{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T11:43:03Z","timestamp":1768218183670,"version":"3.49.0"},"reference-count":28,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T00:00:00Z","timestamp":1768176000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurol."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To investigate factors influencing somatic symptom disorder (SSD) in epilepsy patients and construct a cut-off point prediction model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using structured interviews and based on DSM-5 diagnostic criteria, the 206 epilepsy patients included in this study were categorized into SSD and non-SSD (n-SSD) groups. Demographic and clinical data were collected, and assessments were conducted using the Quality of Life in Epilepsy (QOLIE-31), Generalized Anxiety Disorder-7 (GAD-7), Neuropsychiatric Disease and Disability Inventory-Extended (NDDI-E), and Pittsburgh Sleep Quality Index (PSQI). Age, negative life events, seizure anxiety, energy\/fatigue, GAD-7, NDDI-E, and PSQI scores were identified as independent risk factors for SSD comorbidity in epilepsy. The constructed cut-off model demonstrated good predictive performance. External validation in an independent multicenter cohort is required prior to clinical implementation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Compared with the n-SSD group, the SSD group exhibited statistically significant differences in age, age at onset, years of education, place of residence, number of comorbid physical illnesses, and adverse life events (all\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt;\u20090.05). The SSD group also showed significantly higher scores on GAD-7, NDDI-E, and PSQI, but lower total QOLIE-31 score and lower subscale scores for seizure worry, medication effects, energy\/fatigue, life satisfaction, social functioning, and emotional well-being (all\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt;\u20090.05). Multivariate logistic regression analysis revealed that age (OR\u2009=\u20091.076, 95% CI: 1.015\u20131.141), negative life events(OR\u2009=\u20096.624, 95% CI: 2.130\u201320.606), seizure anxiety (OR\u2009=\u20090.945, 95% CI: 0.895\u20130.999), energy\/fatigue (OR\u2009=\u20090.923, 95% CI: 0.872\u20130.977), and GAD-7 (OR\u2009=\u20091.274, 95% CI: 1.015\u20131.274) were independently associated with higher QOLIE-31 total scores. Fatigue (OR\u2009=\u20090.923, 95% CI: 0.872\u20130.977), GAD-7 (OR\u2009=\u20091.274, 95% CI: 1.037\u20131.565), NDDI-E (OR\u2009=\u20091.233, 95% CI: 1.038\u20131.442), and PSQI (OR\u2009=\u20091.375, 95% CI: 1.097\u20131.723) were independent predictors of SSD. The AUC of the nomogram model constructed based on the aforementioned factors was 0.939 (95% CI: 0.904\u20130.975), with an AUC of 0.907 following internal validation. The optimal risk probability cutoff value was 0.200 (based on the Yorden index), yielding a sensitivity of 84.7% and specificity of 95.3%. Calibration curve and decision curve analyses demonstrated good model calibration and clinical net benefit.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Older age, exposure to negative life events, higher GAD-7, NDDI-E, and PSQI scores, and lower scores on the seizure worry and energy\/fatigue dimensions of QOLIE-31 are independent risk factors for SSD in epilepsy patients. The constructed nomogram model demonstrates favorable predictive performance. External validation within an independent multicenter cohort is required prior to clinical implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fneur.2025.1758811","type":"journal-article","created":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T08:43:25Z","timestamp":1768207405000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["The construction and validation of a clinical predictive model for somatic symptom disorders in epilepsy 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