辨体-辨病-辨证诊疗模式在慢性病防治中的应用策略

依据中国防治慢性病中长期规划（2017-2025年），按照国医大师王琦教授倡导的"辨体-辨病-辨证诊疗模式"，提出慢性病"3+4+3"防治路向：面向三类人群（一般、高危、患病人群），朝向四种状态（无病、病前、病中、病后状态），指向三辨模式（辨体-辨病-辨证诊疗模式）。进而探讨其应用策略：对于一般人群无病状态——辨体养生，固本防病；对于高危人群病前状态——辨体干预，治本救萌；针对患病人群病中状态——"三辨"施治，标本兼顾；针对患病人群病后状态——辨体调理，固本防复。文中结合案例加以佐证，具有临床指导价值。     

中西医结合治疗帕金森病非运动症状的系统评价与Meta分析

[目的]系统评价中西医结合治疗帕金森病非运动症状的临床疗效与安全性。[方法]全面检索相关中英文数据库,搜集自建库至2018年7月所有中药联合西医基础治疗与西医基础治疗(和中药安慰剂)的临床随机对照试验,根据纳入标准、排除标准,选择符合标准的相关文献并提取资料,依据Cochrane Handbook对纳入的文献进行质量评价,并采用RevMan5.3软件进行Meta分析。[结果]最终纳入24篇RCT,共计1 836例患者,分别采用主要指标及次要指标进行评价。结果显示:NMSS量表[MD=-6.19,95%CI=(-7.68,-4.69),Chi2=0.83,DF=3,n=302];NMSQuest量表[MD=-2.17,95%CI=(-2.67,-1.68),n=601]UPDRS I量表,未进行Meta分析[Chi2=75.91,DF=10,n=882],UPDRS II量表[MD=-2.71,95%CI=(-3.34,-2.08),n=1164];PDQ-39量表[MD=-7.81,95%CI=(-9.97,-5.64),n=407]。[结论]中西医结合治疗帕金森病非运动症状有效,且优于单纯西医基础治疗。     

数据挖掘法探讨周珉教授治疗原发性肝癌用药规律及经验总结

[目的]数据挖掘法分析周珉教授治疗原发性肝癌的中医用药规律，探讨相关病机并进行经验总结。[方法]收集2016年2月—2018年5月周珉教授门诊期间治疗原发性肝癌的方剂，运用“中医传承辅助系统（V2.50）”进行数据挖掘，并结合周珉教授临床经验，进行原发性肝癌病机探讨及用药规律分析。[结果]共收集治疗原发性肝癌方剂176首，涉及中药235种，列出方剂中的高频药物及组合规律。[结论]总结原发性肝癌以“湿热痰毒、气阴两伤”为基础病机，“清热化湿、健脾养阴”治则贯穿原发性肝癌治疗始末，同时，根据疾病不同发展阶段及治疗措施，权衡“扶正”与“祛邪”的主次分配，斟酌应用“攻毒散结”“行气化瘀”等治法，以达到改善患者生活质量、延缓疾病进展的目的。     

Emergency department patient payer status after implementation of the Affordable Care Act: A nationwide analysis using NHAMCS data

ObjectiveTo evaluate changes in insurance status among emergency department (ED) patients presenting in the two years immediately before and after full implementation of the Affordable Care Act (ACA).MethodsWe evaluated National Hospital Ambulatory Medical Care Survey (NHAMCS) Emergency Department public use data for 2012–2015, categorizing patients as having any insurance (private; Medicare; Medicaid; workers' compensation) or no insurance. We compared the pre- and post-ACA frequency of insurance coverage—overall and within the older (≥65), working-age (18–64) and pediatric (<18) subpopulations—using unadjusted odds ratios with 95% confidence intervals. We also conducted a difference-in-differences analysis comparing the change in insurance coverage among working-age patients with that observed for older Medicare-eligible patients, while controlling for sex, race and underlying temporal trends.ResultsOverall, the proportion of ED patients with any insurance did not significantly change from 2012 to 2013 to 2014–2015 (74.2% vs 77.7%) but the proportion of working-age adult patients with at least one form of insurance increased significantly, from 66.0% to 71.8% (OR 1.31, CI: 1.13–1.52). The difference-in-differences analysis confirmed the change in insurance coverage among working-age adults was greater than that seen in the reference population of Medicare-eligible adults (AOR 1.70, CI: 1.29–2.23). The increase was almost entirely attributable to increased Medicaid coverage.ConclusionIn the first two years following full implementation of the ACA, there was a significant increase in the proportion of working-age adult ED patients who had at least one form of health insurance. The increase appeared primarily associated with expansion of Medicaid.     

An Introduction to the Residency Application Process

Emergency medicine (EM) is a swiftly developing yet still relatively young discipline. We are going to present in the Medical Student Forum section of the Journal of Emergency Medicine several article series covering the key topics that medical students interested in emergency medicine will find helpful. This article introduces the topics that will be tackled in the first compilation of articles dealing with the residency application process.     

经典名方中“术”的本草考证

中药经典名方的研发是促进中医药继承创新和提高临床服务水平的重要途径,经典名方中药材基原的确定对其研发尤为重要,是保证质量、药效及安全性的源头。"术"入药历史悠久,《神农本草经》中列为上品,为经典名方中常用中药。但南北朝以前"苍术""白术"均可作为"术"入药,未做明确区分,致使本草考证是含"苍术""白术"经典名方研发中的难题。结合历代本草,从植株形态、产地、性味、功效等方面梳理"术"的历史变迁,以期为"术"的本草考证以及经典名方的研发提供参考借鉴。     

辛味中药在治疗消渴证中的应用价值及中药五味理论现代研究的思考

辛味是中药五味学说中的重要性味之一,通常具有“发散”“行气”和“行血”的作用,且辛味中药在传统医学临床应用中占有较大比例。结合中药辛味的功效内涵及传统中医理论对消渴证的认识,阐述辛味中药与消渴证治疗之间的内在联系,总结辛味中药对“消渴三消”的治疗意义与价值。并在此基础上,对中药五味理论的现代研究趋势和发展方向进行思考,为同行研究提供参考。     

Composite interaction tree for simultaneous learning of optimal individualized treatment rules and subgroups

Treatment response heterogeneity has long been observed in patients affected by chronic diseases. Administering an individualized treatment rule (ITR) offers an opportunity to tailor treatment strategies according to patient-specific characteristics. Overly complex machine learning methods for estimating ITRs may produce treatment rules that have higher benefit but lack transparency and interpretability. In clinical practices, it is desirable to derive a simple and interpretable ITR while maintaining certain optimality that leads to improved benefit in subgroups of patients, if not on the overall sample. In this work, we propose a tree-based robust learning method to estimate optimal piecewise linear ITRs and identify subgroups of patients with a large benefit. We achieve these goals by simultaneously identifying qualitative and quantitative interactions through a tree model, referred to as the composite interaction tree (CITree). We show that it has improved performance compared to existing methods on both overall sample and subgroups via extensive simulation studies. Lastly, we fit CITree to Research Evaluating the Value of Augmenting Medication with Psychotherapy trial for treating patients with major depressive disorders, where we identified both qualitative and quantitative interactions and subgroups of patients with a large benefit.