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Risk Factors for Massive Cerebral Infarction in Pediatric Patients With Moyamoya Disease
Fangbin Hao1, Gan Gao1, Qingbao Guo1
1Department of Neurosurgery, Chinese PLA General Hospital, Beijing, China; Chinese PLA Medical School, Beijing, China; Department of Neurosurgery, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, China.
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.
Insights
Family history, higher MRA scores, poor collateral circulation, and RNF213 variations increase the risk of massive cerebral infarction (MCI) in children with moyamoya disease (MMD). Early identification of these risk factors aids timely intervention.
Area of Science:
- Neurology
- Pediatric Medicine
- Genetics
Background:
- Moyamoya disease (MMD) is a rare cerebrovascular disorder.
- Pediatric MMD patients face risks of preoperative massive cerebral infarction (MCI).
- Identifying MCI risk factors is crucial for early intervention.
Purpose of the Study:
- To explore risk factors for preoperative MCI in pediatric moyamoya disease patients.
- To develop a predictive model for MCI in this population.
Main Methods:
- Retrospective analysis of 308 pediatric MMD patients (2017-2022).
- Logistic regression and nomogram construction to identify MCI predictors.
- Receiver operating characteristic (ROC) curve analysis for risk factor assessment.
Main Results:
- 36 pediatric MMD patients developed MCI.
- Key risk factors identified: family history, higher MRA score, lower collateral circulation score, and RNF213 p.R4810K variations.
- A nomogram and integrated ROC model showed high predictive accuracy (85.11%).
Conclusions:
- Family history, elevated MRA score, reduced collateral circulation, and RNF213 variations are significant MCI risk factors in pediatric MMD.
- The developed predictive model demonstrates superior efficacy for early risk identification.
- Timely intervention based on predictive models can improve patient outcomes.
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