National Institutes of Health Stroke Scale Item Profiles as Predictor of Patient Outcome External Validation on Independent Trial Data
National Institutes of Health Stroke Scale Item Profiles as Predictor of Patient Outcome External Validation on Independent Trial Data
复制标题
DOI：
10.1161/strokeaha.114.006837
复制
发表时间：
2015-02-01
期刊：
影响因子：
8.3
通讯作者：
Lees, Kennedy R.
中科院分区：
文献类型：
--
作者：
Abdul-Rahim, Azmil H.;Fulton, Rachael L.;Lees, Kennedy R.
背景和目的——最近提出的美国国立卫生研究院卒中量表（NIHSS）项目概况可能在临床和研究中都有用。我们的目的是在一个急性队列中验证NIHSS项目概况。方法：我们对随机临床试验的汇总数据进行回顾性分析。我们应用衍生研究中发展出来的特征隶属度的潜在类分析概率来获得症状分组，a-NIHSS项目特征。我们实施了独立的潜在类别分析，以获得次要症状分组，b-NIHSS项目概况。通过评估与结果的关联以及评估两组NIHSS项目概况对数据的辨别和校准来进行验证。评估的结果包括第90天的修正Rankin量表（mRS；采用完全分布和二分类，mRS, 0-1）和90天的死亡率。结果：我们确定了10 271例患者。mRS的顺序分析证实，对于每组NIHSS项目概况，根据年龄和溶栓治疗进行调整，以逐步方式增加了获得更好结果的几率。在mRS 0到1之间观察到类似的模式，而在死亡率上观察到相反的模式。a-NIHSS和b-NIHSS项目资料在mRS 0 ~ 1时的c统计量相似，分别为0.71（95%可信区间0.70 ~ 0.72）和0.74（0.73 ~ 0.75）和0.75（0.73 ~ 0.76）。校准良好。结论：这些NIHSS项目概况通过潜在类别分析确定，提供了一种可靠的方法来捕捉与脑卒中后功能、结果和死亡率相关的真实反应模式。这种方法有可能提高NIHSS总体评分的临床价值。
Background and Purpose-National Institutes of Health Stroke Scale (NIHSS) item profiles that were recently proposed may prove useful both clinically and for research studies. We aimed to validate the NIHSS item profiles in an acute cohort.Methods-We conducted a retrospective analysis on pooled data from randomized clinical trials. We applied the latent class analysis probabilities of profile membership developed from the derivation study to obtain symptom grouping, a-NIHSS item profiles. We implemented an independent latent class analysis to derive secondary symptom grouping, b-NIHSS item profiles. Validation was performed by assessing the associations with outcomes and evaluating both sets of NIHSS item profiles' discrimination and calibration to the data. The outcomes evaluated included modified Rankin Scale (mRS; using the full distribution and dichotomized, mRS, 0-1) at day 90 and mortality by 90 days.Results-We identified 10 271 patients. Ordinal analysis of mRS confirmed increased odds of better outcome across the profiles in a stepwise manner, adjusted for age and thrombolysis treatment, for each set of NIHSS item profiles. Similar patterns were observed for mRS 0 to 1, and inverse patterns were seen for mortality. The c-statistics of a-NIHSS and b-NIHSS item profiles for mRS 0 to 1 were similar at 0.71 (95% confidence interval, 0.70-0.72) and for mortality, 0.74 (0.73-0.75) and 0.75 (0.73-0.76), respectively. Calibration was good.Conclusions-These NIHSS item profiles identified using latent class analysis offer a reliable approach to capture the true response patterns that are associated with functional and outcome and mortality post stroke. This approach has the potential to enhance the clinical value of the overall NIHSS score.