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Clinico-sero-pathological profiles and risk prediction model of idiopathic inflammatory myopathy (IIM) patients with different perifascicular changes.
Zhang, Lining; Fu, Lijun; Zhang, Guoyong; Hou, Ying; Ma, Xiaotian; Zhao, Dandan; Li, Wei; Dai, Tingjun; Shu, Qiang; Yan, Chuanzhu; Zhao, Bing.
Afiliação
  • Zhang L; Department of Rheumatology, Qilu Hospital of Shandong University, Jinan, Shandong, China.
  • Fu L; Department of Neurology, Qilu Hospital of Shandong University, Jinan, Shandong, China.
  • Zhang G; School of Finance, Southwestern University of Finance and Economics, Chengdu, China.
  • Hou Y; Department of Neurology, Qilu Hospital of Shandong University, Jinan, Shandong, China.
  • Ma X; Department of Neurology, Qilu Hospital of Shandong University, Jinan, Shandong, China.
  • Zhao D; Department of Medicine Experimental Center, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, Shandong, China.
  • Li W; Department of Neurology, Qilu Hospital of Shandong University, Jinan, Shandong, China.
  • Dai T; Department of Neurology, Qilu Hospital of Shandong University, Jinan, Shandong, China.
  • Shu Q; Department of Neurology, Qilu Hospital of Shandong University, Jinan, Shandong, China.
  • Yan C; Department of Rheumatology, Qilu Hospital of Shandong University, Jinan, Shandong, China.
  • Zhao B; Shandong Key Laboratory of Medicine and Prevention Integration in Rheumatism and Immunity Disease, Qilu Hospital of Shandong University, Jinan, Shandong, China.
CNS Neurosci Ther ; 30(8): e14882, 2024 Aug.
Article em En | MEDLINE | ID: mdl-39097917
ABSTRACT

AIMS:

To explore the clinico-sero-pathological characteristics and risk prediction model of idiopathic inflammatory myopathy (IIM) patients with different muscular perifascicular (PF) changes.

METHODS:

IIM patients in our center were enrolled and the clinico-sero-pathological data were retrospectively analyzed. A decision tree model was established through machine learning.

RESULTS:

There were 231 IIM patients enrolled, including 53 with perifascicular atrophy (PFA), 39 with perifascicular necrosis (PFN), and 26 with isolated perifascicular enhancement of MHC-I/MHC-II (PF-MHCn). Clinically, PFA patients exhibited skin rashes and dermatomyositis-specific antibodies (DM-MSAs, 74.5%) except for anti-Mi2. PFN patients showed the most severe muscle weakness, highest creatine kinase (CK), anti-Mi2 (56.8%), and anti-Jo-1 (24.3%) antibodies. PF-MHCn patients demonstrated negative MSAs (48.0%) and elevated CK. Histopathologically, MAC predominantly deposited on PF capillaries in PFA but on non-necrotic myofiber in PFN (43.4% and 36.8%, p < 0.001). MxA expression was least in PF-MHCn (36.0% vs. 83.0% vs. 63.2%, p < 0.001). The decision tree model could effectively predict different subgroups, especially PFA and PFN.

CONCLUSIONS:

Three types of PF change of IIMs representing distinct clinico-serological characteristics and pathomechanism. Undiscovered MSAs should be explored especially in PF-MHCn patients. The three pathological features could be accurately predicted through the decision tree model.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Miosite Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: CNS Neurosci Ther Assunto da revista: NEUROLOGIA / TERAPEUTICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Miosite Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: CNS Neurosci Ther Assunto da revista: NEUROLOGIA / TERAPEUTICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China