{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T23:11:45Z","timestamp":1783120305079,"version":"3.54.6"},"reference-count":40,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2024,8,4]],"date-time":"2024-08-04T00:00:00Z","timestamp":1722729600000},"content-version":"vor","delay-in-days":3,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2023QH364"],"award-info":[{"award-number":["ZR2023QH364"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82071412"],"award-info":[{"award-number":["82071412"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["CNS Neurosci Ther"],"published-print":{"date-parts":[[2024,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Aims<\/jats:title><jats:p>To explore the clinico\u2010sero\u2010pathological characteristics and risk prediction model of idiopathic inflammatory myopathy (IIM) patients with different muscular perifascicular (PF) changes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>IIM patients in our center were enrolled and the clinico\u2010sero\u2010pathological data were retrospectively analyzed. A decision tree model was established through machine learning.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>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\u2010I\/MHC\u2010II (PF\u2010MHCn). Clinically, PFA patients exhibited skin rashes and dermatomyositis\u2010specific antibodies (DM\u2010MSAs, 74.5%) except for anti\u2010Mi2. PFN patients showed the most severe muscle weakness, highest creatine kinase (CK), anti\u2010Mi2 (56.8%), and anti\u2010Jo\u20101 (24.3%) antibodies. PF\u2010MHCn patients demonstrated negative MSAs (48.0%) and elevated CK. Histopathologically, MAC predominantly deposited on PF capillaries in PFA but on non\u2010necrotic myofiber in PFN (43.4% and 36.8%, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001). MxA expression was least in PF\u2010MHCn (36.0% vs. 83.0% vs. 63.2%, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001). The decision tree model could effectively predict different subgroups, especially PFA and PFN.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Three types of PF change of IIMs representing distinct clinico\u2010serological characteristics and pathomechanism. Undiscovered MSAs should be explored especially in PF\u2010MHCn patients. The three pathological features could be accurately predicted through the decision tree model.<\/jats:p><\/jats:sec>","DOI":"10.1111\/cns.14882","type":"journal-article","created":{"date-parts":[[2024,8,4]],"date-time":"2024-08-04T16:59:11Z","timestamp":1722790751000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Clinico\u2010sero\u2010pathological profiles and risk prediction model of idiopathic inflammatory myopathy <scp>(IIM)<\/scp> patients with different perifascicular changes"],"prefix":"10.1111","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7563-6957","authenticated-orcid":false,"given":"Lining","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Rheumatology Qilu Hospital of Shandong University  Jinan Shandong China"},{"name":"Department of Neurology Qilu Hospital of Shandong University  Jinan Shandong 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