PDCA循环法在自动乳腺全容积成像诊断乳腺疾病中的应用

目的探讨PDCA（Plan计划，Do执行，Check检查，Action行动）循环法在自动乳腺全容积成像（ABVS）诊断乳腺疾病中的应用。 方法收集中南大学湘雅三医院2018年1月至2019年12月期间行ABVS检查并经病理确诊或临床明确诊断的乳腺疾病患者2070例，根据PDCA循环法应用时间分为2组，PDCA循环法应用前（2018年1月至2018年12月）患者840例，PDCA循环法应用后（2019年1月至2019年12月）患者1230例。使用χ²检验分析比较PDCA循环法应用前后的诊断符合率、漏诊率、误诊率以及患者满意度的差异。 结果与PDCA循环法应用前比较，PDCA实施后ABVS诊断符合率提高（87.89% vs 82.74%），误诊率下降（11.47% vs 15.63%），漏诊率下降（14.39% vs 23.20%），患者满意度提升（92.59% vs 87.12%），差异均具有统计学意义（χ²=10.856、4.507、3.936、3.922，P=0.010、0.034、0.047、0.048）。 结论PDCA循环法能提升ABVS诊断乳腺疾病过程中的医疗质量。     

农村老年人老化期望现状及影响因素研究

目的 了解农村老年人的老化期望现状，分析其影响因素，为针对干预提供参考。 方法 采用一般资料调查表、UCLA孤独感量表简化版、老化期望量表、简版自我感知老化量表对199名农村老年人进行问卷调查。 结果 老化期望总分为32.72±9.18，孤独感得分为15.11±3.82，自我感知老化得分为52.75±2.76；多元线性回归分析显示，性别、婚姻状况、患慢性病种数、独居、孤独感、自我感知老化及经济来源是农村老年人老化期望的影响因素（调整R2=0.612，均P＜0.05）。 结论 农村老年人的老化期望水平较低，女性、孤独、无配偶、患慢性病较多、老化态度消极及低收入人群是关注的重点。     

Risk factors related to the severity of COVID-19 in Wuhan

Objective: To evaluate the characteristics at admission of patients with moderate COVID-19 in Wuhan and to explore risk factors associated with the severe prognosis of the disease for prognostic prediction.Methods: In this retrospective study, moderate and severe disease was defined according to the report of the WHO-China Joint Mission on COVID-19. Clinical characteristics and laboratory findings of 172 patients with laboratory-confirmed moderate COVID-19 were collected when they were admitted to the Cancer Center of Wuhan Union Hospital between February 13, 2020 and February 25, 2020. This cohort was followed to March 14, 2020. The outcomes, being discharged as mild cases or developing into severe cases, were categorized into two groups. The data were compared and analyzed with univariate logistic regression to identify the features that differed significantly between the two groups. Based on machine learning algorithms, a further feature selection procedure was performed to identify the features that can contribute the most to the prediction of disease severity.Results: Of the 172 patients, 112 were discharged as mild cases, and 60 developed into severe cases. Four clinical characteristics and 18 laboratory findings showed significant differences between the two groups in the statistical test (P<0.01) and univariate logistic regression analysis (P<0.01). In the further feature selection procedure, six features were chosen to obtain the best performance in discriminating the two groups with a linear kernel support vector machine. The mean accuracy was 91.38%, with a sensitivity of 0.90 and a specificity of 0.94. The six features included interleukin-6, high-sensitivity cardiac troponin I, procalcitonin, high-sensitivity C-reactive protein, chest distress and calcium level.Conclusions: With the data collected at admission, the combination of one clinical characteristic and five laboratory findings contributed the most to the discrimination between the two groups with a linear kernel support vector machine classifier. These factors may be risk factors that can be used to perform a prognostic prediction regarding the severity of the disease for patients with moderate COVID-19 in the early stage of the disease.     

浅谈新型冠状病毒肺炎合并基础病的中医药防治策略＊

2019年12月始，新型冠状病毒肺炎（Corona Virus Disease 2019，COVID-19）以湖北武汉为中心向全国各地蔓延。目前数据显示，COVID-19合并糖尿病、高血压、肿瘤等基础病的患者病情较为严峻，病死率相对较高。该类患者的临床治疗策略有待进一步深入研究。在此次疫情防治过程中，中西医结合治疗手段于COVID-19的防治及患者基础疾病的兼顾治疗方面展现出了一定的特色及优势。本文结合中医“未病先防，既病防变，瘥后防复”思想，拟从COVID-19合并糖尿病、高血压、肿瘤三个方面，探讨COVID-19爆发形势下合并基础病患者的中医药防治策略。     

基于CT图像的评分模型预测食管鳞癌喉返神经旁淋巴结转移风险

目的:基于原发肿瘤及淋巴结CT特征建立评分模型预测食管鳞癌患者喉返神经旁淋巴结(RLN-LN)转移风险。方法:回顾性收集2014年1月至2019年12月于北京大学肿瘤医院行食管癌根治术并清扫RLN-LN的92例食管鳞癌患者。根据术后淋巴结病理结果分为RLN-LN转移组(n=37)和非转移组(n=55)。评估术前CT图像,记录食管癌患者年龄、性别、分化程度、肿瘤位置、肿瘤大小(肿瘤长度、肿瘤厚度、厚度/长度)、RLN-LN大小(淋巴结短径、长径、短径/多平面重建(MPR)最长径]。采用多元logistic回归筛选独立预测因子并建立评分模型,采用ROC曲线评估评分模型及独立预测因子诊断RLN-LN转移的效能,采用Z检验比较曲线下面积(AUC)的差异。应用Hosmer-Lemeshow检验和校准曲线评估模型拟合度。结果:肿瘤位置、肿瘤长度、RLN-LN短径、短径/MPR最长径是RLN-LN转移的独立预测因子,其诊断RLN-LN转移的AUC分别为0.586、0.705、0.831、0.777。基于以上4个CT特征建立评分模型,评分模型诊断RLN-LN转移的AUC为0.903(95%CI 0.846~0.959),优于各单一CT特征(Z=5.812,P<0.001;Z=2.161,P=0.030;Z=2.929,P=0.003;Z=4.052,P<0.001)。拟合优度Hosmer-Lemeshow检验结果显示P=0.555,校准曲线提示评分模型预测RLN-LN转移风险与实际转移风险之间具有良好的一致性。结论:基于CT图像的评分模型有助于食管鳞癌RLN-LN转移状态危险分层。     

精神分裂症患者攻击/暴力行为的MRI研究进展

精神分裂症是一种重性精神疾病，攻击行为是重性精神疾病的特征之一。精神分裂症发 生攻击 / 暴力行为的风险高于一般人群，社会危害性大。理解、掌握精神分裂症攻击 / 暴力行为的神经 生物学机制对其控制和预防至关重要。目前关于精神分裂症患者攻击/暴力行为的MRI研究虽有一定的 进展但成果较为有限，研究结果也不尽相同。现对精神分裂症患者攻击/暴力行为的MRI研究进行综述。