Abstract：
BACKGROUND: To explore the risk factors for preoperative massive cerebral infarction (MCI) in pediatric patients with moyamoya disease (MMD).
METHODS: Pediatric patients with MMD treated between 2017 and 2022 were enrolled. Logistic regression analysis was performed to identify risk factors for MCI among the patients, and a nomogram was constructed to identify potential predictors of MCI. Receiver operating characteristic (ROC) curves and areas under the curves were calculated to determine the effects of different risk factors.
RESULTS: This study included 308 pediatric patients with MMD, including 36 with MCI. The MCI group exhibited an earlier age of onset than the non-MCI group. Significant intergroup differences were observed in familial MMD history, postcirculation involvement, duration from diagnosis to initiation of treatment, Suzuki stage, magnetic resonance angiography (MRA) score, collateral circulation score, and RNF213 p.R4810K variations. Family history, higher MRA score, lower collateral circulation score, and RNF213 p.R4810K variations were substantial risk factors for MCI in pediatric patients with MMD. The nomogram demonstrated excellent discrimination and calibration capabilities. The integrated ROC model, which included all the abovementioned four variables, showed superior diagnostic precision with a sensitivity of 67.86%, specificity of 87.01%, and accuracy of 85.11%.
CONCLUSIONS: This study showed that family history, elevated MRA score, reduced collateral circulation score, and RNF213 p.R4810K variations are risk factors for MCI in pediatric patients with MMD. The synthesized model including these variables demonstrated superior predictive efficacy; thus, it can facilitate early identification of at-risk patients and timely initiation of appropriate interventions.
METHODS: Pediatric patients with MMD treated between 2017 and 2022 were enrolled. Logistic regression analysis was performed to identify risk factors for MCI among the patients, and a nomogram was constructed to identify potential predictors of MCI. Receiver operating characteristic (ROC) curves and areas under the curves were calculated to determine the effects of different risk factors.
RESULTS: This study included 308 pediatric patients with MMD, including 36 with MCI. The MCI group exhibited an earlier age of onset than the non-MCI group. Significant intergroup differences were observed in familial MMD history, postcirculation involvement, duration from diagnosis to initiation of treatment, Suzuki stage, magnetic resonance angiography (MRA) score, collateral circulation score, and RNF213 p.R4810K variations. Family history, higher MRA score, lower collateral circulation score, and RNF213 p.R4810K variations were substantial risk factors for MCI in pediatric patients with MMD. The nomogram demonstrated excellent discrimination and calibration capabilities. The integrated ROC model, which included all the abovementioned four variables, showed superior diagnostic precision with a sensitivity of 67.86%, specificity of 87.01%, and accuracy of 85.11%.
CONCLUSIONS: This study showed that family history, elevated MRA score, reduced collateral circulation score, and RNF213 p.R4810K variations are risk factors for MCI in pediatric patients with MMD. The synthesized model including these variables demonstrated superior predictive efficacy; thus, it can facilitate early identification of at-risk patients and timely initiation of appropriate interventions.
摘要：
背景：探讨烟雾病（MMD）患儿术前发生大面积脑梗死（MCI）的危险因素。
方法：纳入2017年至2022年接受MMD治疗的儿科患者。采用Logistic回归分析确定MCI患者的危险因素,并构建列线图以确定MCI的潜在预测因子。计算受试者工作特征（ROC）曲线和曲线下面积，以确定不同风险因素的影响。
结果：这项研究包括308名患有MMD的儿科患者，包括36与MCI。MCI组比非MCI组表现出更早的发病年龄。在家族性MMD病史中观察到显著的组间差异，后循环参与，从诊断到开始治疗的持续时间，铃木舞台，磁共振血管造影(MRA)评分,侧支循环评分,和RNF213p.R4810K变体。家族史,MRA评分更高,较低的侧支循环评分，和RNF213p.R4810K变异是MMD儿科患者MCI的重要危险因素。列线图显示了出色的辨别和校准能力。集成的ROC模型，其中包括所有上述四个变量，显示出较高的诊断精度，灵敏度为67.86%，特异性为87.01%，准确率为85.11%。
结论：这项研究表明，家族史，MRA评分升高,侧支循环评分降低，和RNF213p.R4810K变异是MMD儿科患者MCI的危险因素。包括这些变量的综合模型表现出优异的预测功效；因此，它可以促进早期识别高危患者并及时启动适当的干预措施.
方法：纳入2017年至2022年接受MMD治疗的儿科患者。采用Logistic回归分析确定MCI患者的危险因素,并构建列线图以确定MCI的潜在预测因子。计算受试者工作特征（ROC）曲线和曲线下面积，以确定不同风险因素的影响。
结果：这项研究包括308名患有MMD的儿科患者，包括36与MCI。MCI组比非MCI组表现出更早的发病年龄。在家族性MMD病史中观察到显著的组间差异，后循环参与，从诊断到开始治疗的持续时间，铃木舞台，磁共振血管造影(MRA)评分,侧支循环评分,和RNF213p.R4810K变体。家族史,MRA评分更高,较低的侧支循环评分，和RNF213p.R4810K变异是MMD儿科患者MCI的重要危险因素。列线图显示了出色的辨别和校准能力。集成的ROC模型，其中包括所有上述四个变量，显示出较高的诊断精度，灵敏度为67.86%，特异性为87.01%，准确率为85.11%。
结论：这项研究表明，家族史，MRA评分升高,侧支循环评分降低，和RNF213p.R4810K变异是MMD儿科患者MCI的危险因素。包括这些变量的综合模型表现出优异的预测功效；因此，它可以促进早期识别高危患者并及时启动适当的干预措施.
