脑网络改变与ApoB/ApoAⅠ比值对脑卒中合并脑白质病变严重程度的预测价值OA
Predictive value of brain network changes and ApoB/ApoAⅠratio on the severity of stroke with white matter lesions
目的 探讨脑网络改变与载脂蛋白(Apo)B/ApoAⅠ比值对脑卒中合并脑白质病变严重程度的预测价值.方法 选取2021-12-2023-12天水市第一人民医院收治的205例脑卒中合并脑白质病变患者为对象,所有患者均完善头颅磁共振检查.采用Fazekas脑白质病变评测量表评估患者病变严重程度,分为轻度组(Fazekas评分<3分,n=118)和中重度组(Fazekas评分≥3分,n=87),比较2组患者脑结构网络参数,血清ApoB、ApoAⅠ水平及其比值,结合受试者工作特征(ROC)曲线分析,评估上述指标对病变严重程度的预测价值.结果 轻度组在全局效率、局部效率、最短路径长度及集聚系数上均优于中重度组,血清ApoAⅠ水平显著高于中重度组,ApoB/ApoAⅠ比值显著低于中重度组(P<0.05).Logistic回归分析显示,局部效率、全局效率、最短路径长度、聚集系数、血清ApoAⅠ水平及ApoB/ApoAⅠ比值均是影响脑卒中合并脑白质病变严重程度的独立危险因素(P<0.05).ROC曲线分析表明,联合检测脑结构网络参数与ApoB/ApoAⅠ比值能显著提高预测病变严重程度的准确性,AUC达0.910,敏感度93.75%,特异度75.01%.结论 脑网络改变与ApoB/ApoAⅠ比值在脑卒中合并脑白质病变严重程度的预测中具有重要价值,联合检测具有更高的诊断价值,可以更全面地评估患者的病变状态,为临床决策提供有力支持.
Objective To investigate the predictive value of brain network changes and apolipoprotein(Apo)B/ApoAⅠratio on the severity of white matter lesions in stroke patients.Methods A total of 205 patients with stroke complicated by white matter lesions who were admitted to Tianshui First People's Hospital between December 2021 and December 2023 were enrolled in this study.All patients underwent cranial MRI.The severity of white matter lesions was evaluated using the Fazekas scale,and patients were categorized into mild group(Fazekas score<3,n=118)and moderate-to-severe group(Fazekas score≥3,n=87).Brain structural network parameters,serum ApoB and ApoAⅠlevels,and the ApoB/ApoAⅠratio were compared between the two groups.Receiver operating characteristic(ROC)curve analysis was performed to assess the predictive value of these indicators for lesion severity.Results Compared with the moderate-to-severe group,the mild group demonstrated significantly better global efficiency,local efficiency,shortest path length,and clustering coefficient of the brain structural network.Serum ApoAⅠlevels were significantly higher in the mild group,whereas the ApoB/ApoAⅠratio was significantly lower(P<0.05).Logistic regression analysis revealed that local efficiency,global efficiency,shortest path length,clustering coefficient,serum ApoAⅠlevel,and the ApoB/ApoAⅠratio were independent predictors of WML severity in stroke patients(P<0.05).ROC curve analysis showed that the combined assessment of brain structural network parameters and the ApoB/ApoAⅠratio markedly improved the accuracy for predicting lesion severity,yielding the area under the curve(AUC)of 0.910,with the sensitivity of 93.75%and the specificity of 75.01%.Conclusion Brain network changes and ApoB/ApoAⅠratio play important roles in predicting the severity of white matter lesions in stroke patients.Combined detection offers better diagnostic value and can more comprehensively evaluate the extent of lesions,providing robust support for clinical decision-making.
蒲敏;张庆华
甘肃中医药大学,甘肃 兰州 730000天水市第一人民医院,甘肃 天水 741000
医药卫生
脑卒中脑白质病变脑网络结构参数ApoBApoAⅠ血清预测价值
StrokeWhite matter lesionsStructural parameters of brain networkApoBApoAⅠSerumPredicted value
《中国实用神经疾病杂志》 2026 (3)
294-299,6
甘肃省自然科学基金项目(编号:20JR10RA788)
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