Department of Ophthalmology, Chongqing Key Laboratory for the Prevention and Treatment of Major Blinding Eye Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China.
Clin Rheumatol. 2024 Sep;43(9):2899-2910. doi: 10.1007/s10067-024-07034-y. Epub 2024 Jul 13.
This study aimed to explore ocular manifestations in ANCA-associated vasculitis (AAV), focusing on granulomatosis with polyangiitis (GPA), eosinophilic granulomatosis with polyangiitis (EGPA), and microscopic polyangiitis (MPA) and to examine the associations with laboratory parameters and other systemic manifestations.
This retrospective study reviewed data from 533 AAV patients across two major Chinese medical centers from January 2016 to November 2023. Data including diagnosis, cranial manifestations of disease, ocular complications, and laboratory parameters were analyzed. Univariate and multivariable logistic regression analyses assessed associations across disease manifestations. Machine learning models were also utilized to predict the risk of retinal/eye involvement in AAV patients.
Among 533 patients (210 GPA, 217 MPA, 99 EGPA, and 7 unclassified AAV), ocular complications were observed in 20.64% of them, with a distribution of 36.67% in GPA, 7.37% in MPA, and 18.18% in EGPA. The most common ocular manifestations included scleritis and retro-orbital mass/dacryocystitis, which were notably prevalent in GPA patients. Retinal involvement was observed in 9.09% of EGPA cases. The machine learning models yielded that eosinophil percentage (EOS%), high-sensitivity C-reactive protein (hsCRP), and CD4 + T cell/CD8 + T cell ratio (T4/T8) can predict retinal involvement. Furthermore, the white blood cell, EOS%, APTT, IgA, hsCRP, PR3-ANCA, and T4/T8 can predict eye involvement.
Ocular manifestations are a prevalent complication across all forms of AAV. Predictive models developed through machine learning offer promising tools for early intervention and tailored patient care. This necessitates a multidisciplinary approach, integrating rheumatology and ophthalmology expertise for optimal patient outcomes.
本研究旨在探讨抗中性粒细胞胞浆抗体(ANCA)相关性血管炎(AAV)的眼部表现,重点关注肉芽肿性多血管炎(GPA)、嗜酸性肉芽肿性多血管炎(EGPA)和显微镜下多血管炎(MPA),并研究其与实验室参数和其他系统表现的关系。
本回顾性研究分析了 2016 年 1 月至 2023 年 11 月来自中国两家主要医疗中心的 533 例 AAV 患者的数据。数据包括诊断、疾病的颅部表现、眼部并发症和实验室参数。单变量和多变量逻辑回归分析评估了疾病表现之间的关联。还利用机器学习模型预测 AAV 患者视网膜/眼部受累的风险。
在 533 例患者(210 例 GPA、217 例 MPA、99 例 EGPA 和 7 例未分类 AAV)中,20.64%的患者出现眼部并发症,其中 GPA 患者的分布为 36.67%,MPA 患者为 7.37%,EGPA 患者为 18.18%。最常见的眼部表现包括巩膜炎和眼眶肿块/泪囊炎,这些表现主要见于 GPA 患者。9.09%的 EGPA 病例出现视网膜受累。机器学习模型显示,嗜酸性粒细胞百分比(EOS%)、高敏 C 反应蛋白(hsCRP)和 CD4+T 细胞/CD8+T 细胞比值(T4/T8)可预测视网膜受累。此外,白细胞、EOS%、APTT、IgA、hsCRP、PR3-ANCA 和 T4/T8 可预测眼部受累。
眼部表现是所有 AAV 形式的常见并发症。通过机器学习开发的预测模型为早期干预和个体化患者护理提供了有前途的工具。这需要多学科方法,整合风湿病学和眼科学专业知识,以获得最佳的患者结局。