Correlation between genetic polymorphisms and stroke recovery: Analysis of the GAIN Americas and GAIN International Studies
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Recovery after stroke occurs on the basis of specific molecular events. Genetic polymorphisms associated with impaired neural repair or plasticity might reduce recovery from stroke and might also account for some of the intersubject variability in stroke recovery. This study hypothesized that the ApoE ε4 polymorphism and the val(66) met polymorphism for brain-derived neurotrophic factor (BDNF) are each associated with poorer outcome after stroke. Associations with mitochondrial genotype were also explored. METHODS: Genotypes were determined in 255 stroke patients who also received behavioral evaluations in the Glycine Antagonist In Neuroprotection (GAIN) clinical trials. The primary outcome measure was recovery during the first month post-stroke, as this is the time when neural repair is at a maximum and so when genetic influences might have their largest impact. Two secondary outcome measures at 3 months post-stroke were also examined. RESULTS: Genotype groups were similar acutely post-stroke. Presence of the ApoE ε4 polymorphism was associated with significantly poorer recovery over the first month post-stroke (P = 0.023) and with a lower proportion of subjects with minimal or no disability (modified Rankin score 0-1, P = 0.01) at 3 months post-stroke. Indeed, those with this polymorphism were approximately half as likely to achieve minimal or no disability (18.2%) versus those with polymorphism absent (35.5%). Findings were confirmed in multivariate models. Results suggested possible effects from the val(66) met BDNF polymorphism and from the R0 mitochondrial DNA haplotype. CONCLUSIONS: Genetic factors, particularly the ApoE ε4 polymorphism, might contribute to variability in outcomes after stroke.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it