Abstract：
The purpose of this study was to differentiate clinically meaningful improvement or deterioration from normal fluctuations in patients with disorders of consciousness (DoC) following severe brain injury. We computed indices of responsiveness for the Coma Recovery Scale-Revised (CRS-R) using data from a clinical trial of 180 participants with DoC. We used CRS-R scores from baseline (enrollment in a clinical trial) and a 4-week follow-up assessment period for these calculations. To improve precision, we transformed ordinal CRS-R total scores (0-23 points) to equal-interval measures on a 0-100 unit scale using Rasch Measurement theory. Using the 0-100 unit total Rasch measures, we calculated distribution-based 0.5 standard deviation (SD) minimal clinically important difference, minimal detectable change using 95% confidence intervals, and conditional minimal detectable change using 95% confidence intervals. The distribution-based minimal clinically important difference evaluates group-level changes, whereas the minimal detectable change values evaluate individual-level changes. The minimal clinically important difference and minimal detectable change are derived using the overall variability across total measures at baseline and 4 weeks. The conditional minimal detectable change is generated for each possible pair of CRS-R Rasch person measures and accounts for variation in standard error across the scale. We applied these indices to determine the proportions of participants who made a change beyond measurement error within each of the two subgroups, based on treatment arm (amantadine hydrochloride or placebo) or categorization of baseline Rasch person measure to states of consciousness (i.e., unresponsive wakefulness syndrome and minimally conscious state). We compared the proportion of participants in each treatment arm who made a change according to the minimal detectable change and determined whether they also changed to another state of consciousness. CRS-R indices of responsiveness (using the 0-100 transformed scale) were as follows: 0.5SD minimal clinically important difference = 9 units, minimal detectable change = 11 units, and the conditional minimal detectable change ranged from 11 to 42 units. For the amantadine and placebo groups, 70% and 58% of participants showed change beyond measurement error using the minimal detectable change, respectively. For the unresponsive wakefulness syndrome and minimally conscious state groups, 54% and 69% of participants changed beyond measurement error using the minimal detectable change, respectively. Among 115 participants (64% of the total sample) who made a change beyond measurement error, 29 participants (25%) did not change state of consciousness. CRS-R indices of responsiveness can support clinicians and researchers in discerning when behavioral changes in patients with DoC exceed measurement error. Notably, the minimal detectable change can support the detection of patients who make a \"true\" change within or across states of consciousness. Our findings highlight that the continued use of ordinal scores may result in incorrect inferences about the degree and relevance of a change score.
摘要：
这项研究的目的是将严重脑损伤后意识障碍（DoC）患者的临床上有意义的改善或恶化与正常波动区分开。我们使用来自180名DoC参与者的临床试验数据计算昏迷恢复量表修订（CRS-R）的反应性指数。我们使用来自基线的CRS-R评分(临床试验中的登记)和四周的随访评估期来进行这些计算。为了提高精度，我们使用Rasch测量理论将序数CRS-R总分(0~23分)转换为0~100单位量表上的等间隔测量值.使用0到100单位的总Rasch措施，我们计算了基于分布的0.5标准差(SD)最小临床重要差异，使用95%置信区间可检测到的最小变化，和使用95%置信区间的条件最小可检测变化。基于分布的最小临床重要差异评估组水平的变化，而可检测的最小变化值评估个体水平的变化。最小临床重要差异和最小可检测变化是使用基线和四周时总测量的总体变异性得出的。为每个可能的CRS-RRasch人测量对生成条件最小可检测变化，并考虑整个尺度的标准误差变化。我们应用这些指数来确定两个子组中每个子组中做出超出测量误差的更改的参与者的比例，基于治疗臂(盐酸金刚烷胺或安慰剂)或基线Rasch人对意识状态的分类(即，反应迟钝的觉醒综合症和最低意识状态)。我们比较了每个治疗组中根据可检测到的最小变化做出改变的参与者的比例，并确定他们是否也改变为另一种意识状态。CRS-R反应性指数（使用0-100转化量表）如下：0.5SD最小临床重要差异=9个单位，最小可检测变化=11个单位，条件最小可检测变化范围为11到42个单位。对于金刚烷胺和安慰剂组，67%和58%的参与者使用最小的可检测变化表现出超出测量误差的变化，分别。对于反应迟钝的觉醒综合征和最低意识状态组，52%和67%的参与者使用最小的可检测变化超出测量误差，分别。在115名参与者(占总样本的64%)中，他们做出了超出测量误差的改变，29名参与者(25%)没有改变意识状态。反应性的CRS-R指数可以支持临床医生和研究人员辨别DoC患者的行为变化何时超过测量误差。值得注意的是,最小的可检测的变化可以支持对在意识状态内或跨意识状态做出真实变化的患者的检测。我们的发现强调，继续使用序数分数可能会导致对更改分数的程度和相关性的错误推断。
