Yang Yalin, Huang Dingding, Liu Cuicui, Zhong Ningxuan, Peng You, Wang Lulu, Xiao Linlin, Zhao Weiwei
Department of Microbiology Laboratory, Linfen Central Hospital, Linfen, 041000, China.
Department of Anesthesiology, Affiliated Sixth People's Hospital South Campus, Shanghai Jiaotong University, Shanghai, 201499, China.
Heliyon. 2024 Jan 14;10(2):e24523. doi: 10.1016/j.heliyon.2024.e24523. eCollection 2024 Jan 30.
Systemic lupus erythematosus (SLE) is a chronic autoimmune disease involving multi-system and multi-organ dysfunction, and is easily misdiagnosed early in the disease course. We aimed to accurately predict early SLE nomogram to provide a reference basis for the early clinical diagnosis of SLE. : We retrospectively analyzed 167 patients who were first diagnosed with SLE at Fengxian District Central Hospital, Shanghai, between March 2017 and October 2022. Three groups of 129 physically healthy subjects, 67 patients with rheumatoid arthritis, and 40 patients with rashes were selected as controls during the same period. Patients with SLE and control group were randomly divided into training (n = 217) and validation (n = 141) group. Univariate and multivariate analyses were used to identify independent risk factors for early SLE diagnosis. The independent risk factors for diagnosis were used to construct a nomogram to predict early SLE. Based on the training group, three variables were identified as independently influencing early SLE: platelets (odds ratio OR = 0.993, P = 0.047), albumin (OR = 0.833, P = 0.007), and complement component 1q (OR = 0.956, P = 0.000). The precision of the nomogram was assessed using C-index values and calibration plot diagrams. The C-index values were 0.929 for training group and 0.898 for validation group. Both the training group and validation group calibration curves showed good predicted outcomes. The construction of a nomogram can accurately predict the risk of early SLE. The model showed good discriminatory power and calibration for use in the diagnosis of SLE, providing a visual tool and reference basis for the early diagnosis of SLE.
系统性红斑狼疮（SLE）是一种涉及多系统和多器官功能障碍的慢性自身免疫性疾病，在疾病早期很容易被误诊。我们旨在构建准确预测早期SLE的列线图，为SLE的早期临床诊断提供参考依据。我们回顾性分析了2017年3月至2022年10月期间在上海奉贤区中心医院首次诊断为SLE的167例患者。同期选取129名身体健康受试者、67例类风湿关节炎患者和40例皮疹患者作为对照组。将SLE患者和对照组随机分为训练组（n = 217）和验证组（n = 141）。采用单因素和多因素分析确定早期SLE诊断的独立危险因素。将诊断的独立危险因素用于构建预测早期SLE的列线图。基于训练组，确定了三个独立影响早期SLE的变量：血小板（比值比OR = 0.993，P = 0.047）、白蛋白（OR = 0.833，P = 0.007）和补体成分1q（OR = 0.956，P = 0.000）。使用C指数值和校准曲线图评估列线图的准确性。训练组的C指数值为0.929，验证组为0.898。训练组和验证组的校准曲线均显示出良好的预测结果。列线图的构建可以准确预测早期SLE的风险。该模型在SLE诊断中显示出良好的辨别力和校准能力，为SLE的早期诊断提供了一种可视化工具和参考依据。
