Pediatric neurology · 2024
Risk Factors for Massive Cerebral Infarction in Pediatric Patients With Moyamoya Disease.
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Hao Fangbin, Gao Gan, Guo Qingbao, Liu Simeng, Wang Minjie, Chang Zhengyao, Wang Hui, Lu Mingming, Liu Shitong, Zou Zhengxing, Zhang Qian, Wang Xiaopeng, Fu Heguan, Li Jingjie, Han Cong, Duan Lian
Аннотация
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.