Optimizing Stroke Systems of Care by Enhancing Transitions Across Care Environments
Bibliographic record
Abstract
Stroke affects many aspects of the lives of stroke survivors and their family caregivers. Supporting long-term recovery and rehabilitation are necessary to help stroke survivors adapt to living with the effects of stroke and to help family members adapt to the caregiving role. During recovery and rehabilitation, many elements of the health care continuum are utilized, including emergency response, acute care, inpatient and outpatient rehabilitation, and community and long-term care. With the advent of thrombolytic therapy and the benefits of stroke units, stroke survival and outcomes are improving. As a result, the current emphasis of stroke system improvement is to implement stroke units throughout the developed world. To enhance the patient centeredness of stroke care delivery, an important next phase of stroke system improvement will center on the experiences of stroke survivors and their family caregivers as they move through diverse care environments. The objective of this article was to conduct a scoping review of the literature on stroke transitions to identify the current areas of research emphasis. This article highlights stroke survivors' and family caregivers' experiences with transitions across care environment and some potential strategies to improve those transitions.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".