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Record W4213217769 · doi:10.1007/s40120-022-00335-x

The Humanistic and Economic Burden of Alzheimer's Disease

2022· review· en· W4213217769 on OpenAlexaff
Amir Abbas Tahami Monfared, Michael Byrnes, Leigh Ann White, Quanwu Zhang

Bibliographic record

VenueNeurology and Therapy · 2022
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University Health Centre
FundersEisai
KeywordsQuality of life (healthcare)DementiaMedicineCaregiver burdenDiseaseGerontologyCognitionDisease burdenActivities of daily livingComorbidityClinical psychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Alzheimer's disease (AD) is the leading cause of cognitive impairment and dementia in older individuals (aged ≥ 65 years) throughout the world. As a result of these progressive deficits in cognitive, emotional, and physical function, AD dementia can cause functional disability and loss of independence. To gain a deeper understanding of the recent literature on the burden of AD, including that of mild cognitive impairment (MCI) due to AD, we conducted a comprehensive targeted review of the PubMed-indexed literature (2014 to 2021) to examine the humanistic and economic burden of AD (including MCI) in North America, Europe, and Asia. Our literature review identified a range of factors associated with quality of life (QoL): some factors were positively associated with QoL, including caregiver relationship, religiosity, social engagement, and ability to engage in activities of daily living (ADL), whereas other factors such as neuropsychiatric symptoms were associated with poorer QoL. While patient- and proxy-rated QoL are highly correlated in patients with early AD dementia, proxy-rated QoL declines more substantially as severity worsens. The maintenance of self-reported QoL in patients with more severe AD dementia may be due to lack of awareness or to adaptation to circumstances. Compared to persons with normal cognition, MCI is associated with a greater cost burden, and individuals with MCI exhibit worse QoL. Key drivers of the societal economic burden of AD include disease severity, dependence level, institutionalization, and comorbidity burden. Evaluation of the impact of a hypothetical disease-modifying treatment delaying the progression from MCI to AD has suggested that such a treatment may result in cost savings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.367
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations143
Published2022
Admission routes1
Has abstractyes

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