Columbia University, Department of Neurology, New York NY, USA.
Universidade Federal de São Paulo, São Paulo SP, Brazil.
Arq Neuropsiquiatr. 2022 May;80(5):455-461. doi: 10.1590/0004-282X-ANP-2021-0091.
Hemorrhagic transformation (HT) is a complication in ischemic strokes, regardless of use of reperfusion therapy (RT). There are many predictive scores for estimating the risk of HT. However, most of them include patients also treated with RT. Therefore, this may lead to a misinterpretation of the risk of HT in patients who did not undergo RT.
We aimed to review published predictive scores and analyze their accuracy in our dataset.
We analyzed the accuracy of seven scales. Our dataset was derived from a cohort of 1,565 consecutive patients from 2015 to 2017 who were admitted to a comprehensive stroke center. All patients were evaluated with follow-up neuroimaging within seven days. Comparison of area under the curve (AUC) was performed on each scale, to analyze differences between patients treated with recombinant tissue plasminogen activator (tPA) and those without this treatment.
Our dataset provided enough data to assess seven scales, among which six were used among patients with and without tPA treatment. HAT (AUC 0.76), HTI (0.73) and SEDAN (0.70) were the most accurate scores for patients not treated with tPA. SPAN-100 (0.55) had the worst accuracy in both groups. Three of these scores had different cutoffs between study groups.
The predictive scores had moderate to fair accuracy for predicting HT in patients treated with tPA. Three scales were more accurate for predicting HT in patients not treated with tPA. Through standardizing these characteristics and including more patients not treated with RT in a large multicenter series, accurate predictive scores may be created.
无论是否使用再灌注治疗（RT），出血性转化（HT）都是缺血性中风的一种并发症。有许多预测评分用于估计 HT 的风险。然而，大多数评分都包括接受 RT 治疗的患者。因此，这可能导致对未接受 RT 治疗的患者的 HT 风险的错误解释。
我们旨在回顾已发表的预测评分，并分析其在我们的数据集的准确性。
我们分析了七种量表的准确性。我们的数据集来自于 2015 年至 2017 年间，一个综合卒中中心连续收治的 1565 例患者的队列。所有患者在七天内均进行了随访神经影像学评估。对每个量表进行曲线下面积（AUC）的比较，以分析接受重组组织型纤溶酶原激活剂（tPA）治疗和未接受该治疗的患者之间的差异。
我们的数据集提供了足够的数据来评估七种量表，其中六种量表用于有和没有 tPA 治疗的患者。在未接受 tPA 治疗的患者中，HAT（AUC 0.76）、HTI（0.73）和 SEDAN（0.70）是最准确的评分。SPAN-100（0.55）在两组中均具有最差的准确性。这三个评分在研究组之间具有不同的截断值。
预测评分对接受 tPA 治疗的患者预测 HT 具有中等至良好的准确性。对于未接受 tPA 治疗的患者，有三个评分更准确地预测 HT。通过标准化这些特征，并在一个大型多中心系列中纳入更多未接受 RT 治疗的患者，可能会创建更准确的预测评分。
