value of social media data sources as a resource for in-depth studies of those affected by a dementia diagnosis and the potential to develop novel support systems based on their real time processing in line with the increasing digitalisation of medical care.

scholarly journals Predicting dementia diagnosis from cognitive footprints in electronic health records: a case–control study protocol

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e043487
Author(s):  
Hao Luo ◽  
Kui Kai Lau ◽  
Gloria H Y Wong ◽  
Wai-Chi Chan ◽  
Henry K F Mak ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Hong Kong ◽  
Electronic Health Records ◽  
Case Control Study ◽  
Case Control ◽  
Dementia Diagnosis ◽  
Health Records ◽  
Electronic Health ◽  
Control Study

IntroductionDementia is a group of disabling disorders that can be devastating for persons living with it and for their families. Data-informed decision-making strategies to identify individuals at high risk of dementia are essential to facilitate large-scale prevention and early intervention. This population-based case–control study aims to develop and validate a clinical algorithm for predicting dementia diagnosis, based on the cognitive footprint in personal and medical history.Methods and analysisWe will use territory-wide electronic health records from the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong between 1 January 2001 and 31 December 2018. All individuals who were at least 65 years old by the end of 2018 will be identified from CDARS. A random sample of control individuals who did not receive any diagnosis of dementia will be matched with those who did receive such a diagnosis by age, gender and index date with 1:1 ratio. Exposure to potential protective/risk factors will be included in both conventional logistic regression and machine-learning models. Established risk factors of interest will include diabetes mellitus, midlife hypertension, midlife obesity, depression, head injuries and low education. Exploratory risk factors will include vascular disease, infectious disease and medication. The prediction accuracy of several state-of-the-art machine-learning algorithms will be compared.Ethics and disseminationThis study was approved by Institutional Review Board of The University of Hong Kong/Hospital Authority Hong Kong West Cluster (UW 18-225). Patients’ records are anonymised to protect privacy. Study results will be disseminated through peer-reviewed publications. Codes of the resulted dementia risk prediction algorithm will be made publicly available at the website of the Tools to Inform Policy: Chinese Communities’ Action in Response to Dementia project (https://www.tip-card.hku.hk/).

Global Perspectives on Brief Cognitive Assessments for Dementia Diagnosis

2021 ◽  
pp. 1-13
Author(s):  
Elena Tsoy ◽  
Alissa Bernstein Sideman ◽  
Stefanie D. Piña Escudero ◽  
Maritza Pintado-Caipa ◽  
Suchanan Kanjanapong ◽  
...  
Keyword(s):  
Older Adult ◽  
Adult Population ◽  
Dementia Diagnosis ◽  
Cognitive Assessments ◽  
Middle Income ◽  
Global Perspectives ◽  
Dementia Patients ◽  
Diagnosis Of Dementia ◽  
Theme Identification ◽  
Diagnostic Decision Making

Background: Timely diagnosis of dementia is a global healthcare priority, particularly in low to middle income countries where rapid increases in older adult populations are expected. Objective: To investigate global perspectives on the role of brief cognitive assessments (BCAs) in dementia diagnosis, strengths and limitations of existing measures, and future directions and needs. Methods: This is a qualitative study of 18 dementia experts from different areas of the world. Participants were selected using purposeful sampling based on the following criteria: 1) practicing in countries with projected growth of older adult population of over 100%by 2050; 2) expertise in dementia diagnosis and treatment; 3) involvement in clinical practice and training; and 4) recognition as a national dementia expert based on leadership positions within healthcare system, research, and/or policy work. Participants were individually interviewed in their language of choice over secure videoconference sessions. Interviews were analyzed by a multidisciplinary team using theme identification approach. Results: Four domains with subthemes emerged illustrating participants’ perspectives: 1) strengths of BCAs; 2) limitations of BCAs; 3) needs related to the use of BCAs; and 4) characteristics of an ideal BCA. While most experts agreed that BCAs were important and useful for dementia diagnosis, the themes emphasized the need for development and validation of novel measures that are sensitive, psychometrically sound, and culturally appropriate. Conclusion: BCAs are important for guiding diagnosis and care for dementia patients. Findings provide a roadmap for novel BCA development to assist in diagnostic decision making for clinicians serving a rapidly growing and diverse dementia population.

scholarly journals Interrater agreement in dementia diagnosis: a systematic review and meta‐analysis

2021 ◽  
Author(s):  
Enzo Cerullo ◽  
Terry J Quinn ◽  
Jenny McCleery ◽  
Elpida Vounzoulaki ◽  
Nicola J Cooper ◽  
...  
Keyword(s):  
Systematic Review ◽  
Meta Analysis ◽  
Interrater Agreement ◽  
Dementia Diagnosis

scholarly journals Cognitive dispersion and ApoEe4 genotype predict dementia diagnosis in 8-year follow-up of the oldest-old

2020 ◽  
Author(s):  
Tam Watermeyer ◽  
Jantje Goerdten ◽  
Boo Johansson ◽  
Graciela Muniz-Terrera
Keyword(s):  
Cognitive Performance ◽  
Cox Regression ◽  
Oldest Old ◽  
Cost Effective ◽  
Carrier Status ◽  
Dementia Diagnosis ◽  
Cognitive Domains ◽  
Dementia Incidence ◽  
Composite Scores

Abstract Background Cognitive dispersion, or inconsistencies in performance across cognitive domains, has been posited as a cost-effective tool to predict conversion to dementia in older adults. However, there is a dearth of studies exploring cognitive dispersion in the oldest-old (>80 years) and its relationship to dementia incidence. Objective The main aim of this study was to examine whether higher cognitive dispersion at baseline was associated with dementia incidence within an 8-year follow-up of very old adults, while controlling for established risk factors and suggested protective factors for dementia. Methods Participants (n = 468) were from the Origins of Variance in the Old-Old: Octogenarian Twins study, based on the Swedish Twin Registry. Cox regression analyses were performed to assess the association between baseline cognitive dispersion scores and dementia incidence, while controlling for sociodemographic variables, ApoEe4 carrier status, co-morbidities, zygosity and lifestyle engagement scores. An additional model included a composite of average cognitive performance. Results Cognitive dispersion and ApoEe4 were significantly associated with dementia diagnosis. These variables remained statistically significant when global cognitive performance was entered into the model. Likelihood ratio tests revealed that cognitive dispersion and cognitive composite scores entered together in the same model was superior to either predictor alone in the full model. Conclusions The study underscores the usefulness of cognitive dispersion metrics for dementia prediction in the oldest-old and highlights the influence of ApoEe4 on cognition in very late age. Our findings concur with others suggesting that health and lifestyle factors pose little impact upon cognition in very advanced age.

Suicide risk in first year after dementia diagnosis in older adults

2021 ◽  
Author(s):  
Timothy Schmutte ◽  
Mark Olfson ◽  
Donovan T. Maust ◽  
Ming Xie ◽  
Steven C. Marcus
Keyword(s):  
Older Adults ◽  
Suicide Risk ◽  
First Year ◽  
Dementia Diagnosis
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