Cilostazol use is associated with FIM cognitive improvement during convalescent rehabilitation in patients with ischemic stroke: a retrospective study.
Bibliographic record
Abstract
Cilostazol is a phosphodiesterase III-inhibiting antiplatelet agent that is often used to prevent stroke and peripheral artery disease, and its administration has shown significant improvements for cognitive impairment. We investigate the potential of cilostazol for reducing or restoring cognitive decline during convalescent rehabilitation in patients with non-cardioembolic ischemic stroke. The study sample included 371 consecutive patients with lacunar (n = 44) and atherothrombosis (n = 327) subtypes of non-cardioembolic ischemic stroke (224 men and 147 women; mean age, 72.9 ± 8.1 years) who were required for inpatient convalescent rehabilitation. Their medical records were retrospectively surveyed to identify those who had received cilostazol (n = 101). Patients were grouped based on cilostazol condition, and Functional Independence Measure (FIM) scores (total and motor or cognitive subtest scores) were assessed both at admission and discharge. The gain and efficiency in FIM cognitive scores from admission to discharge were significantly higher in patients who received cilostazol than those who did not (p = 0.047 and p = 0.035, respectively); we found no significant differences in other clinical factors or scores. Multiple linear regression analysis confirmed that cilostazol was a significant factor in FIM cognitive scores at discharge (β = 0.041, B = 0.682, p = 0.045); the two tested dosages were not significantly different (100 mg/day, n = 43; 200 mg/day, n = 58). Cilostazol can potentially improve cognitive function during convalescent rehabilitation of patients with non-cardioembolic ischemic stroke, although another research must be needed to confirm this potential.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".