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Record W2912045039 · doi:10.1161/str.50.suppl_1.tp560

Abstract TP560: Cognitive Impairment Should Be an Independent Predictor of Poor Functional Outcome in Acute Minor Stroke

2019· article· en· W2912045039 on OpenAlexaboutno aff
Takuya Nishimura

Bibliographic record

VenueStroke · 2019
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMontreal Cognitive AssessmentModified Rankin ScaleStroke (engine)CognitionInternal medicineLogistic regressionPhysical therapyCognitive impairmentIschemic strokeIschemiaPsychiatry

Abstract

fetched live from OpenAlex

Objective: The evaluation of cognitive status is not routine in the acute stroke setting. The aim of the study was to elucidate the association between cognitive function and functional outcome in acute minor ischemic stroke patients. Methods: From December 2016 to November 2017, patients with acute minor ischemic stroke (prehospital modified Rankin Scale (mRS) ≤1 and National Institute of Health Stroke Scale (NIHSS) score ≤3) who were admitted to our department were prospectively analyzed. Prestroke cognitive state was estimated by Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) which was completed by the patient’s relative at the time of admission. Cognitive performance was measured using the Japanese version of Montreal Cognitive Assessment (MoCA-J) within the first 7 days of admission. Cognitive impairment was defined as MoCA-J <23. Functional outcomes were assessed using the mRS at the time of discharge. A poor discharge outcome was defined as an mRS score of 3-5 or death (mRS score of 6). The impacts of cognitive function on outcome were assessed by multivariate logistic regression analyses. Results: Overall, 581 consecutive patients with acute ischemic stroke admitted to our department during the study period. Finally, 128 patients with minor ischemic stroke (median age 72years) were enrolled. In total, 74 (58%) patients had impaired cognitive impairment in the acute phase. Age ( P = 0.0161), NIHSS score on admission ( P <0.0001), IQCODE ( P =0.0167), Moca-J ( P <0.0001), dyslipidemia ( P =0.0101), and sex ( P =0.0222) were different between good and poor outcome. Multivariate analysis showed that high NIHSS score (odds ratio [OR], 7.30; 95% confidence interval [CI], 2.33-39.95, P < 0.0001) upon admission as well as low Moca-J score (OR, 1.32; 95% CI, 1.11-1.61, P = 0.0006) was independently associated with poor functional outcome. Conclusion: Cognitive impairment in acute minor ischemic stroke was common and independently associated with poor functional outcome after adjusting for the effects of stroke severity, prestroke cognitive status, and various risk factors.

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)0.003
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.033
GPT teacher head0.299
Teacher spread0.267 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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