Construction and validation of clinical prediction model of somatic symptom disorder in epilepsy patients
10.3969/j.issn.1004-1648.2025.04.014
- VernacularTitle:癫痫患者躯体症状障碍临床预测模型的构建与验证研究
- Author:
Wenjing SHEN
1
;
Changguo ZHANG
;
Zhongxia SHEN
Author Information
1. 313000 湖州市第三人民医院神经内科
- Publication Type:Journal Article
- Keywords:
epilepsy comorbidity;
somatic symptom disorder;
prediction model
- From:
Journal of Clinical Neurology
2025;38(4):283-289
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the influencing factors of somatic symptom disorder(SSD)in patients with epilepsy,and to construct a nomogram prediction model.Methods Using structured interviews,according to the diagnostic criteria of Diagnostic and Statistical Manual of Mental Disorders(Fourth Edition),206 patients with epilepsy included in this study were divided into SSD group and non-SSD(n-SSD)group.The clinical data of the two groups were compared.The quality of life in epilepsy inventory(QOLIE-31),general anxiety disorder-7(GAD-7),neurological disorders depression inventory for epilepsy(NDDI-E)and Pittsburgh sleep quality index(PSQI)were used to evaluate the anxiety,depression and sleep of patients.LASSO regression was used for variable screening,and Logistic regression model was used to explore the risk factors of SSD in patients with epilepsy.Based on these factors,a nomogram was constructed and the area under the ROC curve(AUC)was calculated and verified internally.Calibration curve and decision curve analysis were used to evaluate the calibration and clinical utility of the nomogram,respectively.Results Compared with those in the n-SSD group,there were significant differences in age,age of onset,educational background,place of residence,number of physical diseases and negative life events in the SSD group(all P＜0.05).Compared with those in the n-SSD group,GAD-7 score,NDDI-E score,PSQI score,total score of QOLIE-31 and the scores of seizure worry,drug influence,energy/fatigue,life satisfaction,social function and emotion in the SSD group were significantly lower(all P＜0.05).Multivariate Logistic regression analysis showed that age(OR=1.076,95％CI:1.015-1.141),negative life events(OR=6.624,95％CI:2.130-20.606),seizure worry(OR=0.945,95％CI:0.895-0.999),energy/fatigue(OR=0.923,95％CI:0.872-0.977),GAD-7 score(OR=1.274,95％CI:1.037-1.565),NDDI-E score(OR=1.233,95％CI:1.038-1.442),PSQI score(OR=1.375,95％CI:1.097-1.723)were independent predictors of SSD.According to the variables in the results of multivariate Logistic regression analysis and their corresponding regression coefficients,the nomogram of SSD in patients with epilepsy was established.The AUC of the nomogram was 0.939(95％CI:0.904-0.975),the best cut-off value was 0.200,the sensitivity was 0.847,the specificity was 0.953,and the discrimination was good.The decision curve risk threshold showed that the model provides significant clinical net benefits.Conclusions Age,negative life events,seizure concerns,energy/fatigue,GAD-7 score,NDDI-E score and PSQI score are risk factors for epileptic SSD.The columniogram model constructed based on the above factors can effectively predict the risk of epileptic SSD.
