The Application of mRS in the Methods of Outcome Assessment in Chinese Stroke Trials / 中国神经精神疾病杂志

ABSTRACT

Objective To evaluate the current situation and problems of the application of modified Rankin scale (mRS) in the outcome assessment in Chinese stroke trials. Methods Randomised and quasi-randomised controlled tri?als on stroke therapy published before September 2013 in 3 Chinese databases were included. All clinical trials applied mRS as the method of outcome assessment. Subarachnoid hemorrhage and transient cerebral ischemia were excluded. Types of stroke, statistical methods used for data analysis, duration of follow up, blinding of outcome assessment, types of intervention and the significance of the results were evaluated. Results Two hundred and ninety-eight trials were includ?ed in this analysis. 71.14%was for ischemic stroke, 21.48%for hemorrhagic stroke, 7.38%for both ischemic and hemor?rhagic stroke and 91.28%was for acute stroke(onset time<14d). Regarding to statistical methods used for data analysis, 50.00%of the trials used t-test or variance analysis which treated the mRS score as continuous data, while 22.15%used rank sum test or Chi-square test which regarded the mRS score as ranked data or multiply variable data. Dichotomous data was applied in statistical analysis accounts for 25.50%of trials. 12.42%trials applied mRS with other scales as the methods of outcome assessment. Duration of follow up ranged from 10d to 2 years (median 90 d, interquartile range 30-90 d). Only 5.03%assessed outcome blindly. 60.07%of the trials were drug therapy, 7.72%was rehabilitation thera?py, 10.40%were surgical treatment, 14.43%were combined therapy, 2.35%were management mode, 0.67%were nurs?ing, and 4.36%other therapy. Results in 86.91%of the trials were favorable to the tested interventions. Conclusions In aspects of, there is large difference between domestic and foreign clinical stroke trials in methodology of mRS including duration of follow up, blinding of outcome assessment and statistical methods used for data analysis.