An intuitive risk factors search algorithm: usage of the Bayesian network technique in personalized medicine

The article focuses on the application of the Bayesian networks (BN) technique to problems of personalized medicine. The simple (intuitive) algorithm of BN optimization with respect to the number of nodes using naive network topology is developed. This algorithm allows to increase the BN prediction quality and to identify the most important variables of the network. The parallel program implementing the algorithm has demonstrated good scalability with an increase in the computational cores number, and it can be applied to the large patients database containing thousands of variables. This program is applied for the prediction for the unfavorable outcome of coronary artery disease (CAD) for patients who survived the acute coronary syndrome (ACS). As a result, the quality of the predictions of the investigated networks was significantly improved and the most important risk factors were detected. The significance of the tumor necrosis factor-alpha gene polymorphism for the prediction of the unfavorable outcome of CAD for patients survived after ACS was revealed for the first time.     

Interview schedule development for a Sequential explanatory mixed method design: complementary-alternative medicine (CAM) study among Indonesian psychologists

Sequential explanatory mixed method design is the most frequently applied in both health and social sciences literature. It is denoted by ‘QUAN → qual’ which represents the quantitative study occurs first and has greater weight in addressing the study’s aims, and the qualitative study follows to explain quantitative results. Despite the extensive use of sequential explanatory design, there are limited references to this design. Therefore, this methodological paper attempts to fill the gap by providing an illustration in developing a sequential explanatory interview schedule based on complementary-alternative medicine (CAM) study among clinical psychologists in Indonesia. The most important step to develop sequential explanatory interview schedule was the construction of aspects and questions that were immensely grounded on the most notable quantitative results. In this study, eight aspects of interview schedule were constructed after analyses of the nationwide survey. The interview schedule then piloted among participants with fairly similar characteristics to the participants in the main interviews. This process enhanced the quality of questions through feedback from participants and improved the interviewer’s skills through familiarization with questions. It is expected that this reflection report could be adopted as a practical guideline in developing interview schedule for sequential explanatory mixed method design, particularly in the field of psychology.     

The case of vegetovascular dystonia: inventing the most common Soviet disease

ABSTRACT

The paper considers the case of vegetovascular dystonia, one of the most typical and common “Soviet” diseases. This syndrome emerged in Soviet medicine after World War II, and very quickly become a popular diagnosis among physicians. The author describes how the construct of vegetovascular dystonia was formed and developed, what changes it underwent, and what affected those changes. The concept and history of vegetovascular dystonia can provide an understanding of Soviet medicine and health science in general.     

Implementing a college mental health program – an overview of the first twelve months

Objective: To evaluate the demographics and clinical utilization patterns among college students during the initial 12 months of a novel, multi-disciplinary, collaborative, college mental health program (CMHP). Participants: Undergraduate and graduate students receiving treatment at the CMHP from Jan-Dec 2015. Methods: De-identified data was obtained via electronic health records for all students receiving care through the CMHP. Results: 1.2 FTE clinical providers treated 278 undergraduate and graduate students during the year (65.1% < age 26, 53.6% female, 49.6% caucasian). There were 1822 CMHP outpatient visits, 318 other medical visits and 103 total emergency room (ER)/inpatient visits. Ten students were identified as high utilizers of ER/inpatient services, while charges to the CMHP totaled $470,157 and total charges to the Health System were $2,378,315. Conclusions: Students with complex psychiatric/medical co-morbidities received cost effective, convenient and integrative treatment. Over time, we hope to intervene earlier and decrease ER/inpatient visits.     

Development of predictive signatures for treatment selection in precision medicine with survival outcomes

For survival endpoints in subgroup selection, a score conversion model is often used to convert the set of biomarkers for each patient into a univariate score and using the median of the univariate scores to divide the patients into biomarker‐positive and biomarker‐negative subgroups. However, this may lead to bias in patient subgroup identification regarding the 2 issues: (1) treatment is equally effective for all patients and/or there is no subgroup difference; (2) the median value of the univariate scores as a cutoff may be inappropriate if the sizes of the 2 subgroups are differ substantially. We utilize a univariate composite score method to convert the set of patient's candidate biomarkers to a univariate response score. We propose applying the likelihood ratio test (LRT) to assess homogeneity of the sampled patients to address the first issue. In the context of identification of the subgroup of responders in adaptive design to demonstrate improvement of treatment efficacy (adaptive power), we suggest that subgroup selection is carried out if the LRT is significant. For the second issue, we utilize a likelihood‐based change‐point algorithm to find an optimal cutoff. Our simulation study shows that type I error generally is controlled, while the overall adaptive power to detect treatment effects sacrifices approximately 4.5% for the simulation designs considered by performing the LRT; furthermore, the change‐point algorithm outperforms the median cutoff considerably when the subgroup sizes differ substantially.     

江苏省核医学科关于新型冠状病毒肺炎疫情防控工作的意见和建议

新型冠状病毒感染的暴发已成为全球最具挑战性的公共卫生突发事件。在我国新型冠状病毒感染的肺炎被纳入传染病防治法规定的乙类传染病,采取甲类传染病管理。核医学科作为多个临床科室的“桥梁”,在实验室检查、临床影像检查及核素治疗中扮演重要角色,是科学防控的关键部门。为切实做好疫情防控工作,保证医疗质量和医疗安全,现根据核医学学科特点和性质及新型冠状病毒肺炎流行病学和传播特点,制定江苏省核医学科防控意见和建议。     

江苏省徐州市中医文化软实力研究

中医是我国优秀的文化资源,也是文化软实力的重要组成部分,提升江苏省中医文化软实力是健康江苏建设的重要任务。文章以增强徐州市中医文化软实力,传承中医文化为目的。从知识生产力、价值吸引力和社会影响力三个维度具体分析江苏省徐州市中医文化内涵,根据《中国卫生统计年鉴》的相关数据,总结徐州市中医文化软实力的优势和不足。     

个性化表达的盛筵——2014年度湖南散文创作综述

2014年湖南散文创作成绩斐然,个性化表达成为其鲜明标志,其中包含了两个重要方面:在思想情感方面,以个性化的情感体验和对现实人生的个性化思考为亮点;在文体方面,则表现为独特的历史文化品位以及叙述手法的革新。     

以服务基层为导向的全科医学人才培养模式的探索

当前，我国基层卫生技术人员队伍建设相对滞后，已经成为制约基层卫生机构发展的瓶颈。医学院校充分发挥人才培养职能，积极探索符合基层医疗服务特点的全科医生培养模式，对推动我国基层医疗卫生服务质量的提高，促进我国医药卫生体制改革的深化具有重要作用。本文对现阶段我国全科医学人才培养中存在的问题进行了分析，介绍了开展全科医学教育的重要意义，并结合辽宁医学院的工作实践，提出了以服务基层为导向的全科医学人才培养的建议和措施。     

培养医学生阅读风格促进中华医药传统文化教育

阅读从来就是培养文化和传承文化的重要途径，阅读风格的培养是涵养医学人文品格的重要内容。重构大学生阅读兴趣，提升医学生阅读层次，通过漫阅读、深阅读、精阅读、动阅读等多元形式，引导大学生在书籍的海洋里涵养身心，以提高医学生全面素质，培养医学人文精神，传承中华医药传统文化。