Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

Reacreditación o recertificación de los cirujanos generales en España: esa es la cuestión. Resultados de una encuesta nacional

IntroductionThe Law for the Regulation of Health Professions (LOPS) indicates that health professionals will carry out continuous training throughout their professional life, and will regularly prove their professional competence. The objective of the study was to carry out a national survey to find out the opinion of Spanish surgeons and thus be able to prepare a recertification project by the Spanish Association of Surgeons (AEC).MethodsCross-sectional observational study carried out in June-July 2020, through a survey sent to the members of the AEC.ResultsThe survey had a total of 1230 visits and an overall completion rate of 784 responses (67.3%). 69.6% were unaware of the LOPS forecasts and 83.4% were unaware of similar initiatives in other specialties and 95.5% agreed to demand adequate information. 71.4% believed it necessary but only 57% believed that it should be mandatory. 82.9% would agree that it should be regulated through an objective and predictable official procedure.ConclusionsThe concept of re-accreditation is not well known in our specialty and in view of the results obtained, adequate and reliable information seems necessary. Therefore, it would be pertinent to propose by the AEC a specific project to assess activities and skills.     

Prolyl and lysyl hydroxylases in collagen synthesis

Collagens are the most abundant proteins in the extracellular matrix. They provide a framework to build organs and tissues and give structural support to make them resistant to mechanical load and forces. Several intra‐ and extracellular modifications are needed to make functional collagen molecules, intracellular post‐translational modifications of proline and lysine residues having key roles in this. In this article, we provide a review on the enzymes responsible for the proline and lysine modifications, that is collagen prolyl 4‐hydroxylases, 3‐hydroxylases and lysyl hydroxylases, and discuss their biological functions and involvement in diseases.     

COVID-19 Gender Disparities and Mitigation Recommendations: A Narrative Review

The coronavirus disease 2019 (COVID-19) pandemic has rapidly created widespread impacts on global health and the economy. Data suggest that women are less susceptible to severe illness. However, sex-disaggregated data are incomplete, leaving room for misinterpretation, and focusing only on biologic sex underestimates the gendered impact of the pandemic on women. This narrative review summarizes what is known about gender disparities during the COVID-19 pandemic and the economic, domestic, and health burdens along with overlapping vulnerabilities related to the pandemic. In addition, this review outlines recommended strategies that advocacy groups, community leaders, and policymakers should implement to mitigate the widening gender disparities related to COVID-19.     

我国家庭医生签约服务政策执行的制约因素与优化路径：基于史密斯政策执行过程模型

深化家庭医生签约服务是深化医药卫生体制改革、强化基层医疗卫生服务、实现"健康中国"战略目标的重要选择，也是当前更好维护人民群众健康的重要途径。为有效推进签约服务工作，国家陆续推出各项政策，全国各地也在积极进行实践探索，成效明显。但是，签约服务仍面临诸多问题，其中"执行难"是签约服务深度推进的一大困境。通过史密斯政策执行过程模型，结合签约服务政策执行过程，发现签约服务仍存在法治性不足、政策执行人员水平不高、激励不足、政策环境影响等诸多制约因素。因此，需要从法律和制度方面进行顶层设计、提升执行人员素质和职业认同、建立医患互信、优化政策执行环境等角度进行政策创新，探索家庭医生签约服务可持续发展的路径。     

Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy

1. Download : Download high-res image (173KB)
2. Download : Download full-size image

     

流动人口基层医疗卫生机构首诊现状及影响因素分析

目的:了解流动人口基层首诊现状及其影响因素,为推进流动人口分级诊疗提供实证参考依据。方法:基于2017年全国流动人口动态监测调查数据中82734名最近1次患病(负伤)流动人口数据,利用SPSS 25.0统计软件分析其基层首诊情况及影响因素。结果:82734名最近1次患病(负伤)流动人口中首选到基层医疗卫生机构就诊15936人,基层首诊率仅为19.3%;二分类logistic回归分析结果显示:年龄≥65岁、农业户口、流动时间0~5年、患慢性病、至少参加1项医疗保险,居住地到最近医疗服务机构所需时间≤15 min的流动人口患病后更愿意选择到基层首诊。学历大专及以上、家庭月均收入>10000元、市跨县、东北地区、不愿意落户、自评健康状况为不健康的流动人口患病后更不愿意选择到基层首诊。结论:流动人口患病(负伤)后选择到基层首诊率较低,年龄、受教育程度、户口类型、家庭月均总收入、流动时间、流动范围、流入地区域、落户意愿、自评健康状况、是否患慢性病、有无参加医疗保险、居住地到最近医疗服务机构所需时间是影响流动人口患病(负伤)后选择到基层首诊的主要因素。