Malec James F, Parrot Devan, Altman Irwin M, Swick Shannon
a Physical Medicine and Rehabilitation , Indiana University School of Medicine and Rehabilitation Hospital of Indiana, and Mayo Clinic , Indianapolis , USA.
Neuropsychol Rehabil. 2015;25(5):663-76. doi: 10.1080/09602011.2015.1013139. Epub 2015 Feb 24.
The objective of the study was to develop statistical formulas to predict levels of community participation on discharge from post-hospital brain injury rehabilitation using retrospective data analysis. Data were collected from seven geographically distinct programmes in a home- and community-based brain injury rehabilitation provider network. Participants were 642 individuals with post-traumatic brain injury. Interventions consisted of home- and community-based brain injury rehabilitation. The main outcome measure was the Mayo-Portland Adaptability Inventory (MPAI-4) Participation Index. Linear discriminant models using admission MPAI-4 Participation Index score and log chronicity correctly predicted excellent (no to minimal participation limitations), very good (very mild participation limitations), good (mild participation limitations), and limited (significant participation limitations) outcome levels at discharge. Predicting broad outcome categories for post-hospital rehabilitation programmes based on admission assessment data appears feasible and valid. Equations to provide patients and families with probability statements on admission about expected levels of outcome are provided. It is unknown to what degree these prediction equations can be reliably applied and valid in other settings.
本研究的目的是通过回顾性数据分析，开发统计公式以预测颅脑损伤康复出院后的社区参与水平。数据收集自一个以家庭和社区为基础的颅脑损伤康复服务网络中七个地理位置不同的项目。参与者为642名创伤性脑损伤患者。干预措施包括以家庭和社区为基础的颅脑损伤康复。主要结局指标是梅奥-波特兰适应性量表（MPAI-4）参与指数。使用入院时的MPAI-4参与指数评分和病程对数的线性判别模型能够正确预测出院时的良好（无至最小参与限制）、非常好（非常轻微的参与限制）、良好（轻微参与限制）和有限（显著参与限制）结局水平。基于入院评估数据预测出院后康复项目的广泛结局类别似乎是可行且有效的。提供了用于向患者及其家属说明入院时预期结局水平概率的公式。尚不清楚这些预测公式在其他环境中能够可靠应用和有效的程度。
