Targeting to improve clinical thinking and practice skill of interns, modified Team-based learning (TBL) based on seeing real patient was performed for interns from eight-year clinical medicine program. Teachers prepared the corresponding case material before the teaching and made teaching aids. And interns were mobilized and guided to preview and self-study in teams. During modi-fied TBL, in-class application of seeing real patient was performed to assess the effect of self-study in teams, besides individual test and team test deriving from traditional TBL. All teams were assigned one task of seeing real patient by drawing lots, and then finished the task, answered teachers' questions. And the students' performance was given comments and comprehensive scores by the judges. After the completion of teaching, the teaching effectiveness of the modified TBL was assessed from students' performance, their scores and their teaching evaluation. Practice shows that the modified TBL can not only attract students to engage in it, but also elevate their abilities of clinical thinking and practical skill. It can also cultivate their interpersonal ability.

Objective:To improve the awareness of cholesterol crystal embolism syndrome (CCE) inrheumatologists.Methods:The clinical characteristics of 40 Chinese CCE patients admitted to our department (one case) were summarize and in the literature (thirty-nine cases) were reviewed.Results:Among these 40 patients, 87.5%(35/40) were male and the mean age was (68±6) years. All patients suffered from athero-sclerosis and 87.5%(35/40) of them had precipitating factors such as endovascular intervention, vascular surgery, anticoagulant, or thrombolytic therapy. The clinical manifestations included renal insufficiency (90.0%, 36/40), blue toe syndrome (82.5%, 33/40), ulceration or gangrene (25.0%, 10/40), and livedo reticularis (15%, 6/40). Acute phase reactant was tested in 25 cases, of whom 84.0%(21/25) showed elevated C-reactive protein (CRP) and 56.0%(14/25) showed elevated erythrocyte sedimentation rate (ESR).Conclusion:Rheumatologists should be alert that CCE is one of the differential diagnosis of systemic vasculitis, especially for patients with severe atherosclerosis.

Objective:To improve the differential diagnosis of systemic sclerosis (SSc) with hypertension and renal insufficiency.Methods:The clinical characteristics, diagnosis and treatment of a SSc patient with hypertension and renal insufficiency were reported and discussed.Results:A middle-aged female patient with a history of SSc for 5 years, headache and gross hematuria for 10 days was admitted. Abrupt increase in blood pressure and creatinine, glomerular hematuria, proteinuria, low complement C3 and C4, positive antinuclear antibody (ANA), anti-dsDNA antibody and perinuclear antineutrophil cytoplasmic antibody (pANCA) were presented. Renal pathology showed lupus nephritis (LN) (type Ⅳ). After glucocorticoid pulse therapy, followed by cyclophosphamide, belimumab, and symptomatic treatment, the symptoms were relievedand lupus disease activity were decreased.Conclusion:For SSc patients with increased blood pressure and creatinine, the presence of other diseases should be considered in addition to scleroderma renal crisis. Renal biopsy and pathological examination should be performed to confirm the diagnosis and avoid misdiagnosis.

Objective To investigate clinical characteristics and renal uric acid excretion in early-onset gout patients.Methods Consecutive inpatients with primary gout were recruited between 2013 and 2017.The patients with gout onset younger than 30 were defined as early-onset group while the others were enrolled as control group.Clinical characteristics and uric acid (UA) indicators were compared between two groups.Results Among 202 recruited patients,the early-onset group included 36 patients (17.8％).Compared with control group,the early-onset group presented more patients with obesity [13 patients (36.1％) vs.22 patients (13.3％),P＜0.05],significantly higher serum UA level [(634± 124)μmol/L vs.(527± 169).μmol/L] and glomerular load of UA[(7.2±2.8)mg· min-1 · 1.73m-2 vs.(4.4±2.2)mg· min-1 · 1.73m-2] and estimated glomerular filtration rate (GFR) [(83±21)ml· min-1 · 1.73m-2 vs.(67±21)ml· min-1 · 1.73m-2] (all P＜ 0.05),lower fractional excretion of UA [4.4％ (3.4％,6.1％) vs.7.2％ (5.2％,9.6％),P＜0.05],whereas 24h urinary UA excretion was comparable [(2 788±882)l,μmol/1.73m2 vs.(2 645±1 140)μmol/1.73m2,P=0.274].Subgroup analysis of patients without chronic kidney disease showed significantly lower fractional excretion of UA in the early-onset group [4.5％(3.3％,6.1％) vs.6.7％ (5.1％,8.7％),P＜0.05].Logistic regression analysis showed that obesity (OR=3.25) and fractional excretion of UA less than 7％ (OR=9.01,all P＜0.05) were risk factors of gout early onset.Conclusion The gout patients with early-onset younger than 30 present high serum and glomerular load of uric acid which might be due to obesity and relative under-excretion of renal uric acid.

Objective To investigate the characteristics of body composition (BC) in gout patients and its clinical significance. Methods Consecutive gout patients were recruited between August 2017 and December 2018. Demographic information, clinical characteristics and comorbidities were collected. BC was assessed by bioelectric impedance analysis including body fat percentage (BF% ), trunk and limb BF%, appendicular skeletal muscle index. Overfat was defined by BF%≥25% for male and≥35% for female. The association between BC and serum uric acid (sUA) was evaluated by multiple linear regression. Results A total of 362 gout patients were recruited with median age 38 (30, 52) years, 96.1% (348/362) were male. Mean sUA was(551±133)μmol/L. The mean BF% was (25.8±6.4)% with 53.6%(194/362) patients overfat. Male gout patients with overfat showed more affected joints [4(2, 6) vs. 2(2, 5)], higher sUA [(576 ± 126)μmol/L vs. (523 ± 134) μmol/L], higher prevalence of dyslipidemia [70.1%(131/187) vs. 54.0%(87/161)], metabolic syndrome [60.8%(118/187) vs. 28.0%(47/161)], fatty liver [58.2%(113/187) vs. 35.1%(59/161)] and hypertension [44.4%(83/187) vs. 25.5%(41/161)] than male patients with normal fat (all P<0.05). Their BF% , trunk BF% and limb BF% were positively correlated with the numbers of affected joints, sUA, metabolic syndrome, fatty liver, and hypertension, respectively (r=0.154-0.435, all P<0.05). Multivariable linear regression suggested that BF% (β=4.29, P=0.020) and trunk BF% (β=9.11, P=0.007), but not limb BF% , were positively correlated with sUA. Conclusion Overfat is very common in gout patients. The proportion of trunk fat in male patients is positively correlated with sUA. When assessing obesity in gout patients clinically, body composition analysis should be performed simultaneously.

Objective: To investigate the characteristics of body composition (BC) in gout patients and its clinical significance. Methods: Consecutive gout patients were recruited between August 2017 and December 2018. Demographic information, clinical characteristics and comorbidities were collected. BC was assessed by bioelectric impedance analysis including body fat percentage (BF%), trunk and limb BF%, appendicular skeletal muscle index. Overfat was defined by BF% ≥25% for male and ≥35% for female. The association between BC and serum uric acid (sUA) was evaluated by multiple linear regression. Results: A total of 362 gout patients were recruited with median age 38 (30, 52) years, 96.1% (348/362) were male. Mean sUA was (551±133) μmol/L. The mean BF% was (25.8±6.4)% with 53.6%(194/362) patients overfat. Male gout patients with overfat showed more affected joints [4(2, 6) vs. 2(2, 5)], higher sUA [(576±126)μmol/L vs. (523±134) μmol/L], higher prevalence of dyslipidemia [70.1%(131/187) vs. 54.0%(87/161)], metabolic syndrome [60.8%(118/187) vs. 28.0%(47/161)], fatty liver [58.2%(113/187) vs. 35.1%(59/161)] and hypertension [44.4%(83/187) vs. 25.5%(41/161)] than male patients with normal fat (all P<0.05). Their BF%, trunk BF% and limb BF% were positively correlated with the numbers of affected joints, sUA, metabolic syndrome, fatty liver, and hypertension, respectively (r=0.154-0.435, all P<0.05). Multivariable linear regression suggested that BF% (β=4.29, P=0.020) and trunk BF% (β=9.11, P=0.007), but not limb BF%, were positively correlated with sUA. Conclusion Overfat is very common in gout patients. The proportion of trunk fat in male patients is positively correlated with sUA. When assessing obesity in gout patients clinically, body composition analysis should be performed simultaneously.