Characterization of Class 1 Integron Gene Cassettes among Clinical Bacteria Isolated from One Large Hospital in Northern China

The class 1 integron and complex gene cassettes among different species of clinical isolates in northern China were characterized in this study. 383 clinical isolates were obtained from northern China, and class 1 integrons containing gene cassettes widely distributed among gram negative clinical isolates was observed. We find that the class 1 integron showed positive correlation with multidrug resistance phenotype of gram negative bacteria. In addition, we find that isolates belonged to one species harbored different types of gene cassette arrays, while same types of gene cassette arrays were observed in different species of isolates. The diversity of gene cassette arrays among the isolates indicated the complexity of multidrug resistance in clinical isolates in northern China.

Study of Cofactors Associated with Precancerous High-Grade Cervical Lesions at the Teaching Hospital Gabriel Touré, 2010 to 2015

Introduction: High grade dysplasia of the cervix has a high incidence and can progress to cervical cancer. The aim was to study cofactors associated with high-grade cervical dysplasia. Methodology: This was a retrospective case-control study without matching. Women with high grade dysplasia were the cases while those with a normal screening test represented the controls. The study took place at the Gabriel Touré University Hospital Center in Bamako. We included 351 cases and 420 controls. The capture and analysis were performed using the SPSS 20 software. A univariate and multivariate logistic regression analysis was performed for the analysis of risk cofactors. The statistical tests used were the odds ratio and its confidence interval and the statistical significance threshold was set at p Results: In univariate analysis, the co-factors statistically significantly associated with the occurrence of high-grade dysplasia were parity 0.6 (0.5 - 0.9), gestational 0.7 (0.5 - 0.9), smoking of the spouse 3.4 (1.1 - 11.3), the non-schooling 1.4 (1.2 - 2.1). In multivariate analysis after adjusting for confounding factors, two co-factors have significantly increased the risk of high-grade dysplasia: lack of schooling 1.4 (1.2 - 2.0) and polygamy 1.5 (1.4 - 2.5). Conclusion: At the end of this study, polygamy and lack of schooling were the main risk factors. The prevention of cervical cancer will go through the education of girls and women as well as communication for behavioral change and social change.

Burnout and work-family conflict among nurses during the preparation for reevaluation of a grade A tertiary hospital

Objectives： To gain a better understanding of nurse burnout and work-family conflict for nurses and to help the hospital prepare for hospital grade reevaluation.Methods： This study is a cross-sectional study, and 95 nurses participated. The questionnaires included MBI and Carlson work-family conflict questionnaires, and the data were analyzed using SPSS 17.Results： A total of 71.6% of nurses worked over 8 h per day during the last two months before the reevaluation. The total score of burnout of nurses was 66.84 ± 12.60, and the proportion of heavy work burnout was 44.2%. The personal accomplishment takes the heaviest portion（80.0%）. The total score of work-family conflict is 55.19 ± 9.27. The scores of work-to-family conflict are all higher than that of family-to-work conflict. The time dimension had the highest score.Conclusions： During the preparation period, nurses suffered from a heavy workload and intense job burnout, and many aspects of work-family conflict existed.

Study on Health Management and Service Model of Chifeng Class 3A General Public Hospital

This study investigates the construction of a health management service mode based on large-scale comprehensive hospitals by analyzing health management service modes at home and abroad,that is,taking the Affiliated Hospital of Chifeng University as an example,establish a health examination hospital,undertake core tasks such as health service operation process,system,monitoring,and system formulation,and take the best medical resources.Attract social medical resources to collaborate and give health service mode of health status monitoring,evaluation,and intervention to health service objects,aided by advanced medical technology.To extend the traditional health management service with the hospital as the protagonist to health management with participation from family and society beyond the hospital,forming a closed-loop,rapid,and efficient health service management system.Thus,through graded quality services,to lessen the difficulties of patients seeing a doctor and to solve the problem of overcrowding and minor ailments in major hospitals.

Probe in college English teaching in Grade-C class

College English is not only an essential curriculum of language, but also is an extremely important curriculum of cultural in college education. As a result of various factors, there are individual differences in college students＇ English study. Therefore, to gradually improve all the students＇ English, graded teaching becomes the best choice. In this thesis, graded teaching will be studied from several respects. And I hope it can give some slight help to some of college teachers.

PLDMLT:Multi-Task Learning of Diabetic Retinopathy Using the Pixel-Level Labeled Fundus Images

In the field of medical images,pixel-level labels are time-consuming and expensive to acquire,while image-level labels are relatively easier to obtain.Therefore,it makes sense to learn more information(knowledge)from a small number of hard-to-get pixel-level annotated images to apply to different tasks to maximize their usefulness and save time and training costs.In this paper,using Pixel-Level Labeled Images forMulti-Task Learning(PLDMLT),we focus on grading the severity of fundus images for Diabetic Retinopathy(DR).This is because,for the segmentation task,there is a finely labeled mask,while the severity grading task is without classification labels.To this end,we propose a two-stage multi-label learning weakly supervised algorithm,which generates initial classification pseudo labels in the first stage and visualizes heat maps at all levels of severity using Grad-Cam to further provide medical interpretability for the classification task.A multitask model framework with U-net as the baseline is proposed in the second stage.A label update network is designed to alleviate the gradient balance between the classification and segmentation tasks.Extensive experimental results show that our PLDMLTmethod significantly outperforms other stateof-the-art methods in DR segmentation on two public datasets,achieving up to 98.897%segmentation accuracy.In addition,our method achieves comparable competitiveness with single-task fully supervised learning in the DR severity grading task.

Genomic profiling of lower-grade gliomas uncovers cohesive disease groups:implications for diagnosis and treatment

Lower-grade gliomas(including low-and intermediate-grade gliomas,World Health Organization grades II and III)are diffusely infiltrative neoplasms that arise most often in the cerebral hemispheres of adults and have traditionally been classified based on their presumed histogenesis as astrocytomas,oligodendrogliomas,or oligoastrocytomas.Although the histopathologic classification of lower-grade glioma has been the accepted standard for nearly a century,it suffers from high intra-and inter-observer variability and does not adequately predict clinical outcomes.Based on integrated analysis of multiplatform genomic data from The Cancer Genome Atlas,lower-grade gliomas have been found to segregate into three cohesive,clinically relevant molecular classes.Molecular classes were closely aligned with the status of isocitrate dehydrogenase(IDH)mutations,tumor protein 53 mutations and the co-deletion of chromosome arms 1 p and 19q,but were not closely aligned with histologic classes.These findings emphasize the potential for improved definition of clinically relevant disease subsets using integrated molecular approaches and highlight the importance of biomarkers for brain tumor classification.

Modeling Crash Risk at Rail-Highway Grade Crossings by Track Class

The Federal Railroad Administration (FRA)’s Web Based Accident Prediction System (WBAPS) is used by federal, state and local agencies to get a preliminary idea on safety at a rail-highway grade crossing. It is an interactive and user-friendly tool used to make funding decisions. WBAPS is almost three decades old and involves a three-step approach making it difficult to interpret the contribution of the variables included in the model. It also does not directly account for regional/local developments and technological advancements pertaining to signals and signs implemented at rail-highway grade crossings. Further, characteristics of a rail-highway grade crossing vary by track class which is not explicitly considered by WBAPS. This research, therefore, examines and develops a method and models to estimate crashes at rail-highway grade crossings by track class using regional/local level data. The method and models developed for each track class as well as considering all track classes together are based on data for the state of North Carolina. Linear, as well as count models based on Poisson and Negative Binomial (NB) distributions, was tested for applicability. Negative binomial models were found to be the best fit for the data used in this research. Models for each track class have better goodness of fit statistics compared to the model considering data for all track classes together. This is primarily because traffic, design, and operational characteristics at rail-highway grade crossings are different for each track class. The findings from statistical models in this research are supported by model validation.

The Inquiry of the Junior Graded Teaching Method——A Case Study

Graded teaching divides students into classes in which students are at the same level.Graded teaching is the variant and development of traditional methods.This article makes some introduction of graded teaching,has a review of the theoretical development and tries to analyses its advantages and disadvantages.Lastly,we have some specific requirements for teachers.

基于MassMotion仿真的三甲医院急诊科感控管理优化研究

选取某三甲医院急诊科一层特定时间段所有患者就诊全过程的行为数据,将患者行为数据输入到Mass Moton行人模拟软件中,模拟三种不同管理策略下的急诊科状况,对比不同的模拟结果,对急诊科感控管理策略进行优化。

基于DEA-Malmquist指数的江苏省三级甲等公立中医医院运行效率研究

目的:研究2018—2020年江苏省三级甲等公立中医医院(三甲公立中医院)运行效率状况,为改善中医院医疗服务效率提供参考。方法:基于2018—2020年江苏省卫生资源与医疗服务调查内部资料,运用DEA-Malmquist指数法分析2018—2020年江苏省三甲公立中医院全要素生产率。结果:2018—2020年,江苏省三甲公立中医院综合效率均值为0.965,纯技术效率均值为0.986,规模效率均值为0.977;2018—2020年江苏省三甲公立中医院全要素生产率变化指数上升27.80%,技术效率变化指数上升2.60%,技术变化指数上升23.80%,纯技术效率变化指数上升1.90%,规模效率变化指数上升0.60%。结论:样本期内江苏省三甲公立中医院运行效率呈下降趋势;区域间三甲公立中医院全要素生产效率存在差异,而技术进步是推动全要素生产率提高的关键因素。须激活三甲公立中医院发展新动力,推动全要素生产效率提升。

MOOC Learner’s Final Grade Prediction Based on an Improved Random Forests Method

Massive Open Online Course(MOOC)has become a popular way of online learning used across the world by millions of people.Meanwhile,a vast amount of information has been collected from the MOOC learners and institutions.Based on the educational data,a lot of researches have been investigated for the prediction of the MOOC learner’s final grade.However,there are still two problems in this research field.The first problem is how to select the most proper features to improve the prediction accuracy,and the second problem is how to use or modify the data mining algorithms for a better analysis of the MOOC data.In order to solve these two problems,an improved random forests method is proposed in this paper.First,a hybrid indicator is defined to measure the importance of the features,and a rule is further established for the feature selection;then,a Clustering-Synthetic Minority Over-sampling Technique(SMOTE)is embedded into the traditional random forests algorithm to solve the class imbalance problem.In experiment part,we verify the performance of the proposed method by using the Canvas Network Person-Course(CNPC)dataset.Furthermore,four well-known prediction methods have been applied for comparison,where the superiority of our method has been proved.

“Six-and-twelve” score for outcome prediction of hepatocellular carcinoma following transarterial chemoembolization. In-depth analysis from a multicenter French cohort

The“six-and-twelve”(6&12)score is a new hepatocellular carcinoma(HCC)prognostic index designed for recommended transarterial chemoembolization(TACE)candidates.Quick and easy to use by the sum of tumor size(cm)and number,this model identifies three groups with different survival time(the sum is≤6;or>6 but≤12;or>12);a survival benefit with TACE can be expected for HCC patients with a score not exceeding twelve.Recently,Wang ZW et al showed that the“6&12”model was the best system correlated with radiological response after the first TACE.Thus,we wanted to assess its survival prediction ability as well as its prognostic value and compared it to other systems(Barcelona Clinic Liver Cancer,Hong Kong Liver Cancer(HKLC)staging,Albumin-Bilirubin grade,tumor nodularity,infiltrative nature of the tumor,alpha-fetoprotein,Child-Pugh class,and Performance Status score,Cancer of the Liver Italian Program,Model to Estimate Survival for HCC scores,up-to-seven criteria)different from Wang ZW et al study in a multicenter French cohort of HCC including only recommended TACE candidates retrospectively enrolled.As previously demonstrated,we show that the"6&12”score can classify survival within this French cohort,with a prognostic value comparable to that of other systems,except HKLC staging.More importantly,the“6&12”score simplicity and ability in patients’stratification outperform other systems for a routine clinical practice.

新形势下三甲医院人力资源管理创新策略探究

为更好地发挥三甲医院医务工作者的主观能动性,提升医务工作者的整体素质,应加速推进医院人力资源管理的变革。基于此,笔者通过对三甲医院人力资源管理的现状进行深入剖析,根据实际情况,从管理理念创新、管理制度创新、管理方式创新等方面有针对性地提出了一些策略。

黑龙江省三级甲等医院护士长绩效考评指标体系构建

目的构建黑龙江省三级甲等医院护士长绩效考评指标体系,旨在为临床护理管理提供参考依据。方法通过文献分析、理论研究初步编制黑龙江省三级甲等医院护士长绩效考评指标体系框架与内容,采用德尔菲法进行2轮专家函询,最终构建黑龙江省三级甲等医院护士长绩效考评指标体系。结果构建的黑龙江省三级甲等医院护士长绩效考评指标体系包含5个一级指标、14个二级指标、49个三级指标,专家咨询可信度高。结论构建黑龙江省三级甲等医院护士长绩效考评指标体系不仅能为省内各级医疗机构的护理管理者和研究者提供参考依据,还能为护士长提高自身护理管理水平提供实践指导。

河南省三级公立医院智慧管理建设现状调查与分析

目的:调查分析河南省三级公立医院智慧管理建设现状,为公立医院推动智慧管理建设提供参考。方法:对河南省143所三级公立医院信息管理部门的主管人员和负责管理信息化建设的院领导进行调查。结果:80%的受访医院已开始推进智慧管理建设工作,但仍面临资金和资源不足、技术能力储备不足和业务系统协同困难等挑战。虽然医院智慧管理各业务域的信息化系统建设已有所进展,但在设备设施管理、运营管理、运行保障管理和教学科研管理等方面信息系统建设率相对较低。结论:医院智慧管理建设应实事求是,强化顶层设计与组织管理,进一步提升信息化建设水平,加强数据治理与决策支持。

广东省三级综合医院优质护理服务评价指标的构建

目的构建广东省三级综合医院优质护理服务评价指标,为促进优质护理服务评价工作和规范优质护理服务提供参考。方法基于文献检索的基础上,应用头脑风暴法并借鉴国内已有的相关制度、标准和政策构建出评价指标条目池和问卷初稿;采用德尔菲法对评价指标进行两轮专家函询。结果两轮专家函询的回收率分别为80.00%和91.67%;权威程度系数均为0.93,医院部分Kendall协调系数W分别为0.128和0.116,病区部分分别为0.193、0.107,差异具有统计学意义(均P<0.001)。第2轮函询医院各指标的重要性均数为(4.43~5.00)分。第2轮函询病区各指标的重要性均数为(4.59~5.00)分。构建的广东省三级综合医院优质护理服务评价指标包括医院和病区两个部分,其中医院部分包括一级指标8项、二级指标22项、三级指标65项,病区部分包括一级指标9项、二级指标23项、三级指标50项。结论本研究编制的广东省三级综合医院优质护理服务评价指标具有较好的科学性和可靠性,有利于完善优质护理服务管理制度,引导优质护理服务健康发展。

疾病诊断相关分组支付方式对三甲中医院财务管理的影响及应对策略

探讨了疾病诊断相关分组(DRG)支付方式对三甲中医院财务管理的影响并提出应对策略。结合所在医院随机抽取的某月各科室相关数据,运用DRG支付方式下的相应指标并结合波士顿矩阵理论模型进行全面综合评价分析。2023年1月,所在医院5个科室CMI值高于全院平均水平,且盈余情况良好;8个科室CMI值低于全院平均水平,但有盈余;14个科室CMI值低于全院平均水平,且还有亏损;8个科室CMI值高于全院平均水平,却有亏损。DRG支付方式对三甲中医院来说,既是机遇也是挑战,对三甲中医院信息化数据系统、成本核算精细化提出高要求,对预算管理、拓展收入增长内涵提出新要求。三甲中医院应重视病案质量主体培训,强化成本内控,转为质量效益型运营管理模式,应用临床路径以“提质控费”,发挥中医药优势学科,结合中医治疗特点来制定适合中医发展的DRG支付方式。

混合编班“大学物理”分级教学分类评价研究与实践探索

“大学物理”是为新疆大学16个理工科学院44个理工科本科专业开设的通识教育必修课程。“大学物理”课程所教授的基本概念、基本方法和基本理论是构成新时代大学生科学素养的重要组成部分,在学校各理工科专业高质量发展中发挥着夯基铸魂和启智润心的协同育人作用。基于新疆大学生源结构和专业特点,从混合编班“大学物理”分级教学分类评价的现实意义、具体举措及运行实效三个方面论述了混合编班“大学物理”分级教学分类评价的最新研究成果和实践经验,将为边疆民族地区高等学校混合编班“大学物理”分级教学分类评价提供有益参考。

某大型三甲医院编制外人员用工特点和风险规避研究

随着医疗体制改革的深入推进,三甲医院逐渐重视编制外人员的引入,一定程度上满足医院的用人需求。三甲医院既要调动编制外人员的工作积极性,又要规避用工风险,最大程度上发挥编制外人员在医院诊疗中的作用。笔者以北京某三甲医院为例,介绍了案例医院编制外人员现状,总结了编制外人员用工特点,并从政府、医院、社会三方面探究案例医院编制外人员用工风险规避措施。