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Record W2980166901 · doi:10.3389/fneur.2019.01051

Very Early MoCA Can Predict Functional Dependence at 3 Months After Stroke: A Longitudinal, Cohort Study

2019· article· en· W2980166901 on OpenAlexaboutno aff
Tamar Abzhandadze, Lena Rafsten, Åsa Nilsson, Annie Palstam, Katharina S. Sunnerhagen

Bibliographic record

VenueFrontiers in Neurology · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersVästra Götalandsregionen
KeywordsMontreal Cognitive AssessmentStroke (engine)QuartileReceiver operating characteristicMedicinePhysical therapyCohortModified Rankin ScaleLogistic regressionActivities of daily livingCohort studyCognitionArea under the curveInternal medicinePhysical medicine and rehabilitationCognitive impairmentIschemic strokeConfidence intervalPsychiatry

Abstract

fetched live from OpenAlex

Introduction: After a stroke, cognitive impairment is commonly associated with poor functional outcomes. The primary aim of this study was to investigate if cognitive function, assessed with the Montreal Cognitive Assessment (MoCA) 36-48 h after stroke could predict functional dependence 3 months later. The secondary aim was to identify an optimal threshold for the MoCA score that could predict functional dependence. Materials and methods: This was a longitudinal cohort study. The research database from a stroke unit at Sahlgrenska University hospital was linked with the Swedish Stroke Register – Riksstroke. Cognitive function and Activities of Daily Living (ADL) were assessed with the MoCA and the Barthel Index (BI), respectively, 36-48 h after stroke. Functional outcome 3 months after stroke was studied with the modified Rankin Scale. The predictive characteristics of the MoCA were investigated using logistic regression analyses. Receiver Operating Characteristic curves (AUC) were used for identifying the optimal cut-off score on the MoCA for predicting functional dependence. The MoCA score which had equal sensitivity and specificity was chosen as the optimal score for predicting functional dependence. Results: A total of 305 participants were included in the study (mean age 68.8 years, n=179 men). The MoCA quartiles was a significant predictor of functional dependence 3 months after stroke as an individual variable (p<0.001, AUC = 0.72) and when adjusted for covariates such as age at stroke onset, living arrangement prior to stroke and ADL measured with BI within 36-48 h after stroke (p=0.01, AUC = 0.84). The MoCA score of ≤23 for impaired cognition had equal sensitivity and specificity for predicting functional dependence 3 months after stroke. Discussion and Conclusion: Cognitive function assessed with the MoCA within 36-48 h after stroke could predict functional dependence 3 months later. The participants with MoCA scores ≤23 for impaired cognition were more likely to be functionally dependent. Key words: Activities of daily living, Acute stroke, ADL, Cognition, Disability, Evaluation, Level of global disability, Modified Rankin Scale.

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)0.003
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.243
Teacher spread0.235 · 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

Citations46
Published2019
Admission routes1
Has abstractyes

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