Late Functional Recovery After Lacunar Stroke: Implications For Rehabilitation Studies
Bibliographic record
Abstract
Objective: To compare rates of functional recovery beyond 3-months in patients with lacunar versus non-lacunar strokes in a prospective, population-based cohort study. Background: Non-acute interventions to enhance late stroke recovery are often tested initially in uncontrolled studies in patients with lacunar stroke owing to their low mortality and relatively isolated motor deficits. It is often assumed that neurological recovery is near complete by 3-months after the stroke, but there have been few studies of the capacity for late recovery beyond 3-months. Design/Methods: In 3-month ischaemic stroke survivors of the Oxford Vascular Study (OXVASC; 2002–2014), we examined changes in functional status (modified Rankin Scale [mRS], Rivermead Mobility Index [RMI], Barthel Index[BI]) in lacunar versus non-lacunar strokes from 3–60 months post-stroke, stratifying by age. We used logistic regression adjusted for age, sex, and baseline disability to compare recovery (≥1 mRS grades, ≥1 RMI points and/or ≥2 BI points), particularly from 3–12 months. Results: Among 1,425 3-month survivors, the 234 lacunar stroke patients did not differ from others for outcome at 3-months (aOR for 3-month mRS>2: 1.14, 95%CI 0.75–1.74, p=0.55), but were much more likely to demonstrate further recovery between 3-months and 1-year (aOR: 1.64, 1.17–2.31, p=0.004). Results were similar on restricting the analysis to patients with 3-month mRS 2–4 (the range commonly recruited into recovery studies) and on excluding recurrent events (aOR[mRS] adjusted for age, sex, 3-month mRS: 2.28, 1.34–3.86, p=0.002). Similar results were seen with the BI and RMI (aOR[RMI] adjusted for age, sex, 3-month RMI: 1.78, 1.20–2.64, p=0.004). Conclusions: Lacunar strokes have greater potential for late functional recovery from 3–12 months post-stroke, supporting the focus of studies of restorative therapies on this group. However, such studies cannot assume that improvements after 3-months are treatment-related, and should therefore be randomized and controlled. Study Supported by: OXVASC has been funded by the Wellcome Trust, Wolfson Foundation, and the NIHR Oxford Biomedical Research Centre. PMR has received an NIHR Senior Investigator Award and a Wellcome Trust Senior Investigator Award. AG is funded by the Rhodes Trust. Disclosure: Dr. Ganesh has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Adkins Research Group. Dr. Ganesh has received compensation for serving on the Board of Directors of SnapDx, AHA Health Ltd. Dr. Wharton has nothing to disclose. Dr. Gutnikov has nothing to disclose. Dr. Rothwell has nothing to disclose. Dr. Oxford Vascular Study has nothing to disclose.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.136 | 0.238 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".