OBJECTIVE: To stratify systemic lupus erythematosus (SLE) patients clinically, to analyze the clinical characteristics of patients with and without disease activity, and to explore the application va-lue of key clinical indicators in assessing disease activity, as well as to construct an evaluation model. METHODS: A retrospective analysis was conducted on clinical data of the SLE patients diagnosed at Peking University People' s Hospital from May 1995 to April 2014. Demographic information, clinical manifestations, laboratory tests, and antibody detection results were collected. The patients were divided into active and inactive groups based on systemic lupus erythematosus disease activity index 2000(SLEDAI-2000)scores. t-tests, Mann-Whitney U tests, and χ² tests were used to compare the differences between the groups. Spearman correlation analysis was used to evaluate the relevant clinical indicators associated with SLE activity in the active disease group. Based on the results of statistical analysis, a Logistic regression model was constructed, and the performance of the model was evaluated. RESULTS: No significant differences were found in demographic characteristics between the two groups. In the active disease group, positive rates of antinuclear antibodies (ANA) and anti-double-stranded DNA antibodies (anti-dsDNA) were increased; white blood cell count (WBC), red blood cell count (RBC), hemoglobin (HGB), lymphocytes (LY), total protein (TP), albumin (ALB), and complement 3(C3) levels were significantly decreased; while immunoglobulin A and G levels were markedly elevated. The correlation analysis results showed that hemoglobin, albumin, C3, and complement 4(C4) had higher correlation indices compared with other clinical indicators. Among these, C3 exhibited a certain negative correlation with disease activity. The Logistic regression model based on 12 significantly different indicators (P < 0.05) achieved an accuracy of 91.4%, sensitivity of 94.4%, specificity of 81.0%, and the area under curve (AUC) of the receiver operating characteristic (ROC) was 0.944. CONCLUSION This study comprehensively evaluated a range of clinical indicators related to SLE disease activity, providing a thorough understanding of both laboratory and clinical markers. The Logistic regression model, which was primarily constructed using laboratory test indicators, such as inflammatory markers, immune response parameters, and organ involvement metrics, demonstrated a high degree of accuracy in assessing the disease activity in SLE patients. Consequently, this model might provide a new basis for the diagnosis and treatment of SLE patients, offering significant clinical diagnostic value.
Humans ; Lupus Erythematosus, Systemic/diagnosis* ; Retrospective Studies ; Antibodies, Antinuclear/blood* ; Complement C3/metabolism* ; Complement C4/metabolism* ; Logistic Models ; Severity of Illness Index ; Leukocyte Count ; Female ; Male ; Serum Albumin/analysis*

Objective:To evaluate the significance of copy number variation (CNV) and metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) in the diagnosis of meningeal carcinomatosis (MC).Methods:Ten patients with MC diagnosed in the Department of Neurology of Peking Union Medical College Hospital from March 2022 to June 2022 were consecutively enrolled in this study. The patients were diagnosed according to the criteria of the Chinese expert consensus on the diagnosis of MC by the Chinese Society of Infectious Diseases and Cerebrospinal Fluid Cytology, and the diagnosis of MC was confirmed by CSF cytology. The control group included 10 patients who were diagnosed as autoimmune encephalitis or viral encephalitis. CSF mNGS and CNV analysis were performed simultaneously in all the patients.Results:Of the 10 patients with MC, 6 had lung adenocarcinoma, 4 had breast cancer. CSF mNGS and CNV analysis detected large CNV in 8 of 10 patients with MC, including 4 patients with breast cancer and 4 patients with lung cancer. The results of pathogenic microorganism analysis of CSF mNGS in all the patients were negative. Meanwhile, large CNV was not detected in the control group.Conclusions:CSF CNV can serve as a diagnostic marker for MC. The combination of mNGS and CNV analysis has demonstrated a high positive rate in the diagnosis of MC. The dual-omics analysis of pathogenic microorganisms and CNV has been proposed as a potential strategy to further expand the clinical utility of CSF mNGS in the realm of auxiliary diagnosis.