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Record W2054140188 · doi:10.1136/ebn.12.3.87

Review: long-term annual conversion rate to dementia was 3.3% in elderly people with mild cognitive impairmentCommentary

2009· letter· en· W2054140188 on OpenAlexaff
Diane Buchanan

Bibliographic record

VenueEvidence-Based Nursing · 2009
Typeletter
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsDementiaMedicineCognitive impairmentPsycINFOGerontologyCohortCohort studyAlzheimer's diseaseDiseasePediatricsMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

In elderly people with mild cognitive impairment (MCI), what is the long-term rate of conversion to dementia? Included studies examined the progression of MCI, defined according to accepted criteria. Outcomes were dementia or probable Alzheimer disease (AD). Medline, EMBASE/Excerpta Medica, and PsycINFO (to Mar 2008) were searched for cohort studies that had ⩾5 years of follow-up. 15 studies (n = 2402, mean age 62–82 y) met the selection criteria. Mean follow-up was 6 years (range 5–10 y). The cumulative conversion rate to dementia was 31% (15 studies) and to AD was 33% (11 studies). The table shows annual conversion rates. Annual conversion rates …

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)0.011
metaresearch head score (Gemma)0.053
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: Commentary · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.028
GPT teacher head0.339
Teacher spread0.312 · 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
GenreCommentary

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

Citations1
Published2009
Admission routes1
Has abstractyes

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