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Record W4200095655 · doi:10.1017/brimp.2021.25

Working Memory Impairment in Transient Ischaemic Attack: N-back as a Sensitive Measure for Detection

2021· article· en· W4200095655 on OpenAlexaboutno aff
Laura Smith, Polly Gregory, Philip Clatworthy, George Stothart

Bibliographic record

VenueBrain Impairment · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentCognitionDementiaCognitive impairmentNeuropsychologyMedicineMemory clinicWorking memoryPsychological interventionAudiologyPhysical medicine and rehabilitationPsychiatryInternal medicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Transient ischaemic attack (TIA) can lead to lasting changes in brain structure and function resulting in cognitive impairment. Cognitive screening tools may lack sensitivity for detecting cognitive impairments, particularly executive function, which tends to be the earliest affected domain in vascular cognitive impairment. AIM: In this preliminary study, we examine a working memory (WMem) task as a sensitive measure of cognitive impairment in TIA. METHOD: Patients referred to a TIA clinic for transient neurological symptoms completed a general cognitive screening tool (Montreal Cognitive Assessment; MoCA), and a WMem task (2-N-back) in a cross-sectional design. RESULTS: TIA patients (n = 12) showed significantly reduced WMem performance on the N-back compared to patients diagnosed with mimic clinical conditions with overlapping symptoms (n = 16). No group differences were observed on the MoCA. CONCLUSIONS: Assessing WMem may provide a sensitive measure of cognitive impairment after TIA, with implications for cognitive screening in TIA services to triage patients for further neuropsychological support, or for interventions to prevent vascular dementia.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.031
GPT teacher head0.320
Teacher spread0.290 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2021
Admission routes1
Has abstractyes

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