five

Supplemental materials for publication “Distinguishing Stevens-Johnson syndrome/toxic epidermal necrolysis from clinical mimickers during inpatient dermatologic consultation – a retrospective chart review.” JAAD. 2019.

收藏
doi.org2025-01-15 收录
下载链接:
http://doi.org/10.17632/kzm64tt5k7.1
下载链接
链接失效反馈
官方服务:
资源简介:
Statistical analysis here replicates that performed in the primary manuscript with addition of mucosal involvement (either present or absent) as reported in Supplemental Table 1. Stepwise regression of all significant variables including mucosal involvement yielded an updated model with four predictor variables. A new multivariable model was fit with Nikolsky sign (adjusted OR 49.0, 95% CI 10.6-226.2, p-value <0.001); atypical targets (adjusted OR 26.5, 95% CI 5.5-127.3, p<0.001); fever (adjusted OR 7.6, 95% CI 1.8-33.0, p-value=0.007); mucosal involvement (adjusted OR 21.3, 95% CI 4.1-110.7, p-value <0.001); OR (odds ratio); CI (confidence interval). This new multivariable model for the probability of Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN) is defined as indicated in Supplemental Figure 1. This updated model yields a 91.5% sensitivity and 94.6% specificity with a corresponding positive and negative predictive values of 87.1% and 96.6%, respectively. The AUC for the final model is 0.98 (95% confidence interval 0.96, >0.99 and p-value<0.001). Supplemental Figure 2 is a nomogram which provides the relative contributions of each predictor, including mucosal involvement, to the probability of SJS/TEN.

此处对主稿中进行的统计分析进行了复制,并增加了黏膜受累(无论是否存在)的信息,具体数据详见表1补充资料。逐步回归分析所有显著变量,包括黏膜受累,得出了包含四个预测变量的更新模型。通过拟合新的大变量模型,纳入了尼科尔斯基征(调整后的比值比 49.0,95% 置信区间 10.6-226.2,p 值 <0.001);非典型靶点(调整后的比值比 26.5,95% 置信区间 5.5-127.3,p 值 <0.001);发热(调整后的比值比 7.6,95% 置信区间 1.8-33.0,p 值=0.007);黏膜受累(调整后的比值比 21.3,95% 置信区间 4.1-110.7,p 值 <0.001);OR(优势比);CI(置信区间)。此新多变量模型定义了史蒂文斯-约翰逊综合征/中毒性表皮坏死松解症(SJS/TEN)的发生概率,具体说明如补充图1所示。此更新模型具有91.5%的敏感度和94.6%的特异性,相应的阳性预测值和阴性预测值分别为87.1%和96.6%。最终模型的AUC为0.98(95%置信区间 0.96,>0.99且p值<0.001)。补充图2是一个诺模图,显示了包括黏膜受累在内的每个预测变量对SJS/TEN发生概率的相对贡献。
提供机构:
Mendeley Data
二维码
社区交流群
二维码
科研交流群
商业服务