Network analysis of clinical features in patients with treatment-resistant schizophrenia
ObjectiveThis study compares the clinical features of Treatment-Resistant Schizophrenia (TRS) and Non-Treatment-Resistant Schizophrenia (NTRS) using network analysis.MethodsWe recruited 511 patients, dividing them into TRS (N = 269) and NTRS (N = 242) groups. Eight scales were used: Positive and Neg...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1537418/full |
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| author | Wei Li Jing Zhao Na Hu Wanling Zhang |
| author_facet | Wei Li Jing Zhao Na Hu Wanling Zhang |
| author_sort | Wei Li |
| collection | DOAJ |
| description | ObjectiveThis study compares the clinical features of Treatment-Resistant Schizophrenia (TRS) and Non-Treatment-Resistant Schizophrenia (NTRS) using network analysis.MethodsWe recruited 511 patients, dividing them into TRS (N = 269) and NTRS (N = 242) groups. Eight scales were used: Positive and Negative Syndrome Scale (PANSS), Positive Symptom Assessment Scale (SAPS), Scale for Assessment of Negative Symptoms (SANS), Simpson-Angus Scale (SAS), Abnormal Involuntary Movements Scale (AIMS), Barnes Akathisia Rating Scale (BARS), Calgary Schizophrenia Depression Scale (CDSS), and Global Assessment of Functioning Scale (GAF). Demographic and clinical data were analyzed using T-tests and Chi-square tests. Network analysis was then applied to compare clinical features.ResultsSignificant differences were found in the overall architectures (S = 1.396, p < 0.002) and edge weights (M = 0.289, p < 0.009) of TRS and NTRS networks. Nine edges (p < 0.05) and five nodes (p < 0.01) differed, indicating a correlation between clinical symptoms of the two groups. TRS core symptoms were linked to social functions through both positive (SAPS) and negative symptoms (SANS), while NTRS core symptoms were related to general psychopathological symptoms (PANSS-G).ConclusionFor TRS, it is essential to address both negative and positive symptoms, focusing on the impact of negative symptoms on functioning. Additionally, managing medication side effects is crucial to avoid worsening negative symptoms. |
| format | Article |
| id | doaj-art-f7082358b2f349989dcb4f8409937717 |
| institution | Kabale University |
| issn | 1664-0640 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj-art-f7082358b2f349989dcb4f84099377172025-02-06T07:10:22ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402025-02-011610.3389/fpsyt.2025.15374181537418Network analysis of clinical features in patients with treatment-resistant schizophreniaWei Li0Jing Zhao1Na Hu2Wanling Zhang3Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, ChinaCollege of Art and Design, Beijing University of Technology, Beijing, ChinaDepartment of Psychosomatic Medicine, Beijing Children’s Hospital, Capital Medical University, National Center for Children Healthy, Beijing, ChinaDepartment of Psychosomatic Medicine, Beijing Children’s Hospital, Capital Medical University, National Center for Children Healthy, Beijing, ChinaObjectiveThis study compares the clinical features of Treatment-Resistant Schizophrenia (TRS) and Non-Treatment-Resistant Schizophrenia (NTRS) using network analysis.MethodsWe recruited 511 patients, dividing them into TRS (N = 269) and NTRS (N = 242) groups. Eight scales were used: Positive and Negative Syndrome Scale (PANSS), Positive Symptom Assessment Scale (SAPS), Scale for Assessment of Negative Symptoms (SANS), Simpson-Angus Scale (SAS), Abnormal Involuntary Movements Scale (AIMS), Barnes Akathisia Rating Scale (BARS), Calgary Schizophrenia Depression Scale (CDSS), and Global Assessment of Functioning Scale (GAF). Demographic and clinical data were analyzed using T-tests and Chi-square tests. Network analysis was then applied to compare clinical features.ResultsSignificant differences were found in the overall architectures (S = 1.396, p < 0.002) and edge weights (M = 0.289, p < 0.009) of TRS and NTRS networks. Nine edges (p < 0.05) and five nodes (p < 0.01) differed, indicating a correlation between clinical symptoms of the two groups. TRS core symptoms were linked to social functions through both positive (SAPS) and negative symptoms (SANS), while NTRS core symptoms were related to general psychopathological symptoms (PANSS-G).ConclusionFor TRS, it is essential to address both negative and positive symptoms, focusing on the impact of negative symptoms on functioning. Additionally, managing medication side effects is crucial to avoid worsening negative symptoms.https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1537418/fullTRSNTRSnetwork analysispsychopathological symptomsclinical features |
| spellingShingle | Wei Li Jing Zhao Na Hu Wanling Zhang Network analysis of clinical features in patients with treatment-resistant schizophrenia Frontiers in Psychiatry TRS NTRS network analysis psychopathological symptoms clinical features |
| title | Network analysis of clinical features in patients with treatment-resistant schizophrenia |
| title_full | Network analysis of clinical features in patients with treatment-resistant schizophrenia |
| title_fullStr | Network analysis of clinical features in patients with treatment-resistant schizophrenia |
| title_full_unstemmed | Network analysis of clinical features in patients with treatment-resistant schizophrenia |
| title_short | Network analysis of clinical features in patients with treatment-resistant schizophrenia |
| title_sort | network analysis of clinical features in patients with treatment resistant schizophrenia |
| topic | TRS NTRS network analysis psychopathological symptoms clinical features |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1537418/full |
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