ObjectiveTo compare the clinical disease activity index (CDAI) and simplified disease activity index(SDAI) as well as disease activity score 28(DAS28) by assessing the activity of rheumatoid arthritis (RA) and to explore which one is better.MethodsTwo hundred RA patients were enrolled.Swelling joint counts (SJC),tenderness joint counts(TJC ),patient's and doctor's global assessment of disease activity based on visual analogue scale(PGA,PhGA),health assessment questionnaire(HAQ) were recorded and the erythrocyte sedimentation rate(ESR),C reaction protein (CRP) of each patient were tested.DAS28,CDAI,SDAI of all patients were calculated for all patients.Statistical analysiswas carried out by Pearson correlation for the association between DAS28 and the above parameters,as well as CDAI,and SDAI.We created 4 patient groups based on DAS28,CDAI and SDAI ranks and used kappa statistics to assess the level of overall agreement of different disease activity categories between any of the two indices above for individual patients.We assessed the discriminating validity using receiver operating characteristic(ROC) curve analysis to compare the ability of the CDAI and SDAI to discriminate betwecn patients with remission, low and moderate,high disease activity.ResultsOf all the patients,CDAI(17.2±11.1) and SDA[(19.1±11.6) were correlated with DAS28 (4.3±1.5),the correlation coefficients were 0.876,0.861 (P＜0.05) respectively.CDAI and SDAI were correlated with HAQ (0.6±0.7),as well as DAS28.The correlation coefficients were 0.522,0.523,and 0.482(P＜0.05).The Kappa of CDAI and SDAI was 0.777.The Kappa of CDAI and DAS28,SDAI and DAS28 were 0.482,0.394.The areas under ROC of CDAI and SDAI were 0.906,0.888 if DAS28 was used as the gold standard.ConclusionCDAI and SDAI as well as DAS28 can be used to assess the activity of RA and both are better correlated with HAQ than DAS28.Though there is no CRP in CDAI when compared with SDAI,CDAI has very goodoverall agreement with SDAI and the overall agreement of CDAI and DAS28 is better than SDAI and DAS28.In addition, CDAI is better in discriminating between patients with remission/low and moderate/high disease activity.So,CDAI is a simple,convenient,accurate,quick assessment tool and is suitable for daily application.

Objective:To analyze the clinical features of patients with cardic involvement in eosinophilic granulomatosis with polyangiitis (EGPA), and to enhance the understanding.Methods:We retrospectively reviewed the clinical data of 16 patients with EGPA with cardiac involvement in Bethune hospital of Shan-xi from Jan 2012 to Jun 2019. T test, rank sum test and χ2 test were used for statistical analysis. Results:16 patients with cardiac involvement. There were 11 males and 9 female. The age of 16 patients with cardiac involvement ranged from 14 to 82 years old, and the average age of onset was (58±14) years. Compared with patients without cardiac invo-lvement was (41±15) years, the difference between the two groups was statistically significant ( t=3.230 , P<0.01). The analysis suggested that age was related to whether or not cardiac involvement. Cardiac related clinical symptoms occurred in 4 patients (25%). One patient presented with cardiac involvement as the initial symptom. The other 12 patients presented abnormal electrocardiogram (ECG), cardiac ultrasound or cardiac magnetic resonance imaging (MRI), including 10 patients (62%) with abnormal ECG, 13 patients (81%) with abnormal cardiac ultrasound examination, and1patient with cardiac MRI suggesting endocarditis. Among 16 patients with EGPA cardiac involvement, 14 presented with pulmonary involvement, 10 cases with nasal involvement, 9 cases with perip-heral neurological involvement, 9 cases with skin involvement, 6 cases with gastrointestinal involvement, 2 cases with kidney damage. Eosinophils (EO) were increased in all 16 patients, with a median value of 2.46 (1.49, 3.94) ×10 9/L, and EO was associated with cardiac involvement. Analysis of perinuclear anti-neutrophil cytoplasmic antibo-dies (pANCA) positive rate showed that only 2 of the 16 patients were positive. There was statistically significant difference ( P=0.017) compared with the group without cardiac involvement (8 patients were positive). All 16 patients were treated with glucocorticoid, 12 patients received immunosuppressive therapy, and 10 patients were treated with cyclophosphamide. During the ollow-up, 1 case died of heart failure, 1 case died of cerebral hemorrhage, 3 cases were lost to follow-up, and the other 11 cases were all stable after discharge. Conclusion:EGPA patients have a high incidence of cardiac involvement, and all cardiac stru-ctures can be involved, and most cardic involvement happens in ANCA negative patients. Cardiac involvement is one of the factors with poor prognosis.

Schizophrenia(SZ)is a serious mental illness,and traditional diagnostic methods are prone to missed and misdiagnosis.Using machine learning(ML)algorithms can extract SZ relative features from functional MRI(fMRI)data,hence being helpful for diagnosing and predicting treatment response of SZ.The research progresses of ML based on fMRI for diagnosis and treatment of SZ were reviewed in this article.