Does Specialized Inpatient Rehabilitation Affect Whether or Not People with Traumatic Spinal Cord Injury Return Home?
Bibliographic record
Abstract
Return to living at home is an important patient-reported outcome following traumatic spinal cord injury (tSCI). Specialized inpatient rehabilitation assists such patients in maximizing function and independence. Our project aim was to describe those patients receiving specialized rehabilitation after tSCI in Canada, and to determine if such rehabilitation improved the likelihood of returning home. This cohort study utilized data from the Rick Hansen Spinal Cord Injury Registry (RHSCIR) to identify patients with tSCI discharged from 1 of 18 participating acute specialized spine facilities between 2011 and 2015 to either 1 of 13 participating specialized rehabilitation facilities, or to another discharge destination. To determine if specialized rehabilitation affected likelihood of returning home, multiple logistic regressions and propensity score matchings were performed to account for age at injury, gender, neurological severity and level, acute length of stay (LOS), and region of residence. The χ2 test was used to compare rate of return home between matched groups. Of the 1599 patients included, 71% received specialized rehabilitation. Receiving specialized rehabilitation was a significant and strong predictor of return to home after controlling for covariates (adjusted odds ratio = 3.1; 95% confidence interval [CI], 1.6–5.9). The rate of return to home was significantly higher in the matched rehabilitation group than the no rehabilitation group (98% vs. 87%, p = 0.0004). For the matched patients, an extra 11 patients returned home for every 100 patients receiving specialized rehabilitation. However, effect of age on returning home requires further investigation. Improving access to specialized rehabilitation could potentially reduce discharges to nursing homes or other non-home destinations.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".