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Record W4289868909 · doi:10.1161/jaha.121.025425

Repeated Measures of Modified Rankin Scale Scores to Assess Functional Recovery From Stroke: AFFINITY Study Findings

2022· article· en· W4289868909 on OpenAlexaff
Alexander Chye, Maree L. Hackett, Graeme J. Hankey, Erik Lundström, Osvaldo P. Almeida, John Gommans, Martin Dennis, Stephen Jan, Gillian Mead, Andrew H. Ford, Christopher Etherton‐Beer, Leon Flicker, Candice Delcourt, Laurent Billot, Craig S. Anderson, Katharina S. Sunnerhagen, Qilong Yi, Séverine Bompoint, Thang Huy Nguyen, Thomas Lung

Bibliographic record

VenueJournal of the American Heart Association · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsCanadian Blood ServicesUniversity of Toronto
FundersNational Institute for Health and Care Research
KeywordsMedicineRepeated measures designStroke (engine)Modified Rankin ScaleFunctional Independence MeasurePhysical therapyFluoxetineRandomized controlled trialStroke recoveryLogistic regressionClinical trialPlaceboOdds ratioDepression (economics)Internal medicineActivities of daily livingIschemic strokeRehabilitation

Abstract

fetched live from OpenAlex

Background Function after acute stroke using the modified Rankin Scale (mRS) is usually assessed at a point in time. The analytical implications of serial mRS measurements to evaluate functional recovery over time is not completely understood. We compare repeated-measures and single-measure analyses of the mRS from a randomized clinical trial. Methods and Results Serial mRS data from AFFINITY (Assessment of Fluoxetine in Stroke Recovery), a double-blind placebo randomized clinical trial of fluoxetine following stroke (n=1280) were analyzed to identify demographic and clinical associations with functional recovery (reduction in mRS) over 12 months. Associations were identified using single-measure (day 365) and repeated-measures (days 28, 90, 180, and 365) partial proportional odds logistic regression. Ninety-five percent of participants experienced a reduction in mRS after 12 months. Functional recovery was associated with age at stroke <70 years; no prestroke history of diabetes, coronary heart disease, or ischemic stroke; prestroke history of depression, a relationship partner, living with others, independence, or paid employment; no fluoxetine intervention; ischemic stroke (compared with hemorrhagic); stroke treatment in Vietnam (compared with Australia or New Zealand); longer time since current stroke; and lower baseline National Institutes of Health Stroke Scale & Patient Health Questionnaire-9 scores. Direction of associations was largely concordant between single-measure and repeated-measures models. Association strength and variance was generally smaller in the repeated-measures model compared with the single-measure model. Conclusions Repeated-measures may improve trial precision in identifying trial associations and effects. Further repeated-measures stroke analyses are required to prove methodological value. Registration URL: http://www.anzctr.org.au; Unique identifier: ACTRN12611000774921.

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)0.010
metaresearch head score (Gemma)0.018
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 score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.285
Teacher spread0.241 · 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

Citations38
Published2022
Admission routes1
Has abstractyes

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