红外光谱数据融合对栽培滇重楼产地鉴别*

目的 多样的环境因素使得不同产地栽培滇重楼的化学成分也丰富多样，不同居群栽培滇重楼的甾体皂苷类成分具有很大的差异，多源数据融合分析能更全面的表征药材化学信息，建立一个高效而准确的产地鉴别模型，为其资源合理开发利用提供依据。方法 以来自云南和四川的8个产地（保山、楚雄、大理、红河、丽江、成都、文山、玉溪）共366份栽培滇重楼根茎为实验材料，采集其傅里叶变换近红外光谱（FT-NIR）和衰减全反射-傅里叶变换中红外光谱（ATR-FTMIR）数据。采用Kennard-Stone算法将不同产地的样品分为2/3的训练集和1/3的预测集，基于4种特征变量提取方法（CARS、VIP、SPA、SO-Covsel）结合2种数据融合策略（低级数据融合和中级数据融合），建立偏最小二乘产地判别分析模型。根据模型参数交叉验证均方根误差（RMSECV）和预测均方根误差（RMSEP）评估模型的稳定性，模型训练集和预测集准确率（ACC）评估模型分类性能。结果 近红外光谱和中红外光谱均能反应不同产地栽培滇重楼的化学成分差异，在中级数据融合中，基于VIP和SPA提取的特征变量建立的模型正确率均大于94%。相较于中级数据融合，低级数据融合模型得到了最为满意的结果，其预测集分类正确率达到100%。结论 根据近红外和中红外数据建立的低级数据融合PLS-DA模型，能够用于栽培滇重楼的产地鉴别分析。     

Understanding congenital vertical talus

Congenital vertical talus (CVT) is a rare foot deformity that presents with a rigid flat foot at birth. CVT can present as an isolated abnormality in the newborn, however in at least 50% of cases in association with other conditions. Full neuro-axial imaging is essential to detect any associated neurologic problems. Radiographs of the foot, including forced plantar and dorsiflexion laterals, are diagnostic. Gold standard modern treatment uses the Dobbs method of serial manipulation and casting with minimally-invasive stabilization of the talonavicular joint and Achilles tendon tenotomy.     

Prior surgical fixation of proximal humerus fractures is associated with increased complications following subsequent reverse shoulder arthroplasty

BackgroundThe objective of this study was to compare complication rates between patients undergoing reverse shoulder arthroplasty (RSA) after a prior open reduction and internal fixation (ORIF) for proximal humerus fracture (PHF) to those undergoing RSA as a primary treatment for PHFs, glenohumeral osteoarthritis, or rotator cuff tear arthropathy (CTA).MethodsPatients who underwent RSA between 2015 and 2020 were identified in the Mariner database. Patients were separated into 3 mutually exclusive groups: (1) RSA for osteoarthritis, rotator cuff tear, or CTA (Control-RSA); (2) RSA as a primary treatment for PHF (PHF-RSA); and (3) RSA for patients with prior ORIF of PHFs (ORIF-RSA). Ninety-day medical and 2-year postoperative surgical complications were identified. In addition, patients in the PHF-RSA group were subdivided into those undergoing RSA for PHF within 3 months of the fracture (acute) vs. those treated greater than 3 months from diagnosis (delayed). Multivariate regression was performed to control for differences in comorbidities and demographics.ResultsA total of 30,824 patients underwent primary RSA for arthritis or CTA, 5389 patients underwent RSA as a primary treatment for a PHF, and 361 patients underwent RSA after ORIF of a PHF. ORIF before RSA was associated with an increased risk of overall revision (odds ratio [OR] 2.45, P = .002), infection (OR 2.40, P < .001), instability (OR 2.43, P < .001), fracture (OR 3.24, P = .001), minor medical complications (OR 1.59, P = .008), and readmission (OR 2.55, P = .001) compared with the Control-RSA cohort. RSA as a primary treatment for PHF was associated with an increased risk of 2-year revision (OR 1.60, P < .001), infection (OR 1.51, P < .001), instability (OR 2.84, P < .001), and fracture (OR 2.54, P < .001) in addition to major medical complications (OR 2.02, P < .001), minor medical complications (OR 1.92, P < .001), 90-day emergency department visits (OR 1.26, P < .001) and 90-day readmission (OR 2.03, P < .001) compared with the Control-RSA cohort. The ORIF-RSA group had an increased risk of periprosthetic infection (OR 1.94, P = .002) when compared with the PHF-RSA cohort. There were no differences in medical or surgical complications in the RSA-PHF cohort between patients treated in an acute or delayed fashion.ConclusionRSA following ORIF of a PHF is associated with increased complications compared with patients undergoing RSA for nonfracture indications. Prior ORIF of a PHF is also an independent risk factor for postoperative infection after RSA compared with patients who undergo RSA as a primary operation for fracture. The timing of RSA as a primary operation for PHF does not appear to impact the rates of postoperative medical and surgical complications.     

中国中医药资源配置水平及影响因素探讨＊

目的 分析2013-2019年中国31省市中医药资源配置水平及区域差异，探讨影响资源配置水平的主要因素，为优化中国中医药资源配置提供依据。方法 选取具有代表性的每万人口中医药机构数、每万人口中医药技术人员以及每万人口中医药床位数作为中医药资源配置水平的指标，利用统计年鉴2013-2019年的面板数据，综合运用熵权法、可分解的泰尔指数以及面板时间固定效应模型，分析各省份中医药资源配置水平及区域公平性差异和影响因素。结果 中国中医药资源配置水平均值为0.165，整体呈现递增趋势，不同省份间配置水平有差异；按人口配置的总体泰尔指数优于按面积配置的指数；公平性差异主要来自于四大经济区区域内差异；经济发展水平、城镇化水平和财政自主度是影响中医药资源配置的主要因素（P<0.05）。结论 中医药资源配置整体水平呈增长趋势，资源配置的公平性有待于进一步提高，应重点关注区域内的不公平性。经济发展水平、城镇化水平和财政自主度是影响中医药资源配置水平的主要因素，建议各地区根据当地不同现状精准施策。     

中医移动医疗App信息服务现状研究

以“七麦数据”网站收录的中医移动医疗App作为研究对象，采用网络调查法和文献分析法，根据“七麦数据”对移动医疗App的分类，结合中医移动医疗App的信息服务内容和特点，将筛选出的中医移动医疗App划分为医疗健康类、中医养生类、知识传播类、全面综合类，并根据“七麦数据”网站中对各类中医移动医疗App的打分及累计下载量筛选出最具代表性的12款中医移动医疗App，从全面性、人性化、安全性、实用性4个一级指标和40个二级指标对其信息服务现状进行评价，指出当前中医移动医疗App信息服务存在的问题并提出建议。     

TOPSIS法和秩和比法模糊联合在基本公共卫生服务质量综合评价中的应用研究

背景国家基本公共卫生服务项目的开展是我国新医改的重要举措，自2009年国家基本公共卫生服务项目开展后，其服务经费与服务项目不断扩增，由于涉及指标较多，覆盖面较广，探寻科学、客观、全面的基本公共卫生服务综合评价方法十分必要。目的探索适宜的基本公共卫生服务质量综合评价方法，通过质量评价为调整相关政策和提高服务质量提供依据。方法2019年2—4月，采用多阶段立意抽样方式从Z省南部、中部和北部地区共选取24家社区卫生服务中心（乡镇卫生院）作为评价对象，记为机构A~X。采用逼近理想解排序法（TOPSIS法）、秩和比法及二者模糊联合的方法对24家社区卫生服务中心（乡镇卫生院）2018年基层医疗卫生机构基本公共卫生服务质量进行综合评价（参考2018年国家基本公共卫生服务项目选取12项评价指标）。结果在TOPSIS法评价中，Ci值排名前三名的为A（0.917 4）、C（0.875 9）和G（0.787 9），Ci值排名后三名的为I（0.414 2）、W（0.413 7）和N（0.407 7）。在秩和比法评价中，RSR值排名前三名的为A（0.890 6）、G（0.765 6）和C（0.711 8），RSR值排名后三名的为V（0.381 9）、W（0.362 8）和K（0.357 6）。根据模糊集理论，将W1Ci+W2RSR值进行排序，依据"择多原则"，排名前三名的分别为A、C和G，排名后三名的分别为I、K和W，这与TOPSIS法和秩和比法的评价结果基本一致。结论TOPSIS法和秩和比法模糊联合得到的评价结果及影响因素与其他研究结果相一致，并且两者联用能克服单一使用TOPSIS法或秩和比法的局限性，适宜在基本公共卫生服务质量评价中推广应用。