Dang Mia, Ramsaran Kalinda D, Street Melissa E, Syed S Noreen, Barclay-Goddard Ruth, Stratford Paul W, Miller Patricia A
Mia Dang, BSc Eng, MSc(PT): Physical therapist and graduate of the MSc(PT) Program, School of Rehabilitation Science, McMaster University, Hamilton, Ontario.
Physiother Can. 2011 Summer;63(3):334-41. doi: 10.3138/ptc.2010-17. Epub 2011 Aug 10.
To estimate the predictive accuracy and clinical usefulness of the Chedoke-McMaster Stroke Assessment (CMSA) predictive equations.
A longitudinal prognostic study using historical data obtained from 104 patients admitted post cerebrovascular accident was undertaken. Data were abstracted for all patients undergoing rehabilitation post stroke who also had documented admission and discharge CMSA scores. Published predictive equations were used to determine predicted outcomes. To determine the accuracy and clinical usefulness of the predictive model, shrinkage coefficients and predictions with 95% confidence bands were calculated.
Complete data were available for 74 patients with a mean age of 65.3±12.4 years. The shrinkage values for the six Impairment Inventory (II) dimensions varied from -0.05 to 0.09; the shrinkage value for the Activity Inventory (AI) was 0.21. The error associated with predictive values was greater than ±1.5 stages for the II dimensions and greater than ±24 points for the AI.
This study shows that the large error associated with the predictions (as defined by the confidence band) for the CMSA II and AI limits their clinical usefulness as a predictive measure. Further research to establish predictive models using alternative statistical procedures is warranted.
评估切多克-麦克马斯特卒中评估（CMSA）预测方程的预测准确性和临床实用性。
采用纵向预后研究，使用从104例脑血管意外后入院患者获取的历史数据。提取所有接受卒中后康复治疗且有记录的入院和出院时CMSA评分的患者的数据。使用已发表的预测方程来确定预测结果。为确定预测模型的准确性和临床实用性，计算收缩系数以及带有95%置信区间的预测值。
74例患者有完整数据，平均年龄为65.3±12.4岁。六个功能缺损量表（II）维度的收缩值在-0.05至0.09之间；活动量表（AI）的收缩值为0.21。II维度预测值的相关误差大于±1.5个阶段，AI的相关误差大于±24分。
本研究表明，CMSA的II和AI预测值（由置信区间定义）的较大误差限制了它们作为预测指标的临床实用性。有必要进行进一步研究，使用替代统计程序建立预测模型。
