柴胡加龙骨牡蛎汤加减通过p38 MAPK通路改善CKD小鼠PFC突触可塑性及抑郁行为研究

目的 探讨柴胡加龙骨牡蛎汤加减(CLMD)对慢性肾脏病(CKD)小鼠抑郁行为的作用及可能机制.方法 3月龄雄性C57BL/6小鼠60只,分为对照组、模型组、氟西汀组、CLMD低剂量组、CLMD中剂量组和CLMD高剂量组.除对照组外,其余5组小鼠先予0.2％腺嘌呤饮食喂养2周.中药干预组分别予2.36、4.725、9.4...     

重庆地区748例儿童重症社区获得性肺炎病原学特点及耐药性分析

目的 分析重庆地区748例儿童重症社区获得性肺炎(CAP)的病原学特点及耐药性.方法 回顾性分析重庆市中医院2017年1月至2019年12月收治的748例重症CAP患儿的临床资料,分析患儿感染致病菌的病原学特征.结果 细菌检出率从高到低为流感嗜血杆菌(29.1％)、金黄色葡萄球菌(15.9％)、肺炎链球菌(14.8％)...     

重庆市区23 896名孕妇妊娠期糖尿病发病现况及危险因素分析

目的  分析重庆市区2018-2021年孕妇妊娠期糖尿病(gestational diabetes mellitus, GDM)的发病现况及其相关危险因素,为GDM的防控提供依据。方法  收集2018年1月-2021年6月在重庆医科大学附属妇女儿童医院进行产前检查的孕妇临床资料,并采用logistic回归分析模型分析不同危险因素对GDM的影响。结果  本研究共纳入来自重庆市区23 896名孕妇为研究对象,确诊为GDM的患者有6 269例,占26.2%。2018-2021年GDM的发病率分别为27.3%、25.0%、26.4%和26.4%。多因素logistic回归分析模型分析结果表明,在调整相关变量之后,年龄(OR=1.47, 95% CI: 1.41~1.54, P < 0.001)、BMI (OR=1.74, 95% CI: 1.65~1.83, P < 0.001)和内分泌疾病史(OR=9.32, 95% CI: 8.68~10.01, P < 0.001)是导致GDM患病风险增加的危险因素。结论  本研究发现重庆市区GDM的发病率较高,且高龄孕妇、孕前超重或肥胖和内分泌疾病史是GDM的高危因素。重庆市区应加强系统性的产科护理,关注孕期这些危险因素的变化,以减少GDM的发生。     

三七生肌膏促进激光治疗雀斑术后创面愈合临床观察

目的 观察三七生肌膏促进激光治疗雀斑术后创面愈合的临床疗效.方法 将96例在重庆市中医院美容科使用倍频Q开关Nd：YAG激光（532 nm）治疗雀斑的患者,随机平均分为3组,治疗组术后以三七生肌膏外涂,对照组术后喷洒壳聚糖长效抗菌敷料,空白组术后不采用任何辅助治疗措施.观察周期为15d.观察3组患者的术后创面疼痛消失时间以及创面愈合情况,随访痂皮脱落后色素沉着情况.结果 应用三七生肌膏治疗组的创面疼痛消失时间、愈合时间及色素沉着发生率较对照及空白组的差异均有统计学意义（P＜0.05）.结论 三七生肌膏能减轻激光治疗创面疼痛,促进创面愈合,并减少色素沉着.     

复方芦荟乳剂治疗老年患者药物性静脉炎临床观察术

目的观察自制复方芦荟乳剂治疗老年患者药物性静脉炎的临床疗效。方法将90例因输入刺激性药物致静脉炎的患者随机均分为观察组和对照组各45例，对照组使用50％硫酸镁湿敷，观察组使用自制复方芦荟乳剂涂擦，观察5d后局部疼痛改善和局部皮肤变化情况。结果观察组有效率为100％，局部疼痛得到很明显改善，与对照组比较存在显著差异（P＜O．01）。结论复方芦荟乳剂能有效治疗老年患者的药物性静脉炎，操作简单，疗效好。     

普秃案

A male, 62 years old, suffering from alopecia universalis, was treated with acupuncture. The treating principle was promoting qi and blood circulation. The selected acupoints included Băihuì (百会GV20), Tàiyáng (太阳EX-HN5), Fēngmén (风门BL12), Xīnshū(心俞BL15), Gānshū(肝俞BL18), Shènshū (肾俞BL23), etc. After treated for 3 months, the hair was grown normally and the hair on the scalp got black obviously. In the follow-up for 2 months, the hair on the body and scalp grew in good condition.     

Analysis of 24 Y chromosomal STR haplotypes in a Chinese Han population sample from Henan Province,Central China

We analyzed haplotypes for 24 Y chromosomal STRs (Y-STRs), including 17 Yfiler loci (DYS19, DYS385a/b, DYS389I/II, DYS390, DYS391, DYS392, DYS393, DYS437, DY438, DYS439, DYS448, DYS456, DYS458, DYS635 and Y-GATA-H4) and 7 additional STRs (DYS388, DYS444, DYS447, DYS449, DYS522 and DYS527a/b) in 1100 unrelated Chinese Han individuals from Henan Province using AGCU Y24 STR kit systems. The calculated average gene diversity (GD) values ranged from 0.4105 to 0.9647 for the DYS388 and DYS385a/b loci, respectively. The discriminatory capacity (DC) was 72.91% with 802 observed haplotypes using 17 Yfiler loci, by the addition of 7 Y-STRs to the Yfiler system, the DC was increased to 79.09% while showing 870 observed haplotypes. Among the additional 7 Y-STRs, DYS449, DYS527a/b, DYS444 and DYS522 were major contributors to enhancing discrimination. In the analysis of molecular variance, the Henan Han population clustered with Han origin populations and showed significant differences from other Non-Han populations. In the present study, we report 24 Y-STR population data in Henan Han population, and we emphasize the need for adding additional markers to the commonly used 17 Yfiler loci to achieve more improved discriminatory capacity in a population with low genetic diversity.     

A hybrid approach for risk stratification and predictive modelling of 30-days unplanned readmission of comorbid patients with diabetes

ObjectivesWhen comorbid patients with diabetes have 30-days Unplanned Readmission (URA), they attract more burdens to the healthcare system due to increased cost of treatment, insurance penalties to hospitals, and unavailable bed spaces for new patients. This paper, therefore, aims to develop a risk stratification and a predictive model for identifying patients at various risk severities of 30-days URA.MethodsPatients records of comorbid patients with diabetes treated with different medications were collected from different hospitals and analysed with Principal Component Analysis (PCA) and Multivariate Logistic Regression (MLR) to determine the probability of 30-days URA, which is classified into very low, low, moderate, high, and very high. The risk classes are later modelled using ANOVA feature selection to identify the optimal predictors and the best random forest (RF) hyperparameters for 30-days URA risk stratification. Synthetic Minority Oversampling Technique (SMOTE) was used to balance the risk classes while employing a10-fold cross-validation.ResultsAfter analysing 17,933 episodes of comorbid diabetes patients' treatment, 10.71% are identified to have 30-days URA with 61.95% of patients at moderate risk, 35.5% at low risk, 2.25% at very low risk, 0.37% at high risk, and 0.08% at very high risk. The predictive accuracy of RF is: - recall: 0.947 ± 0.035, precision: 0.951 ± 0.033, F1-score: 0.947 ± 0.035, AUC: 0.994 ± 0.007 and Average Precision (AP) of 0.99. The predictive accuracies of the risk classes measured with F1-score are: - very low: 0.985 ± 0.019, low risk: 0.871 ± 0.079, moderate: 0.881 ± 0.093, high: 0.999 ± 0.003, and very high: 1.000 ± 0.00.ConclusionThis study identified the risk severity of comorbid patients with diabetes treated with different medications, making it easier to identify those that will be prioritized on hospitalization to minimize 30-days URA. By relying on the technique developed, vulnerable patients to 30-days URA can be given better post-discharge monitoring to build critical self-management skills that will minimize the cost of diabetes care and improve the quality of life.