The role of National Immunization Technical Advisory Groups (NITAG) in strengthening health system governance: Lessons from three middle-income countries—Argentina,Jordan, and South Africa (2017–2018)

IntroductionToward the Global Vaccine Action Plan 2020 goal, almost 90% of countries have established a National Immunization Technical Advisory Group (NITAG). However, little is known about NITAG's contributions to governance.MethodsIn 2017–2018, a two-step, qualitative retrospective study was conducted. Jordan (JO), Argentina (AR), and South Africa (SA) were selected owing to government-financed NITAGs from middle-income countries (MICs), geographic diversity, and a vaccine introduction with NITAG support. Country case studies were developed, collecting data through desk review and face-to-face key informant interviews (KIIs) from Ministry of Health (MoH) and NITAG. Case studies were analyzed together, to assess governance applying the European Observatory on Health Systems and Policies framework focusing on transparency, accountability, participation, integrity, and policy capacity (TAPIC).ResultsDocument review and 53 KII (22 AR, 20 SA, 11 JO) showed NITAGs played a pivotal role as advisors promoting a culture of evidence-informed policies. NITAGs strengthened governance, although practices varied among countries. Meetings were conducted behind-closed-doors, participation restricted to members, only in one country agendas, and recommendations were public (AR). To increase participation, policy capacity, and transparency, countries considered adding experts in communications, advocacy, and economics. AR and SA contemplated including community members. NITAGs functioned autonomously from the government, with no established internal or external monitoring or supervision. NITAG meeting minutes allowed the review of integrity, adherence to terms of reference, standard operating procedures, and conflict of interest (CoI). For the most part, NITAGs abided by their mandates. Significant issues were related to the level of MoH support and oversight of CoI declaration and documentation.ConclusionsSystematically implementing governance approaches could improve processes, better tailor policies, and implementation. The long-term survival and resilience of NITAGs in these countries showed they play a significant role in strengthening governance. Lessons learned could be useful to those promoting country-driven evidence-informed decision-making.     

基于复杂网络技术对电针治疗乳腺增生病处方分析

目的基于复杂网络技术分析电针治疗乳腺增生病的核心穴位及配伍穴相关性,并对电针波型进行探讨。方法检索中国期刊全文数据库(CNKI)、万方数据库、维普网数据库(VIP)中从1954年1月1日到2018年12月31日公开发表的电针治疗乳腺增生病的临床中文文献,利用Excel表格工具建立电针治疗乳腺增生病数据库,利用Matlab2014a软件进行节点中心性分析和聚类分析,利用Gephi0.9.1软件制作复杂网络示意图对分析结果进行描述和展示,利用Excel表格工具制作电针治疗乳腺增生病不同波形比例饼状图并分析其规律。结果选定43条电针处方:电针治疗乳腺增生病主穴核心度前三位依次为膻中穴、足三里、肩井穴;配伍穴位核心度前三位依次为太冲穴、太溪穴、脾俞穴;经络核心度前三位依次为足阳明胃经、任脉、足少阳胆经。配伍穴位相关性分析中,相关性频度前三位组合依次为太冲穴-太溪穴、太冲穴-肾俞穴、太冲穴-三阴交。电针波形中以连续波与疏密波常见,均具有较高的临床应用价值。结论电针治疗乳腺增生病处方以足阳明胃经为最多,其次为任脉;电针波型以连续波为主。     

普通变异型免疫缺陷病合并肝硬化1例并文献复习

目的:讨论普通变异型免疫缺陷病(common variable immunodeficiency disease,CVID)的发病机制、临床表现及治疗方法。方法:报道1例普通变异型免疫缺陷病合并肝硬化患者并复习相关文献。结果:普通变异型免疫缺陷病是临床少见病,易误诊,病因不清,临床表现复杂,部分患者病程中可出现肝功能异常,甚至并发肝硬化。结论:临床反复感染的患者应考虑CVID的可能,须进一步作血浆免疫球蛋白的检测确诊。对已经确诊患者定期补充静脉丙种球蛋白,同时还应定期检查肝功能。     

提高选题策划质量 提升行业期刊品牌影响力——以金属加工杂志社实践为例

【目的】 探讨行业期刊进行选题策划的方法,提升选题策划的质量。【方法】 利用互联网技术及新媒体资源,结合金属加工杂志社选题策划实例,归纳出几种选题策划的途径及方法。【结果】 结合行业热点进行选题策划,注重实效性和内容深度,提升期刊内容的可读性,可使期刊获得更多读者的关注和认可,提升期刊的行业影响力。【结论】 提高选题策划质量,可有效提升期刊内容的可读性,从而进一步提升期刊在行业的影响力。     

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.     

Analysis of relative effectiveness of high-dose versus standard-dose influenza vaccines using an instrumental variable method

Background

Observational studies of the relative effectiveness of influenza vaccines are essential for public health decision making. Their estimates, however, are subject to bias due to unmeasured confounders. Instrumental variable (IV) methods can control for observed and unobserved confounders.