Objective: To explore the best method to treat post-stroke depression. Methods:60 Cases of the patients with post-stroke depression were selected and divided randomly into the two groups, 30 cases in each group. The treatment group was treated by scalp acupuncture plus body acupuncture, and the control group was treated by oral administration of Fluoxetine. The therapeutic effects were assessed after 30 d of the treatments. Results: The total effective rate was 90.0% in the treatment group, with average effective time of 5 d, and was 80.0% in the control group, with average effective time of 15 d. The comparison of the total effective rates between the two groups was not significant statistically (P＞0.05). But the comparison of the average effective time was significant statistically (P＜0.05). Conclusion: The therapeutic effect is positive in the treatment of post-stroke depression by scalp acupuncture plus body acupuncture, similar to the therapeutic effect of Fluoxetine, but faster in the effective time.

Objective To investigate the risk factors for postmenopausal osteoporosis in Shanghai.Methods Five hundred postmenopausal community-dwelling women aged 45-80 years were recruited. The case-control study was performed from June 2008 to September 2008.A total number of 250 women with postmenopausal osteoporosis identified with their bone mineral density (BMD) were selected as case group, and 250 non-osteoporosis women were selected as control group. BMD was measured by dual energy X-ray absorption (DEXA). Results Univariate logistic regression analysis showed that age, eduction level, occupation, years since menopause, BMI, use of calcium,historyofnon-violencefracture,fall,diabetesmellitus,chronicgastricdiseases, gastrointestinal resection and diarrhea were related to osteoporosis.Multiple logistic regression showed that age, years since menopause and nutritional status were the risk factors for osteoporosis. ConclusionsThe occurrence of osteoporosis is related with many factors in postmenopausal women in Shanghai, and women with early menopause, low BMI and older age should pay more attention to the prevention and treatment of osteoporosis.

Primary sclerosing cholangitis （PSC） is a cholestatic disease characterized by chronic progressive bile duct inflammation and has a low incidence rate and poor prognosis in China. There is still no drug therapy that can change the course of PSC， and liver transplantation is the only effective treatment for PSC， with a 5-year survival rate of 85% after transplantation. Drug therapy for PSC is facing great challenges based on the current status of PSC. At present， drugs for the treatment of PSC are in the stage of clinical trials and have shown certain application prospect， among which ursodeoxycholic acid is the most widely studied and commonly used drug. In addition， there are many emerging drugs in the pipeline. This article summarizes the latest advances in drug therapy for PSC.

More and more studies have found that red blood cell distribution width (RDW) can be used for acute pancreatitis (AP) classification, dynamic monitoring and evaluation of disease severity, mortality, prognosis and complication. Some inflammatory markers, such as procalcitonin (PCT), C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR) and pancreatitis scoring system are also associated with severity of AP, and can further improve the evaluation of AP severity when combined with RDW. This article reviewed the RDW and classification of AP, the dynamic changes of RDW and AP, RDW combined with inflammatory indices for prediction of severity of AP, and RDW combined with pancreatitis scoring system for prediction of severity of AP, so as to improve the understanding of predictive value of RDW in assessing the severity of AP.

Objective To investigate the correlation between atherogenic index of plasma (AIP) and the severity of hypertriglyceridemic acute pancreatitis (HTG-AP) and the value of AIP combined with Bedside Index for Severity in Acute Pancreatitis (BISAP) score in the early prediction of severe HTG-AP (sHTG-AP). Methods A retrospective analysis was performed for the clinical data of 170 patients with HTG-AP who were hospitalized in The General Hospital of Central Theater Command from January 2017 to December 2021, and according to related guidelines, they were divided into the sHTG-AP group with 28 patients and non-sHTG-AP group with 142 patients. Peripheral blood samples were collected from all patients within 24 hours after admission, and the two groups were compared in terms of sex, age, laboratory test results, AIP, BISAP score, and modified CT severity index (MCTSI) score. The chi-square test or the Fisher's exact test was used for comparison of categorical data between groups; the Mann-Whitney U test was used for comparison of continuous data between groups. The Spearman rank correlation test was used to investigate the correlation between each factor and the severity of HTG-AP, and the binary logistic regression analysis were used to investigate the independent risk factors for sHTG-AP. The receiver operating characteristic (ROC) curve was plotted to assess the predictive efficacy of each indicator. Results There were significant differences between the two groups in the medical history of diabetes, lymphocyte count, albumin, Ca 2+ , triglyceride, high-density lipoprotein cholesterol, AIP, BISAP score, MCTSI score, length of hospital stay, and hospital costs (all P < 0.05). The sHTG-AP group had a longer length of hospital stay, higher hospital costs, and a higher AIP value. AIP (odds ratio [ OR ]=1.244, 95% confidence interval [ CI ]: 1.062-1.458, P =0.007), BISAP score ( OR =5.525, 95% CI : 1.646-18.543, P =0.006), and MCTSI score ( OR =2.029, 95% CI : 1.245-3.305, P =0.004) were risk factors for sHTG-AP. AIP, BISAP score, and MCTSI score were positively correlated with the severity of HTG-AP ( r =0.291, 0.631, and 0.649, all P < 0.001), and AIP was positively correlated with BISAP score and MCTSI score ( r =0.190 and 0.215, both P < 0.05). AIP had an optimal cut-off value of 1.095 in predicting sHTG-AP, and AIP, BISAP score, and AIP combined with BISAP score had an area under the ROC curve of 0.759, 0.887, 0.925, respectively, a sensitivity of 0.821, 0.857, and 0.786, respectively, and a specificity of 0.627, 0.817, and 0.937, respectively (all P < 0.001). Conclusion AIP is a risk factor for sHTG-AP and is correlated with disease severity, and AIP combined with BISAP score has a relatively high value in the early prediction of sHTG-AP.