ArticleThe journal of spinal cord medicine2025
Predicting inpatient rehabilitation length of stay for adults with traumatic spinal cord injury.
Article in The journal of spinal cord medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- How recovery influences community reintegration: perspectives of persons with spinal cord injury and their support persons.Frontiers in rehabilitation sciences · 2025Article
- Rehabilitation to Improve Outcomes after Cervical Spine Surgery: Narrative Review.Journal of clinical medicine · 2024Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionMost post-injury traumatic spinal cord injury (TSCI) care occurs in the inpatient rehabilitation setting. The inpatient rehabilitation length of stay (R-LOS) has been shown to be a significant predictor of motor function restoration in persons with TSCI. Due to the complexity, and heterogeneity of individuals with TSCI, the R-LOS is challenging to predict at admission. PURPOSE: To identify the main predictors of R-LOS and derive an equation to estimate R-LOS in persons with TSCI.
methodsThis is a retrospective analysis of data from adults with TSCI from The Rick Hansen Spinal Cord Injury Registry in Alberta, Canada, who received rehabilitation care between May 10, 2005, and January 28, 2020. Multiple linear regression analysis was used to determine significant relationships between R-LOS and measures of participant demographics, length of stay, impairment and injury classification, and comorbidities.
resultsThe analysis included 736 adults with TSCI from an eligible cohort of 1365. The median R-LOS was 65 days (IQR 39-99 days), ranging from 1 to 469 days. Multivariate linear regression analysis identified two significant predictors of R-LOS, total FIM score and the injury classification. This model was used to derive a R-LOS prediction equation, which explained 34% of the variance in R-LOS.
conclusionWe developed a simple equation to predict R-LOS based on the level of impairment and total FIM scores in persons with TSCI. These data have implications for health system planning, improvement, and innovation, and provide insights to support further research into the predictors of R-LOS, identification of higher-risk individuals.
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