کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4933860 | 1433883 | 2017 | 25 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Defining functioning levels in patients with schizophrenia: A combination of a novel clustering method and brain SPECT analysis
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
روانپزشکی بیولوژیکی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
This study aims to define functioning levels of patients with schizophrenia by using a method of interpretable clustering based on a specific functioning scale, the Functional Remission Of General Schizophrenia (FROGS) scale, and to test their validity regarding clinical and neuroimaging characterization. In this observational study, patients with schizophrenia have been classified using a hierarchical top-down method called clustering using unsupervised binary trees (CUBT). Socio-demographic, clinical, and neuroimaging SPECT perfusion data were compared between the different clusters to ensure their clinical relevance. A total of 242 patients were analyzed. A four-group functioning level structure has been identified: 54 are classified as "minimal", 81 as "low", 64 as “moderate”, and 43 as "high". The clustering shows satisfactory statistical properties, including reproducibility and discriminancy. The 4 clusters consistently differentiate patients. “High” functioning level patients reported significantly the lowest scores on the PANSS and the CDSS, and the highest scores on the GAF, the MARS and S-QoL 18. Functioning levels were significantly associated with cerebral perfusion of two relevant areas: the left inferior parietal cortex and the anterior cingulate. Our study provides relevant functioning levels in schizophrenia, and may enhance the use of functioning scale.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Psychiatry Research: Neuroimaging - Volume 270, 30 December 2017, Pages 32-38
Journal: Psychiatry Research: Neuroimaging - Volume 270, 30 December 2017, Pages 32-38
نویسندگان
Faget-Agius Catherine, Vincenti Aurélie, Guedj Eric, Michel Pierre, Richieri Raphaëlle, Alessandrini Marine, Auquier Pascal, Lançon Christophe, Boyer Laurent,