高血压危险因素分类树分析

目的 探讨高血压的主要危险因素与高危人群，为高血压的防制提供理论依据。方法 采用以社区人群为基础的病例对照研究；以某工厂人群中筛检出的、未经药物系统治疗的l16名高血压患及136名血压正常健康为研究对象；运用分类树分析探讨高血压的主要危险因素与高危人群。结果 高血压的主要危险因素为：超重、中心型肥胖、饮酒、吸烟、高血脂症、年龄与性别。高血压主要高危人群为：(1)超重 中心型肥胖 饮酒；(2)超重 中心型肥胖 高年龄及其男性吸烟；(3)超重 高血脂症；(4)中心型肥胖 饮酒 吸烟。上述高危人群病例数占总病例数的82．76％。以学习集的分类结果为：灵敏度为82．76％，特异度为74．26％；以检验集的分类结果为：灵敏度为71．55％，特异度为61．03％。结论 对高血压不同高危人群应采取不同的防制措施；控制体重、饮酒、血脂水平、戒烟应为高血压一般人群防制的主要预防措施。     

低血压患病及其危险因素的分类树研究

[目的]了解居民低血压患病情况,探讨低血压的危险因素。[方法]利用广东省 2002 年居民营养与健康状况调查数据,分析15 951名15岁以上常住居民低血压患病情况,应用分类树模型分析其危险因素。[结果]低血压的患病率为3 9%,女性及低年龄组人群患病率较高。低血压的分类树分析中,共有7个中间结、8个终结点。女性、白领、睡眠时间长是低血压的危险因素,高年龄组、独居、重度职业性体力活动、腰围粗、体重指数高、高盐摄入、血脂高是其保护因素。分类树模型的灵敏度与特异度在学习集分别为 93 4%和 77 1%,在检验集分别为 83 2%和 77 9%。[结论]女性及低年龄组人群是低血压的高发人群;女性、白领、睡眠时间长是低血压的危险因素。     

应用分类树模型筛选logistic回归中的交互因素

目的探索自动筛选logistic模型中交互作用因素的方法。方法借助一个实例,说明分层、分类树与lo-gistic模型之间的关系,借助分类树模型自动进行筛选logistic模型中交互作用因素。结果本例分析结果表明,可以应用分类树为logistic模型筛选交互作用因素,并用logistic模型对可能的交互作用因素作最后检验,并通过实例说明应用要点。结论在logistic回归分析中,分类树可以有效地用于自动筛选可能的交互效应因素。     

基于分类树模型的2型糖尿病患者住院费用影响因素研究

目的 采用分类树模型对佛山市某三级医院2型糖尿病患者住院费用进行影响因素分析,为医院控制医疗费用、优化资源配置、完善制度设计提供依据。方法 以该院2021年1月至12月出院的2型糖尿病患者为研究对象,采用χ²检验进行单因素分析,分类树模型进行多因素分析。结果 2型糖尿病患者住院费用的中位数为6 370.64元,诊断费用最高,药品费用居第2位。住院费用与住院天数、并发症数量、支付方式和入院途径有关。结论 2型糖尿病患者住院费用结构不合理,需要进一步优化,应通过缩短住院时间、提高医疗水平、加强宣传教育、制定相关政策来降低住院费用。     

应用分类树模型构建缺血性脑卒中发病风险的预测模型

目的应用分类树模型构建缺血性脑卒中发病风险的预测模型,并评价其应用价值。方法采用1:1配比病例对照研究设计,选择深圳市2所综合性医院的309名缺血性脑卒中患者为病例组,同时选择按年龄、性别匹配的健康者作为对照;采用卡方自动交互检测(CHAID)法建立缺血性脑卒中发病风险的预测模型,采用错分概率Risk值、索引图及受试者工作特征曲线(ROC)评价模型的应用价值。结果所建立的分类树模型共包括4层,共19个结点,共筛检出6个解释变量;其中最为重要的预测因素为体育锻炼和高血压病史。模型错分概率Risk值为0.207,利用预测概率绘制的ROC曲线下面积为0.789,与0.5比较,差异有统计学意义(P=0.001),模型拟合的效果较好。结论分类树模型不仅能有效地拟合缺血性脑卒中发病风险的预测模型,还可以有效地筛检变量间的交互作用效应。     

应用分类树模型筛选恶性肿瘤危险因素的研究

目的介绍分类树模型筛选恶性肿瘤危险因素基本原理、运算法则和应用价值.方法以浙江省嘉善县乳腺癌现场调查数据为例,采用Exhaustive CHAID法建立分类树模型对调查结果进行危险因素筛选,使用错分概率Risk值和ROC曲线下面积对模型进行评价.结果分类树模型从全部105个候选变量中筛选出9个危险因素,其中职业是最重要的影响因素,工人、教师及退休人员的乳腺癌发生概率显著高于其他人员.另外,模型显示经常参加体育锻炼在不同人群中对乳腺癌的影响效果有所不同.模型错分概率Risk值为0.174,利用预测概率绘制的ROC曲线下面积为0.872,与0.5比较具有显著的统计学意义,模型拟合效果很好.结论分类树模型不仅可以有效挖掘筛选出主要的影响因素,还可以对研究变量科学定义分界点,展示变量间复杂的相互作用,在流行病学研究中具有较高的应用价值.     

广州市某中学初中生零食行为及其影响因素的分类树研究

目的 了解广州市初中生的零食行为,探讨其影响因素,为学校和相关卫生部门开展零食教育工作提供依据.方法 采用便利抽样方法,对广州市天秀初级中学全体在校生进行问卷调查,比较<儿童青少年零食消费指南>知晓程度以及性别对零食行为的影响,并用分类树模型筛选影响因素.结果 该校初中生零食消费率为46.3%;良好零食行为习惯形成比率是12.1%～72.6%;对指南认知程度不同的学生在注意零食营养(χ2=18.317,P＜0.05)、注意零食保质期(χ2=54.014,P＜0.05)、不在上网、看电视时吃零食(χ2=4.799,P＜0.05)、不在正餐前/后1～2 h吃零食(χ2=56.147,P＜0.05)、不以零食代替正餐(χ2=7.635,P＜0.05)等条目上差异有统计学意义;不同性别的学生在大部分的零食行为上差异均有统计学意义(P＜0.05);分类树分析表明:家长态度、每周可用零食费用、对指南的知晓程度和零食包装能够影响初中生每天的零食食用次数.结论 初中生良好的零食消费观念和行为还需改善,加强多部门合作,采取多种途径的宣传教育,合理指导初中生零食选择和食用十分重要.     

临床营养用药专题研讨会报道:肠内营养制剂分类及其依据

肠内营养制剂(enteralnutrition,EN)的临床应用在中国已有38年的历史。1974年EN制剂在北京应用于临床,并取得良好的效果。1979年在中国发表的有关肠外肠内营养临床应用的论文被美国MEDLINE文献库收录。但长期以来EN没有得到足够的重视,在中国的发展相当慢。许多人对分类也不清楚,有的药品指南中没有规范的分类,各地在使用EN通用名时常发生不规范的现象。这些已影响到EN的管理与合理应用。中华医学会北京分会于2002年11月在北京举行了第一次EN制剂的分类依据研讨会。邀请了国家药品监督管理局药品审评中心专家、国家药典委员会专家、…     

WAP-1型手握键白细胞骨髓细胞分类自动计数器的应用

近十年来 ,我国的检验医学取得了飞跃的发展 ,首先表现在仪器和技术方面的进展和更新。自动化仪器代替了手工操作 ,但是有些传统的检验技术仍然不能丢掉 ,例如骨髓细胞分类和白细胞分类 ,国内外检验专家认为 ,用显微镜分类才是真实的 ,血球自动分析仪 ,白细胞分类常出现很大的误差 ,几届全国临床检验学术会议上都有不少人提出这个问题。因此国内外多数医院坚持白细胞用显微镜分类 ,尤其白细胞总数异常的。有些省市发出文件明文规定 ,凡用血球自动分析仪的医院 ,一定要用显微镜进行白细胞分类。临床检验自动化仪器更新换代很快 ,而白细胞分类…     

长沙市甲型H1N1流感病程及其影响因素分类回归树分析

目的探讨影响甲型H1N1流感病程的影响因素。方法对长沙市2009-2010年甲型H1N1流感疫情资料,运用分类回归树的方法建立回归树模型,分析影响甲型H1N1流感病程的因素。结果发病到就诊的时间3 d、有基础性疾病、年龄≤3.5岁是导致甲型H1N1流感病程延长的危险因素。结论发病后及时就诊,加强对有基础性疾病及婴幼儿人群的预防与治疗,有助于缩短甲型H1N1流感病例的病程,减少重症病例的发生。     

Abnormal Behavior and Its Classification

Objective Make you better know about, pay more attention to, and more effectively distinguish the abnormal behavior. Methods Having analysed and compared the abnormal behavior in both the sociology and the psychiatry study - area, we define the idea of abnormal behavior from the mental - health angle, analyse its basic characters, and classify some types from multiple angles. Results According to the categories of human - being behavior, according to the cause or the nature of the abnormal behavior, and according to its social results, we make a classification. Conclusion Based upon an abnormal or unhealthy mentality, here＇ s abnormal behavior means deviating from the social normality and doing harm to oneself, others and society. So, in the view of mental health, the abnormal behavior in socioiogy obviously ranges too wide, while in psychiatry too narrowly.     

分类树中QUEST算法与多水平logistic模型的联合应用与比较

目的探讨分类树中的QUEST算法和多水平logistic模型联合应用于分析层次资料的可行性.方法首先介绍模型的原理,据此提出联合应用的具体思路,然后采用分析实例进行深入探讨,并用预测准确率和ROC曲线对模型拟合效果加以比较.结果QUEST算法能非常准确地搜索出主要影响因素,并能更加深入地刻画因变量、自变量间的复杂联系,在此基础上再进行多水平logistic模型会更加高效、准确.结论QUEST算法和多水平logistic模型各有优势,将它们联合用于层次资料的分析将更能保证分析的正确性和完善性.     

The Use of Risk Assessment to Predict Recurrent Maltreatment: A Classification and Regression Tree Analysis (CART)

Research has suggested that recurrent maltreatment may be best predicted by a combination of factors that vary across families. The present study set out to determine whether a pattern-centered analytic approach would better predict families at high risk for recurrence when compared to logistic regression methods. Archival data from substantiated investigations during 2003 were collected from a Connecticut Department of Children and Families county branch. Families (n = 244) with a substantiated index case were followed for 18 months to identify the presence of additional substantiated cases within the CPS system. Classification and Regression Tree (CART) analyses revealed that prior CPS involvement was the best predictor of recurrent maltreatment. Further, risk items that were associated with recurrence were different for families with and without previous CPS investigations. Families with only prior unsubstantiated CPS investigations and poor child visibility within the community were at high risk for recurrence. Families without prior CPS involvement that were not actively involved in case planning and had a history of domestic violence were at high risk for recurrence. These findings suggest that pattern-centered analyses may be a useful approach to informing site-specific predictors of maltreatment recurrence by creating clear decision points that delineate high risk subgroups.     

Classification of sporadic Creutzfeldt-Jakob disease based on clinical and neuropathological characteristics

Creutzfeldt-Jakob disease (CJD) is a rare and fatal neurodegenerative disease of unknown cause. Patients are usually aged between 50 and 75 and typical clinical features include rapidly progressive dementia associated with myoclonus and a characteristic electroencephalographic pattern. Neuropathological examination reveals cortical spongiform change, hence the term 'spongiform encephalopathy'. Several statistical techniques were applied to classify patients with sporadic CJD (sCJD), based on clinical and neuropathological investigation. We focus on the classification of neuropathologically confirmed sCJD patients. In order to obtain a classification rule that correctly classifies this type of patients and at the same time controls the overall error rate, we apply several classification techniques, which in general, produce comparable results. The boosting method produces the best results and the variable 14-3-3 protein in cerebrospinal fluid plays the most important role in the prediction of neuropathologically confirmed sCJD.     

浅谈非医疗事故医疗侵权行为的种类及认定

非医疗事故医疗侵权行为的种类及认定问题是司法实践中的难点.文章结合实际情况对非医疗事故医疗侵权行为的种类进行了分析、概括;对非医疗事故医疗侵权行为的认定问题也提出了自己的意见,以有益于非医疗事故医疗侵权行为的司法实践和侵权赔偿的理论研究.     

麻疹监测病例分类标准及其影响因素的分析

结合山东省1999年麻疹监测资料,对麻疹监测病例的分类及其影响因素进行了分析。通过比较卫生部1998年提出的分类标准与我省现行分类标准的优缺点,为今后我国加速麻疹控制乃至消除麻疹各阶段麻疹监测病例的分类标准提供依据。     

Classification trees for identifying non-use of community-based long-term care services among older adults

Home- and center-based long-term care (LTC) services allow older adults to remain in the community while simultaneously helping caregivers cope with the stresses associated with providing care. Despite these benefits, the uptake of community-based LTC services among older adults remains low. We analyzed data from a longitudinal study in Singapore to identify the characteristics of individuals with referrals to home-based LTC services or day rehabilitation services at the time of hospital discharge. Classification and regression tree analysis was employed to identify combinations of clinical and sociodemographic characteristics of patients and their caregivers for individuals who did not take up their referred services. Patients’ level of limitation in activities of daily living (ADL) and caregivers’ ethnicity and educational level were the most distinguishing characteristics for identifying older adults who failed to take up their referred home-based services. For day rehabilitation services, patients’ level of ADL limitation, home size, age, and possession of a national medical savings account, as well as caregivers’ education level, and gender were significant factors influencing service uptake. Identifying subgroups of patients with high rates of non-use can help clinicians target individuals who are need of community-based LTC services but unlikely to engage in formal treatment.