K-Means Clustering to Elucidate Vulnerable Subpopulations Among Medicare Patients Undergoing Total Joint Arthroplasty

BackgroundThe role of preoperative laboratory values for risk stratification following joint arthroplasty is currently ambiguous. In order to improve upon existing risk stratification within joint arthroplasty, this study sought to define novel phenotypes of total hip or total knee arthroplasty patients based entirely on preoperative laboratory measures. These phenotypes (“clusters”) were compared to elucidate statistically and clinically significant differences in outcomes.MethodsA total of 134,252 patients were gathered from the National Surgical Quality Improvement Program database between 2005 and 2015. “K-means” with 3 clusters was applied using 9 preoperative laboratory values: sodium, blood urea nitrogen (BUN), creatinine, albumin, bilirubin, white blood cell count, hematocrit, platelet count, and international normalized ratio of prothrombin values (INR). Outcome measures included 30-day readmissions, severe adverse events, and discharge to nonhome.ResultsCluster 2 was characterized by elevated preoperative BUN, creatinine, and INR and demonstrated almost twice the rate of adverse events (3.52% vs 2.20% and 2.22%), 30-day readmissions (6.39% vs 3.31% and 3.71%), and discharge to nonhome (47.97% vs 30.50% and 35.85%). Cluster 3 was characterized by a slightly higher risk of discharge to nonhome than cluster 1 and was overwhelmingly female (79.5% female, 35.8% discharge to nonhome). Cluster 1 represents the lowest-risk subgroup, experiencing the lowest rates of readmissions, adverse events, and discharge to nonhome.ConclusionPreoperative laboratory values, namely BUN, creatinine, and INR, are useful in identifying patients at risk of adverse outcomes. This analysis supports the existing surgical literature pushing for preoperative hydration as a targeted intervention to expedite recovery.     

Non-Gaussian water diffusion in aging white matter

Age-associated white matter degeneration has been well documented and is likely an important mechanism contributing to cognitive decline in older adults. Recent work has explored a range of noninvasive neuroimaging procedures to differentially highlight alterations in the tissue microenvironment. Diffusional kurtosis imaging (DKI) is an extension of diffusion tensor imaging (DTI) that accounts for non-Gaussian water diffusion and can reflect alterations in the distribution and diffusion properties of tissue compartments. We used DKI to produce whole-brain voxel-based maps of mean, axial, and radial diffusional kurtoses, quantitative indices of the tissue microstructure's diffusional heterogeneity, in 111 participants ranging from the age of 33 to 91 years. As suggested from prior DTI studies, greater age was associated with alterations in white-matter tissue microstructure, which was reflected by a reduction in all 3 DKI metrics. Prominent effects were found in prefrontal and association white matter compared with relatively preserved primary motor and visual areas. Although DKI metrics co-varied with DTI metrics on a global level, DKI provided unique regional sensitivity to the effects of age not available with DTI. DKI metrics were additionally useful in combination with DTI metrics for the classification of regions according to their multivariate “diffusion footprint”, or pattern of relative age effect sizes. It is possible that the specific multivariate patterns of age-associated changes measured are representative of different types of microstructural pathology. These results suggest that DKI provides important complementary indices of brain microstructure for the study of brain aging and neurologic disease.     

基于融合组合赋权和最优聚类机器学习方法的五味子保胃护肝保健食品配方设计与评价

目的 提出一种融合组合赋权、聚类、决策、评价等多种机器学习算法用于保健食品配方设计及评价的方法。方法以五味子Schisandre Chinensis Fructus为例,构建含五味子处方数据库,筛选与五味子配伍高频药味并挖掘其关联规则。同时结合传统中医药理论和现代科学研究建立评价指标体系,采用兼顾主观性和客观性的层次分析（analytic hierarchy process,AHP）-CRITIC(criteria importance though intercrieria correlation)组合赋权法和优选的聚类算法对高频药味进行加权和聚类,结合中医药理论设计配方并进行逼近理想解排序（technique for order preference by similarity to an ideal solution,TOPSIS）综合评价。结果 频次统计得到黄芪、茯苓、人参等与五味子配伍高频药味31个,关联规则分析显示高频药味间更易产生强关联。构建含3个一级指标、7个二级指标的评价指标体系,AHP-CRITIC组合赋权法计算出的指标组合权重从大到小依次为药味传统功效、现代文献研...     

应用并行化K-means优化算法探究中医治疗高血压用药规律

介绍并行化相关概念,包括Mapreduce编程框架以及Hadoop分布式文件系统,对传统K-means算法进行优化,建立并行化K-means聚类模型,探究中医治疗高血压用药规律,挖掘出中医辨证治疗高血压的8组用药组合,结合中医理论分析,验证结论真实性。     

基于小生境混合遗传算法的文本特征词聚类研究

提出一种基于小生境混合遗传算法的文本特征词聚类方法.该方法首先采用贝叶斯语义模型对语料库进行统计分析,并以K-L距离度量特征词间的距离,然后将小生境遗传算法与K-Means算法相结合,对文本特征词进行聚类,为文本特征词聚类提供了较高的效率和精确度.实验表明该方法是一种高效可行的文本特征词聚类方法.     

云南不明原因猝死时空分布特征研究

目的掌握云南不明原因猝死时空分布特征,为病因研究提供线索。方法使用1975—2008年回顾性调查和监测报告的375例云南不明原因猝死病例,描述其时间分布特征;制作猝死自然村空间分布图、采用一阶邻近系数等空间分析方法和技术来分析病例的空间分布特征;用K-均值聚类方法将发生猝死的自然村聚成几类发病区域,分析不同区域的时间分布特征。结果云南不明原因猝死病例分布在97个自然村;猝死自然村分布在云南省中部和西北部,在空间分布上呈现聚集性特征（一阶最邻近系数为0．489,P〈0．001）;97．0％的猝死发生于6～9月,猝死日期中位数为7月22日,在7月和8月各出现一个高峰;按空间位置可将猝死自然村聚为4类病区,用A、B、C、D表示,以鹤庆和宁蒗为代表的B类病区发病日期中位数为7月30日,比其他病区发病日期中位数7月19日迟11天。结论云南不明原因猝死具有时间特异性和空间特异性,主要在6～9月份集中发生在云南省中部和西北部区域的山区和半山区,不同区域发病时间不完全一致。     

Cluster analysis using physical performance and self-report measures to identify shoulder injury in overhead female athletes

Objectives

To evaluate the diagnostic validity of the Kerlan-Jobe orthopedic clinic shoulder and elbow score (KJOC) and the Closed kinetic upper extremity stability test (CKCUEST) to assess functional impairments associated with shoulder injury in overhead female athletic populations.

基于K-means聚类分析的婴幼儿睡眠模式及与母乳喂养关系的研究

目的 识别婴幼儿睡眠的典型模式及特征,并探讨睡眠模式与生后6个月内母乳喂养的关系。 方法 通过一般情况问卷、简明婴儿睡眠问卷（Brief Infant Sleep Questionnaire,BISQ）及喂养情况问卷,调查1 148名7~35月龄婴幼儿的睡眠情况和喂养方式。采用K-means聚类分析其睡眠模式及特征,并通过多因素logistic回归分析探讨婴幼儿睡眠模式与母乳喂养之间的关联。 结果 1 148名7~35月龄婴幼儿的睡眠模式可分为典型的3类：第1类为就寝时间早、睡眠时间长;第2类为入睡潜伏期短、睡眠时间中等;第3类为就寝时间晚、入睡潜伏期延长、睡眠时间不足。其中只有第3类为睡眠障碍模式。多因素logistic回归分析发现,与人工喂养的婴幼儿相比,生后6个月内的纯母乳喂养可降低69%睡眠障碍模式的发生风险（OR=0.31,95%CI：0.11~0.81,P<0.05）;母乳喂养时间达4~6个月者,相较于1~3个月者,可降低40%睡眠障碍模式的发生风险（OR=0.60,95%CI：0.38~0.96,P<0.05）。 结论 婴幼儿表现出不同的睡眠模式,母乳喂养可一定程度降低婴幼儿睡眠障碍模式的发生。     

徐州市区天主教信众心理健康状况调查

目的 调查徐州市区天主教信仰人群组成及心理健康状况,探讨宗教信仰与心理健康的关系.方法 采用随机整群抽样方法问卷调查江苏省徐州市天主信教人群.对信众的构成进行K-means聚类分析.结果 宗教信仰人群中老年居多,宗教信仰人群的心理异常率为37.6％,信仰天主教改善了人际敏感因子、忧郁因子、焦虑因子、敌对因子、偏执因子.强迫症因子也稍有变化.恐怖因子、精神病性因子未见明显变化,信众的躯体化因子高子常模水平.聚类分析揭示信众分老中青年3组,以女性为主,信教时间分20年左右和6～8年两组.结论 宗教信仰对改善信众的部分因子有帮助,而躯体化因子、恐怖和精神病性因子无改善,在控制宗教消极作用的前提下,信仰天主教可以改善心理健康状况,共建社会和谐.     

徐州农村空巢老人生存质量评价问题研究

目的 探讨生存质量分级评价的方法.方法选 择3种多元统计分析的方法(主成分分析、聚类分析、判别分析)对生存质量的资料进行分级评价.结果 将209名老人的生存质量分为好、中、差3级,各占的百分比为45.93％、33.02％、21.05％.结论 多种多元统计方法的综合应用能成功解决生存质量分级评价问题.