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Record W2618314005 · doi:10.1016/j.jalz.2017.04.005

Dementia registries around the globe and their applications: A systematic review

2017· review· en· W2618314005 on OpenAlexaff
Karolina Krysińska, Perminder S. Sachdev, John C.S. Breitner, Miia Kivipelto, Walter A. Kukull, Henry Brodaty

Bibliographic record

VenueAlzheimer s & Dementia · 2017
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
FundersNational Institute on AgingUniversity of New South Wales
KeywordsDementiaHarmonizationGlobeGovernment (linguistics)MedicineHealth carePublic healthMEDLINEEpidemiologyFamily medicineNursingPolitical sciencePathology

Abstract

fetched live from OpenAlex

Patient registries are valuable tools helping to address significant challenges in research, care, and policy. Registries, well embedded in many fields of medicine and public health, are relatively new in dementia. This systematic review presents the current situation in regards to dementia registries worldwide. We identified 31 dementia registries operating on an international, national, or local level between 1986 and 2016. More than half of the registries aimed to conduct or facilitate research, including preclinical research registries and registries recruiting research volunteers. Other dementia registries collected epidemiological or quality of care data. We present evidence of practical and economic outcomes of registries for research, clinical practice and policy, and recommendations for future development. Global harmonization of recruitment methods and minimum data would facilitate international comparisons. Registries provide a positive return on investment; their establishment and maintenance require ongoing support by government, policy makers, research funding bodies, clinicians, and individuals with dementia and their caregivers.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.591
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.100
GPT teacher head0.393
Teacher spread0.293 · 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 teacher head, not a consensus.

Study designSystematic review
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

Citations94
Published2017
Admission routes1
Has abstractyes

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