Ceder L, Svensson K, Thorngren K G
Clin Orthop Relat Res. 1980 Oct(152):185-90.
A statistical investigation using multivariate techniques was made of the rehabilitation outcome of 103 consecutive elderly hip fracture patients, all admitted from their own homes. Cluster analysis revealed two main groups of variables, i.e., background variables (age, general medical condition, type of fracture, sex, living with someone) and functional variables (prefracture ability to visit someone and to shop, ability to walk and to manage activities of daily living two weeks postsurgery). A stepwise linear discriminant analysis was used, to estimate the probability of a given patient returning home. At discharge from hospital, certain factors, i.e., ability to walk two weeks postsurgery, living with someone, general medical condition, and type of fracture, were found to be most important for direct return home. At one year after hip fracture, the prefracture ability to visit someone and the age of the patient were of most prognostic significance for having returned and remained at home. The accuracy of the prediction tested by a "jackknife" procedure showed an over all increasingly correct classification during the follow-up year, more than 80% correct for all patients at discharge and 86% correct at one year. This approach to the analysis of soft data concerning hip fracture rehabilitation may prove of prognostic value also in sociomedical systems elsewhere.
采用多变量技术对103例连续的老年髋部骨折患者的康复结局进行了统计调查，所有患者均从家中入院。聚类分析揭示了两组主要变量，即背景变量（年龄、一般健康状况、骨折类型、性别、是否有人陪伴生活）和功能变量（骨折前探访他人和购物的能力、术后两周行走及日常生活自理能力）。采用逐步线性判别分析来估计特定患者回家的概率。出院时，发现某些因素，即术后两周行走能力、有人陪伴生活、一般健康状况和骨折类型，对直接回家最为重要。髋部骨折一年后，骨折前探访他人的能力和患者年龄对回家并留在家中具有最重要的预后意义。通过“交叉验证”程序测试的预测准确性显示，在随访年度中总体分类正确率不断提高，出院时所有患者的正确率超过80%，一年时为86%。这种分析髋部骨折康复软数据的方法在其他地方的社会医疗系统中可能也具有预后价值。
