Abstract 3474: Early Supported Discharge for Post-Stroke Inpatient Rehabilitation: Who and What are we Talking About?
Bibliographic record
Abstract
Background and Purpose Early supported discharge (ESD) post stroke has been demonstrated as a cost-effective strategy for provision of rehabilitation to eligible patients. However, consensus on which patients are best-suited for ESD has yet to be established. This systematic review was designed to retrieve information on patients included in all published, peer-reviewed literature pertaining to ESD for post-stroke rehabilitation with the goal of identifying common criteria used to infer candidacy for ESD. Methods A systematic review of the literature was performed in three electronic databases (Medline, Embase, CINAHL) for peer-reviewed journal articles evaluating ESD for post-stroke rehabilitation published between January 1980 and September 2010. Research studies were considered if 1) they only included patients with primary diagnosis of stroke 2) the intervention under study was outpatient or community-based rehabilitation (ESD) as an alternative to in-hospital rehabilitation and 3) inclusion/ exclusion criteria and/or patient data at time of discharge to the community were reported. Information about study design, inclusion/exclusion criteria, discharge patient data and study results were collected. Results In total, 612 journal articles were screened and 20 were included for further assessment. No consensus on ESD suitability could be derived from the identified studies. Interventions under study ranged from organized in-home rehabilitation to “hospital at home” where therapy was provided by family members. On average, 34.7% (13%-70%) of patients screened for ESD candidacy were identified as suitable, but little consistency in screening procedures or criteria were noted. Recruitment generally took place within the first week post stroke but extended to as many as 4 weeks post stroke, while the average day of discharge into an ESD program ranged from 1 to as many as 42 days post stroke. Nine articles reported information about patient’s functional level within 48 hours of discharge to ESD, however, 27 different measures of patient function were reported. Conclusions Most research to date suggests that ESD is an effective strategy for providing rehabilitation to patients post-stroke. However, based on current research it is not possible to derive definitive criteria by which candidates for ESD can be identified. Future research is warranted.
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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 | 0.026 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".