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Record W4406993297 · doi:10.1161/str.56.suppl_1.wmp42

Abstract WMP42: Exploring The Neural Basis Of Prognostic Tools For Upper Limb Recovery After Stroke: <i>Lesion Topography Of SAFE And Other Medical Research Council Scale Scores</i>

2025· article· en· W4406993297 on OpenAlexaff
Matthew J. Chilvers, Kate Hayward, Michael D. Hill, Sean P. Dukelow

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineStroke (engine)Physical medicine and rehabilitationStroke recoveryScale (ratio)Upper limbLesionRehabilitationPhysical therapySurgeryCartography

Abstract

fetched live from OpenAlex

Background: The Medical Research Council (MRC) scale is used to assess the impact of stroke on muscle strength. Shoulder abduction and finger extension, collectively (SAFE), have been suggested to have prognostic value for stroke outcomes (e.g. PREP-2), and been recommended for use in screening for clinical trials. Few studies have assessed the neuroanatomy associated with SAFE, and other upper extremity MRC scores after stroke. In this study, we used voxel-based lesion symptom mapping (VLSM) to assess lesion locations associated with worse SAFE scores, as well as other movements assessed by the MRC scale. Methods: A trained therapist assessed 12 individual MRC scores at the: shoulder (flexion, extension, abduction, internal and external rotation), elbow (flexion and extension), wrist (flexion and extension) and fingers (flexion, extension and abduction). Clinical neuroimaging (MRI and/or CT) was collected for all participants, and lesioned voxels traced by trained assessors and normalized to a standard template space. VLSM analysis was conducted for all 12 MRC scale scores, and SAFE score, using NiiStat. Only voxels lesioned in >10% of participants were tested. Results: We recruited 226 stroke participants at 2 weeks post-stroke (mean age=62.6; Males=147; Right Hemisphere=131; Ischemic=199, Hemorrhagic=27). VLSM analysis showed that worse SAFE scores were significantly associated with lesions in voxels in the left and right corona radiata, adjacent and dorsal to the lateral ventricles, and consistent with the upper portions of the corticospinal tract in each hemisphere. Additionally, voxels in the putamen were also significantly associated with worse SAFE scores. Interestingly, all other MRC scores were also associated with similar lesion topography to SAFE. Conclusion: This work demonstrates a consistent association between SAFE scores and corticospinal tract damage. The integrity of the corticospinal tract has frequently been suggested as a biomarker of stroke recovery. These findings shed light on why SAFE might be a valuable prognostic tool for stroke recovery, and a quick and efficient screening tool for clinical trials. Despite increasing use of SAFE, other muscle weakness, assessed by the MRC scale, is also represented by the same neuroanatomic regions and may share similar prognostic abilities. Continued investigation into effective prognostic tools for upper-limb recovery is warranted.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.100
GPT teacher head0.339
Teacher spread0.239 · 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
Published2025
Admission routes1
Has abstractyes

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