Sex offender registries: exploring the attitudes and knowledge of political decision-makers

Sex offender registries (SORs) were established due to policies and practices intended to protect the public from individuals who commit sexually violent acts, and yet the empirical literature does not show that public SORs reduce or prevent sexual crimes. Given that politicians prominently influence SOR policies, the current study explores the views of SORs by 26 political decision-makers from Canada and the United States. Participants completed a survey on their opinions regarding SORs and their knowledge of SOR eligibility. Attitudes and political perspectives were assessed to examine their association with SOR opinions. Almost two thirds of those surveyed believed SORs should be publicly available, and one third believed SORs helped to protect the public. These beliefs were associated with those with conservative-leaning political views. These findings help us to explore the perspectives of political decision-makers and gain insight into attitudinal factors that may play a role in influencing opinions regarding SORs.     

Solution‐driven approaches to generic substitution challenges – a survey among international experts

The main objective of this study was to explore the perception and understanding of economic, legal, and social barriers that may restrain generic uptake among recognized international experts in health care, and to identify and verify recommendations on how to streamline generic substitution (GS) at no expense of therapeutic safety. A questionnaire survey was devised, and experts with world‐renowned expertise in the field of generic medicinal products were selected. Almost 3/4 of respondents claimed that all drugs that satisfy bioequivalence criteria represent similar efficacy and adverse effects, and 1/4 of respondents believed that some differences could be reported. The majority of experts supported (i) the right of patients to refuse GS, (ii) the right of physicians to veto GS, and (iii) the introduction of a statutory obligation to provide patients with access to the cheapest generics available on the market. The main obstacles to more general uptake of generics were as follows: (i) perception of generics as lower quality products, (ii) absence of a transparent policy governing GS, and (iii) disincentives to pharmacists and physicians. Among the most popular recommendations were as follows: (i) introduction of various measures to aid physicians in generic prescribing, (ii) setting clear guidelines specifying when GS is not advisable, (iii) supporting competition on the generic market. The views of experts and the resulting recommendations were strongly affected by their opinion on the bioequivalence of generics. From this analysis, we have selected several principal recommendations which could help shape successful healthcare policies regarding GS.     

基于条件随机域的禤国维名老中医医案挖掘分析

目的:基于条件随机域模型对禤国维名老中医临床医案进行挖掘分析。方法:基于条件随机域设计一种新的临床医案文本挖掘信息模型,利用该模型对国医大师禤国维医案进行临床术语信息的自动识别提取,并使用关联规则算法进行数据挖掘分析。结果:基于条件随机域构建的文本信息挖掘模型对不同临床术语类型,不同的病种识别效果良好,其中在不同术语类型的识别中对"中医诊断术语"的F-测度值最高,达到89.87%,在不同病种的识别中对"湿疹"的F-测度值最高,达到83.77%。对其中禤国维名老中医治疗荨麻疹的经验进行挖掘,发现在治法上多采取益气固表、祛风止痒、除湿解毒;常用以治疗的二联药对有黄芪-白术、黄芪-防风、白术-防风等,其中白术-防风的置信度(1.00)和支持度(0.83)最高;常用的三联药物有黄芪-紫苏叶-白术等,常见的药物症状关联有地黄-风团、防风-瘙痒等,其中地黄-风团的置信度(1.00)和支持度(0.97)最高。结论:该研究基于条件随机域构建了一种新的文本挖掘信息模型,该模型有利于高效整理和挖掘名老中医临床医案中的经验与学术思想,对名老中医的学术思想和经验传承具有重要意义。     

Differential physiological and behavioral cues observed in individuals smoking botanical marijuana versus synthetic cannabinoid drugs

Context: Synthetic cannabinoid use has increased in many states, and medicinal and/or recreational marijuana use has been legalized in some states. These changes present challenges to law enforcement drug recognition experts (DREs) who determine whether drivers are impaired by synthetic cannabinoids or marijuana, as well as to clinical toxicologists who care for patients with complications from synthetic cannabinoids and marijuana. Our goal was to compare what effects synthetic cannabinoids and marijuana had on performance and behavior, including driving impairment, by reviewing records generated by law enforcement DREs who evaluated motorists arrested for impaired driving. Methods: Data were from a retrospective, convenience sample of de-identified arrest reports from impaired drivers suspected of using synthetic cannabinoids (n?=?100) or marijuana (n?=?33). Inclusion criteria were arrested drivers who admitted to using either synthetic cannabinoids or marijuana, or who possessed either synthetic cannabinoids or marijuana; who also had a DRE evaluation at the scene; and whose blood screens were negative for alcohol and other drugs. Exclusion criteria were impaired drivers arrested with other intoxicants found in their drug or alcohol blood screens. Blood samples were analyzed for 20 popular synthetic cannabinoids by using liquid chromatography-tandem mass spectrometry. Delta-9-tetrahydrocannabinol (THC) and THC-COOH were quantified by gas chromatography-mass spectrometry. Statistical significance was determined by using Fisher’s exact test or Student’s t-test, where appropriate, to compare the frequency of characteristics of those in the synthetic cannabinoid group versus those in the marijuana group. Results: 16 synthetic cannabinoid and 25 marijuana records met selection criteria; the drivers of these records were arrested for moving violations. Median age for the synthetic cannabinoid group (n?=?16, 15 males) was 20 years (IQR 19–23 years). Median age for the marijuana group (n?=?25, 21 males) was 20 years (IQR 19–24 years) (p?=?0.46). In the synthetic cannabinoid group, 94% (15/16) admitted to using synthetic cannabinoids. In the marijuana group, 96% (24/25) admitted to using marijuana. Blood was available for testing in 96% (24/25) of the marijuana group; 21 of these 24 had quantitative levels of THC (mean?+?SD?=?10.7?+?5 ng/mL) and THC-COOH (mean?+?SD?=?57.8?+?3 ng/mL). Blood was available for testing in 63% (10/16) of the synthetic cannabinoid group, with 80% (8/10) of these positive for synthetic cannabinoids. Those in the synthetic cannabinoid group were more frequently confused (7/16 [44%] vs. 0/25 [0%], p?≤?0.003) and disoriented (5/16 [31%] vs. 0/25 [0%], p?≤?0.003), and more frequently had incoherent, slurred speech (10/16 [63%] vs. 3/25 [12%], p?=?0.0014) and horizontal gaze nystagmus (8/16 [50%] vs. 3/25 [12%], p?=?0.01) than those in the marijuana group. Conclusion: Drivers under the influence of synthetic cannabinoids were more frequently impaired with confusion, disorientation, and incoherent, slurred speech than drivers under the influence of marijuana in this population evaluated by DREs.     

新型冠状病毒肺炎防控期间预防肺功能检查交叉感染专家共识

新型冠状病毒肺炎(novel coronavirus pneunomia,NCP)主要通过呼吸道飞沫传播和接触传播。结合肺功能检查的操作特殊性,本共识从受试者和检查室的准备、肺功能操作人员的防护、仪器的清洗和消毒、特殊情况的应对以及感控的监督等方面,制订了在当前疫情防控的严峻形势下预防肺功能检查交叉感染的具体措施。当前疫情防控重要阶段,建议暂缓肺功能检查,如临床急需,要在做好防护的前提下进行必要的检查。     

尤昭玲“助卵养巢”治疗多囊卵巢综合征经验

多囊卵巢综合征(PC OS)是生育期妇女月经紊乱、不孕最常见的原因之一,其中部分PCOS患者卵巢储备功能下降,在体外受精-胚胎移植过程中呈卵巢低反应状态.“助卵养巢”是尤老师治疗PCOS卵巢储备功能不良特殊患者的思路之一,主要治法为补肾填精,健脾益气,通调冲任.     

中国进展期乳腺癌共识指南（CABC 2015）

在2013年出版的《首届中国进展期乳腺癌共识指南（草案）》（CABC1）的基础上,本指南进一步更新了进展期乳腺癌诊疗过程的一般原则、相关的定义、疗效的评估、不良反应的管理及不同治疗方法的基本策略等内容;专家组系统阅读国内外各种关于进展期乳腺癌的临床研究（包括回顾性的资料分析）,整理并总结了各种相关指南,召开会议组织专家进行了多次讨论,将在循证医学基础上达成的专家共识整理成文,为从事乳腺癌专业的医生,尤其是以治疗进展期乳腺癌为主要专业的医生,提供参考。     

心脑宁胶囊治疗动脉粥样硬化性心血管疾病临床应用专家共识

本共识建立了成人动脉粥样硬化性心血管疾病(atherosclerotic cardiovascular disease,ASCVD)高危人群规范应用心脑宁胶囊以提升疗效的关键流程,概述了心脑宁胶囊的中医配伍理论、药学和药理研究特性,界定了心脑宁胶囊的精确适用人群、干预时机、病证疗效特点及优选应用方案,归纳了心脑宁胶囊的不良反应、使用禁忌、注意事项及非临床安全性等相关证据。本共识适合ASCVD相关专业领域的执业医师、执业中医医师和执业中西医结合医师使用。     

Learning classification models from multiple experts

Building classification models from clinical data using machine learning methods often relies on labeling of patient examples by human experts. Standard machine learning framework assumes the labels are assigned by a homogeneous process. However, in reality the labels may come from multiple experts and it may be difficult to obtain a set of class labels everybody agrees on; it is not uncommon that different experts have different subjective opinions on how a specific patient example should be classified. In this work we propose and study a new multi-expert learning framework that assumes the class labels are provided by multiple experts and that these experts may differ in their class label assessments. The framework explicitly models different sources of disagreements and lets us naturally combine labels from different human experts to obtain: (1) a consensus classification model representing the model the group of experts converge to, as well as, and (2) individual expert models. We test the proposed framework by building a model for the problem of detection of the Heparin Induced Thrombocytopenia (HIT) where examples are labeled by three experts. We show that our framework is superior to multiple baselines (including standard machine learning framework in which expert differences are ignored) and that our framework leads to both improved consensus and individual expert models.