Postdischarge participation and functional outcomes across three common stroke subtypes based on the exploratory retrospective study
Bibliographic record
Abstract
This study investigated the impact of stroke subtypes—ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH)—on long-term participation and functional outcomes 12 months postdischarge. Datasets from two prospective studies were retrospectively analyzed for adults with these stroke subtypes who received inpatient rehabilitation. Outcomes, including Participation Measure-3 Domains, 4 Dimensions (PM-3D4D), Activity Measure for Post-Acute Care, EuroQol 5-Dimension 3-Level, and Montreal Cognitive Assessment scores, were tracked from hospital discharge up to 12 months. Among 646 patients (256 women, mean age 56.6 years), patients with IS (n = 335) and ICH (n = 288) showed similar postdischarge recovery patterns, whereas patients with SAH (n = 23) generally had poorer outcomes at 12 months. The most substantial difference was observed in productivity frequency scores (a PM-3D4D subdomain), with SAH group exhibiting significantly lower scores (0.04 [0–0.09]) compared to IS (0.39 [0.33–0.45]) and ICH (0.44 [0.37–0.51]) groups (P < 0.001). After adjusting for age and sex, better activity function at discharge was found to be an independent predictor of higher PM-3D4D scores 12 months postdischarge. These findings highlight that SAH is associated with poorer long-term outcomes compared to other subtypes, demonstrate subtype-specific profiles, and suggest activity function as a key target for inpatient rehabilitation to enhance participation postdischarge.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".