Abstract 140: Long-term disability after lacunar stroke: Secondary Prevention of Small Subcortical Stroke Study
Bibliographic record
Abstract
Background: Long-term disability after lacunar stroke is under-studied. We hypothesized that vascular and demographic risk factors predict worsening disability after recovery from lacunar stroke, even in the absence of recurrent stroke. Methods: The Secondary Prevention of Small Subcortical Stroke Study is a clinical trial in lacunar stroke patients with annual assessments of disability with the Older Americans Resources and Survey Instrumental Activities of Daily Living (IADL) scale (range 0-14), measuring 7 IADLs. Generalized estimating equations were used to model the likelihood of disability (IADL score <14) over time, adjusting for demographics, medical risk factors, cognitive and mood factors, and region in univariate and multivariable models. IADL assessments after recurrent stroke were censored. We stratified by study region and age quartile (<55, 55-63, 63-72, ≥72 years), and the final model excluded non-significant terms. Results: Among 2820 participants, mean age was 63.4 years (SD 10.8), 63% were male, 51% White, 32% Hispanic, 36% had some college education, 36% had diabetes, 90% had hypertension, and 10% had prior stroke. Mean follow-up was 3.5 years. Mean IADL score at 3 months was 12.5 (SD 2.5), and 43% were disabled. In multivariable models, female sex (OR 1.5, 95% CI 1.3-1.8), diabetes (1.52, 1.30-1.75), current smoking (1.28, 1.06-1.54), non-regular alcohol use (1.6, 1.4-1.9), prior stroke (1.61, 1.28-2.00), cognitive assessment screening instrument score (0.98 per point, 0.97-0.98), and depression (1.79, 1.49-2.17) were associated with disability. The youngest age quartile had decreased odds of disability over time (OR 0.56 per year, 95% CI 0.36-0.91), whereas the oldest age quartile had increased odds (1.33, 0.83-2.22). There was heterogeneity by region (p<0.0001): Americans and Latin Americans had 2.5-fold greater odds of disability per year compared to Spaniards. Conclusion: In lacunar stroke patients, older age predicted worsening long-term disability, even without recurrent stroke. Worse long-term function was associated with vascular risk factors and prior stroke, and regional differences may have been due to geographic variations in health care delivery or scale interpretation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".