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Record W2752276737 · doi:10.1161/str.44.suppl_1.atp439

Abstract TP439: Temporary Cognitive Impairment in Transient Ischemic Attack and Minor Stroke Patients is Predicted by Chronic White Matter Hyperintensity Volume

2013· article· en· W2752276737 on OpenAlexaffabout
Leka Sivakumar, Thomas Jeerakathil, Negar Asdaghi, Richard Camicioli, Christian Beaulieu, Derek Emery, Kenneth Butcher

Bibliographic record

VenueStroke · 2013
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsUniversity of British ColumbiaUniversity of Alberta
Fundersnot available
KeywordsMedicineMontreal Cognitive AssessmentFluid-attenuated inversion recoveryHyperintensityStroke (engine)Internal medicineCardiologyMagnetic resonance imagingLesionLeukoaraiosisWhite matterCognitive impairmentSurgeryRadiologyDisease

Abstract

fetched live from OpenAlex

Background: Cognitive changes have been described in subacute TIA/minor stroke (TIA/MIS), but the temporal profile is unknown. We tested the hypothesis that TIA/MIS patients experience transient cognitive impairment, and that this can be predicted by Diffusion-Weighted Imaging (DWI) lesion volume. Methods: Acute TIA/MIS stroke (NIH stroke scale score ≤3) patients with no history of cognitive impairment were prospectively recruited within 72 h of onset. Patients underwent Montreal Cognitive Assessment (MoCA), Mini-Mental Status Examination (MMSE) and MRI, including DWI and Fluid-Attenuated Inverse Recovery (FLAIR) sequences, at baseline, days 7 and 30. DWI lesion and FLAIR chronic white matter hyperintensity (WMH) volumes were measured planimetrically. Results: Fifty patients (mean age 68 ±15.1 years) were imaged at a median (IQR) of 26.5 (28.5) h after onset. Cognitive impairment (scores ≤26) was detected more frequently with MoCA (31/50, 62%) than MMSE (13/50, 26%, p=0.009). Acute ischemic lesions (DWI) were present in 33 (66%) patients. Mean DWI volume at baseline was 4.5 ± 11.1ml. Patients with DWI lesions (22/33, 67%) had similar impairment rates as those without (9/17, 53%; p=0.34). Linear regression indicated no relationship between acute DWI lesion volume (log transformed) and baseline MoCA scores (β=0.028, 95% CI [-2.09, 2.44]). Impaired patients had larger WMH volumes (13.6 ± 21.9 ml) than unaffected patients (2.6 ± 3.2 ml, p=0.01). Log transformed WMH volumes were inversely predictive of baseline MoCA scores (β=-0.54, 95% CI [-7.84, -2.28]). Median MoCA scores improved over time (27(5) at day 7 and 28(5) at day 30). Patients with baseline impairment and an increase of ≥2 points on MoCA by day 30 were defined as reverters (N=20). DWI lesion frequency was similar in reverters and those with persisting impairment (75% vs 64%, p= 0.50), as was DWI (6.9 ±14.3 ml vs 1.2 ±1.9 ml; p= 0.113) and WMH lesion volume (17.0 ± 26.2 ml vs 8.1 ± 8.1 ml; p= 0.18). Conclusions: Most TIA/MIS patients have evidence of temporary acute cognitive impairment when assessed with MoCA. Deficits are correlated with chronic WMH, suggesting an unmasking of subclinical cognitive impairment. Temporary cognitive deficits should be considered in the management of TIA/MIS patients.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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 designObservational
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
Published2013
Admission routes2
Has abstractyes

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