Establishment and verification of risk nomogram model for attention deficit hyperactivity disorder in epileptic patients

doi:10.19854/j.cnki.1008-2425.2025.03.0003

Abstract

Abstract: Objective A total of 218 patients with epilepsy admitted to our hospital from March.Methods 2020 to September 2022 were divided into observation group (142 cases) and control group (76 cases) according to whether they had ADHD.Univariate and Cox regression analysis of the risk factors of epilepsy co-ADHD and the construction of a competitive risk model for internal and external verification.Recursive segmentation method is used to establish the risk stratification system.Results Univariate analysis showed that there were statistically significant differences in age,E2,TSTO,course of disease,age of first onset,education level,type of seizure (generalized seizure),antiepileptic drugs and EEG abnormalities between the observation group and the control group (P＜0.05).Age (>22 years old),course of disease (>10 years old),age of first onset (>7 years old),education level (college degree or above),antiepileptic drugs (multidrugcombination),type of seizure (generalized seizure),and abnormal EEG were the risk factors for co-epileptic ADHD (P＜0.05).The analysis results of the nomogram model showed that the risk probability of epilepsy comorbid ADHD was 96.74%,and the prediction model had a good degree of differentiation and calibration.The external validation sensitivity of the model was 85.9%,the specificity 84.8%,and the total accuracy 84.7%.Conclusion Based on the risk factors and competing risk model of epilepsy with ADHD,a prediction and evaluation method was constructedin this study to provide scientific basis for clinical screening of high-risk population with epilepsy with ADHD.

Key words: Nomogram model, Epilepsy, Attention deficit hyperactivity disorder, Risk factors

摘要： 目的应用竞争风险模型探究癫痫病人注意缺陷多动障碍(ADHD)的风险及影响因素。方法以2020年3月至2022年9月我院收治的218例癫痫病人作为研究对象,根据病人是否共患ADHD分为观察组(142例)和对照组(76例)。单因素和Cox回归分析癫痫共患ADHD的危险因素及构建竞争风险模型,进行内外部验证。采用递归分割法建立危险分层系统。结果单因素分析结果显示,观察组和对照组在年龄、E2、TSTO、病程、首次发病年龄、受教育程度、癫痫发作类型(全面性发作)、抗癫痫用药、脑电图异常方面存在差异均有统计学意义(P＜0.05)。年龄(＞22岁)、病程(＞10年)、首次发病年龄(＞7岁)、受教育程度(大专及以上)、抗癫痫用药(多药联用)、癫痫发作类型(全面性发作)、脑电图异常是癫痫共患ADHD的危险因素(P＜0.05)。列线图模型分析结果显示,癫痫共患ADHD的风险概率为96.74%,且预测模型具有较好的区分度和校准度。模型外部验证敏感度85.9%,特异度84.8%,总准确率84.7%。结论本研究基于癫痫共患ADHD的危险因素和竞争风险模型,构建癫痫共患ADHD的预测评估方法,为临床上筛查癫痫共患ADHD的高危人群提供科学依据。

关键词: 列线图模型, 癫痫, 注意缺陷多动障碍, 危险因素

CLC Number:

R742.1

Guan Yunli, Huang Jiajun, Li Lang, Deng Qunhua. Establishment and verification of risk nomogram model for attention deficit hyperactivity disorder in epileptic patients[J]. Chinese Journal of Stereotactic and Functional Neurosurgery, 2025, 38(3): 144-149.

官云里, 黄家俊, 李朗, 邓群华. 癫痫患者注意缺陷多动障碍风险列线图模型的建立及验证[J]. 立体定向和功能性神经外科杂志, 2025, 38(3): 144-149.

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