基于医院信息系统的乳腺癌临床特征及中西医用药特征分析

目的 解析真实世界中乳腺恶性肿瘤患者的人群特征、诊断特征、中西医用药特征，为乳腺癌的临床防治提供参考。方法 采集2002年2月至2015年5月全国60家三级甲等医 院信息系统（Hospital Information System，HIS）中，出院诊断为“乳腺癌”的患者用药信息，采用SAS9.3统计软件，对人口学信息、诊断信息、医嘱用药信息等进行描述性分析。结果 39798例乳腺癌患者，平均年龄（50.93者，平均年龄）岁；多以门诊入院，入院病情以“一般”为主;合并疾病主要为高血压，骨肿瘤，联用西药以抑制肿瘤细胞增殖、治疗并发症、缓解放化疗不良反应为主；中医辨证以痰瘀互结证，气阴两虚证，肝气淤滞证，脾气亏虚证型最为常见，临床清热解毒剂、益气扶正剂，活血化瘀剂应用较多。结论 乳腺癌中西医结合治疗，联用药物广泛，临床治疗基本符合临床指南。     

探讨替米沙坦对冠心病合并糖尿病肾病患者疗效的影响

目的:探究替米沙坦对冠心病合并糖尿病肾病患者疗效的影响情况。方法:56例探究目标对象均为某院接收的冠心病合并糖尿病肾病患者,挑选时间2018年6月~2019年6月。将"计算机表法"作为分组的参考,分配为参照组(n=28例)执行依那普利治疗,探究组(n=28例)执行替米沙坦治疗。结果:探究组的LVEF、LVEDd、肌酐、24h尿蛋白4项指标与参照组相比,差异有统计学意义(P<0.05);收缩压、舒张压、空腹血糖、餐后2h血糖4项指标与参照组相比,差异没有统计学意义(P>0.05)。结论:冠心病合并糖尿病肾病患者选择替米沙坦治疗后,心室功能的重构以及肾脏预后结局均得到改善,且临床效果比依那普利好,值得借鉴。     

Hypertension is a risk factor for adverse outcomes in patients with coronavirus disease 2019: a cohort study

Abstract

Background

Comorbidities are commonly seen in patients with coronavirus disease 2019 (COVID-19), but the clinical implication is not yet well-delineated. We aim to characterize the prevalence and clinical implications of comorbidities in patients with COVID-19.     

硒蛋白P在直肠癌中的表达及临床意义

目的应用免疫组织化学染色的方法检测硒蛋白P在直肠癌组织中的表达,以探讨其与直肠癌发生的关系及临床意义。方法收集山西大医院2013年6月至2014年5月间行手术治疗并经病理证实的60例直肠癌组织、40例直肠腺瘤组织、40例正常直肠组织,应用SABC法检测上述组织中硒蛋白P的表达情况,结果依据阳性细胞百分率和染色强度进行评价,三组间样本率的比较采用无序行×列表?2检验(α=0.05),两组间样本率的比较采用独立样本?2检验(α=0.016 7),硒蛋白的表达与直肠癌临床病理参数的关系采用四格表?2检验(α=0.05)进行分析。结果硒蛋白P在正常直肠组织、直肠腺瘤组织、直肠癌组织中的表达阳性率分别为82.5%(33/40)、70.0%(28/40)、45.0%(27/60),组间差异有统计学意义(?2=15.680,P<0.001),癌组织与正常组织、腺瘤组织间差异显著(?2=14.063,P<0.001;?2=6.061,P=0.015);硒蛋白的表达与肿瘤大小、是否浸润浆膜有关(P<0.05),与性别、年龄、淋巴结有无转移、肿瘤细胞分化程度、TNM分期无关(P>0.05)。结论硒蛋白在直肠癌中低表达,对直肠癌的发生发展具有重要作用,有望为直肠癌的治疗提供新思路。     

Rethinking PICO in the Machine Learning Era: ML-PICO

Background  Machine learning (ML) has captured the attention of many clinicians who may not have formal training in this area but are otherwise increasingly exposed to ML literature that may be relevant to their clinical specialties. ML papers that follow an outcomes-based research format can be assessed using clinical research appraisal frameworks such as PICO (Population, Intervention, Comparison, Outcome). However, the PICO frameworks strain when applied to ML papers that create new ML models, which are akin to diagnostic tests. There is a need for a new framework to help assess such papers. Objective  We propose a new framework to help clinicians systematically read and evaluate medical ML papers whose aim is to create a new ML model: ML-PICO (Machine Learning, Population, Identification, Crosscheck, Outcomes). We describe how the ML-PICO framework can be applied toward appraising literature describing ML models for health care. Conclusion  The relevance of ML to practitioners of clinical medicine is steadily increasing with a growing body of literature. Therefore, it is increasingly important for clinicians to be familiar with how to assess and best utilize these tools. In this paper we have described a practical framework on how to read ML papers that create a new ML model (or diagnostic test): ML-PICO. We hope that this can be used by clinicians to better evaluate the quality and utility of ML papers.     

Deferoxamine promotes recovery of traumatic spinal cord injury by inhibiting ferroptosis

Ferroptosis is an iron-dependent novel cell death pathway. Deferoxamine, a ferroptosis inhibitor, has been reported to promote spinal cord injury repair. It has yet to be clarified whether ferroptosis inhibition represents the mechanism of action of Deferoxamine on spinal cord injury recovery. A rat model of Deferoxamine at thoracic 10 segment was established using a modified Allen's method. Ninety 8-week-old female Wistar rats were used. Rats in the Deferoxamine group were intraperitoneally injected with 100 mg/kg Deferoxamine 30 minutes before injury. Simultaneously, the Sham and Deferoxamine groups served as controls. Drug administration was conducted for 7 consecutive days. The results were as follows:(1) Electron microscopy revealed shrunken mitochondria in the spinal cord injury group.(2) The Basso, Beattie and Bresnahan locomotor rating score showed that recovery of the hindlimb was remarkably better in the Deferoxamine group than in the spinal cord injury group.(3) The iron concentration was lower in the Deferoxamine group than in the spinal cord injury group after injury.(4) Western blot assay revealed that, compared with the spinal cord injury group, GPX4, xCT, and glutathione expression was markedly increased in the Deferoxamine group.(5) Real-time polymerase chain reaction revealed that, compared with the Deferoxamine group, mRNA levels of ferroptosis-related genes Acyl-CoA synthetase family member 2(ACSF2) and iron-responsive element-binding protein 2(IREB2) were up-regulated in the Deferoxamine group.(6) Deferoxamine increased survival of neurons and inhibited gliosis. These findings confirm that Deferoxamine can repair spinal cord injury by inhibiting ferroptosis. Targeting ferroptosis is therefore a promising therapeutic approach for spinal cord injury.     

依维莫司联合全反式维甲酸逆转急性早幼粒细胞白血病细胞耐药的研究

目的探讨依维莫司联合全反式维甲酸(简称维甲酸)逆转急性早幼粒细胞白血病(APL)细胞株NB4-R1耐药的作用。方法应用CD11b染色流式细胞术及硝基四唑氮蓝(NBT)还原实验检测两药联合应用对细胞分化的影响, 流式细胞术检测细胞周期情况, Annexin V/PI双染色检测细胞凋亡情况, 蛋白质印迹法检测自噬相关蛋白微管结合蛋白轻链3(LC3)、Beclin 1及早幼粒白血病-维甲酸受体融合蛋白(PML-RARα)、磷酸化核糖体S6激酶(P-P70S6K)、磷酸化4E结合蛋白1(P-4E-BP1) 等表达水平。结果与维甲酸组比较, 联用组能诱导耐药细胞株NB4-R1细胞的分化, 并将细胞增殖阻止在G ₁期而对细胞凋亡无明显影响。100 nmol/L依维莫司组、1μmol/L维甲酸组、联用组、对照组NB4-R1细胞培养48 h后分化百分率分别为(2.29±0.57)%、(17.06±2.65)%、(54.47±4.91)%、(2.54±0.53)%; 处于G ₁期的细胞百分率分别为(35.20±11.97)%、(33.54±6.25)%、(53.70±8.73)%、(27.40±6.01)%; 四组细胞凋亡细胞百分率分别为(2.30±0.14)%、(2.25±0.21)%、(2.40±0.28)%、(1.95±0.07)%。与维甲酸组比较, 联用组mTOR信号通路下游的P70S6K、4E-BP1分子磷酸化水平下降, LC3-II和Beclin 1的表达上调, 且能部分降解融合蛋白PML-RARα。 结论依维莫司联合维甲酸能诱导NB4-R1细胞分化, 且能阻滞细胞周期而不致细胞凋亡, 其机制可能与依维莫司联合维甲酸抑制mTOR信号通路激活自噬作用从而降解PML-RARα蛋白有关。