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Record W2169152323 · doi:10.1161/strokeaha.114.005842

Test Accuracy of Cognitive Screening Tests for Diagnosis of Dementia and Multidomain Cognitive Impairment in Stroke

2014· review· en· W2169152323 on OpenAlexaboutno aff
Rosalind Lees, Johann Selvarajah, Candida Fenton, Sarah T. Pendlebury, Peter Langhorne, David J. Stott, Terence J. Quinn

Bibliographic record

VenueStroke · 2014
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDementiaStroke (engine)CognitionCognitive impairmentCognitive testTest (biology)Screening testPhysical medicine and rehabilitationPsychiatryPediatricsDiseasePathology

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Guidelines recommend screening stroke-survivors for cognitive impairments. We sought to collate published data on test accuracy of cognitive screening tools. METHODS: Index test was any direct, cognitive screening assessment compared against reference standard diagnosis of (undifferentiated) multidomain cognitive impairment/dementia. We used a sensitive search statement to search multiple, cross-disciplinary databases from inception to January 2014. Titles, abstracts, and articles were screened by independent researchers. We described risk of bias using Quality Assessment of Diagnostic Accuracy Studies tool and reporting quality using Standards for Reporting of Diagnostic Accuracy guidance. Where data allowed, we pooled test accuracy using bivariate methods. RESULTS: From 19 182 titles, we reviewed 241 articles, 35 suitable for inclusion. There was substantial heterogeneity: 25 differing screening tests; differing stroke settings (acute stroke, n=11 articles), and reference standards used (neuropsychological battery, n=21 articles). One article was graded low risk of bias; common issues were case-control methodology (n=7 articles) and missing data (n=22). We pooled data for 4 tests at various screen positive thresholds: Addenbrooke's Cognitive Examination-Revised (<88/100): sensitivity 0.96, specificity 0.70 (2 studies); Mini Mental State Examination (<27/30): sensitivity 0.71, specificity 0.85 (12 studies); Montreal Cognitive Assessment (<26/30): sensitivity 0.95, specificity 0.45 (4 studies); MoCA (<22/30): sensitivity 0.84, specificity 0.78 (6 studies); Rotterdam-CAMCOG (<33/49): sensitivity 0.57, specificity 0.92 (2 studies). CONCLUSIONS: Commonly used cognitive screening tools have similar accuracy for detection of dementia/multidomain impairment with no clearly superior test and no evidence that screening tools with longer administration times perform better. MoCA at usual threshold offers short assessment time with high sensitivity but at cost of specificity; adapted cutoffs have improved specificity without sacrificing sensitivity. Our results must be interpreted in the context of modest study numbers: heterogeneity and potential bias.

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)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.759
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.049
GPT teacher head0.398
Teacher spread0.349 · 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 designOther design
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

Citations197
Published2014
Admission routes1
Has abstractyes

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