Friction and shear highly associated with pressure ulcers of residents in long‐term care – Classification Tree Analysis (CHAID) of Braden items

Aims Among various risk assessment scales for the development of pressure ulcers in long‐term care residents that have been published in the last three decades, the Braden scale is among the most tested and applied tools. The sum score of the scale implies that all items are equally important. The aim of this study is to show whether specific items are of greater significance than others and therefore have a higher clinical relevance. Design Data analysis of six pressure ulcer prevalence studies (2004–2009). Methods A total of 17 666 residents (response rate 79.6%) in 234 long‐term care facilities participated in 6 annual point prevalence studies that were conducted from 2004 to 2009 throughout Germany. For the classification of the sample regarding pressure ulcers as a dependent variable and the Braden items as predictor variables, Chi‐square Automatic Interaction Detector (CHAID) for modelling classification trees has been used. Results Pressure ulcer prevalence was 5.4% including pressure ulcer grade 1 and 3.4% for pressure ulcer grades 2–4. CHAID analysis for the classification tree provided the item ‘friction and shear’ as the most important predictor for pressure ulcer prevalence. On the second level, the strongest predictors were ‘nutrition’ and ‘activity’ and on the third level they were ‘moisture’ and ‘mobility’. Residents with problems regarding ‘friction and shear’ and poor nutritional status present with an 18.0 (14.8) pressure ulcer prevalence which is 3–4 times higher than average. Conclusion CHAID analyses have shown that all items of the Braden scale are not equally important. For residents in long‐term care facilities in Germany, the existence of ‘friction and shear’ as a potential and especially as a manifest problem has had the strongest association with pressure ulcer prevalence.     

基于决策树预测糖尿病合并冠心病患病风险的中医人格体质特征研究

目的 探讨中医人格及体质特征对糖尿病（MD）合并冠心病（CHD）的患病风险预测作用。方法 采用五态人格测验、五五体质检测测定110例T2MD患者的中医人格及体质特征;运用EXCEL及SPSS中决策树的CHAID算法,建构中医人格、体质类型预测MD患者合并CHD的患病风险模型,并对模型的预测准确性加以评估。结果 以少阴人格、阴寒质、血瘀质为预测变量构建的MD患病风险模型经10折交叉验证预测准确度为93.6%,准确率较高,并得到3条预测冠心病患病风险的规则。结论 以中医人格及体质特征预测MD合并CHD的风险规则符合中医传统认识,对高危人群的早期筛查、冠心病的防治及临床辨体论治提供了参考依据。      

The neural substrates for atypical planning and execution of word production in stuttering

Using an fMRI-based classification approach and the structural equation modeling (SEM) method, this study examined the neural bases of atypical planning and execution processes involved in stuttering. Twelve stuttering speakers and 12 controls were asked to name pictures under different conditions (single-syllable, multi-syllable, or repeated-syllable) in the scanner. The contrasts between conditions provided information about planning and execution processes. The classification analysis showed that, as compared to non-stuttering controls, stuttering speakers’ atypical planning of speech was evident in their neural activities in the bilateral inferior frontal gyrus (IFG) and right putamen and their atypical execution of speech was evident in their activations in the right cerebellum and insula, left premotor area (PMA), and angular gyrus (AG). SEM results further revealed two parallel neural circuits—the basal ganglia-IFG/PMA circuit and the cerebellum-PMA circuit—that were involved in atypical planning and execution processes of stuttering, respectively. The AG appeared to be involved in the interface of atypical planning and execution in stuttering. These results are discussed in terms of their implications to the theories about stuttering and to clinical applications.     

循环系统病例DRGs组合研究

目的 制定循环系统病例DRGs组合方案并进行初步评价.方法 以某院2003～2005年入院的循环系统病例病案首页相关数据为样本,采用CHAID模型,分别以住院费用和住院天数为目标变量,对内外科样本进行DRGs分组,并采用频数分布图对分组结果分析和评价.结果 对于9 008例循环系统病例,得到4组DRGs组合,频数分布图反映出相邻组合之间住院费用的变化趋势,但区分度有限.结论 以DRGs分组为基础,可引入其他敏感、合理的变量,进一步研究适合我国国情的 DRGs体系.     

Patient perceived priorities between technical skills and interpersonal skills: their influence on correlates of patient satisfaction

Objectives The study objective was to elucidate the differences in factors related to overall patient satisfaction levels among subgroups based on whether patients placed higher priorities on technical or interpersonal skills of health care personnel. Methods This questionnaire survey targeted 2341 patients discharged from five Japanese hospitals in 2007. Patients were grouped based on whether they prioritized technical or interpersonal skills by chi‐squared automatic interaction detection (CHAID) analysis. Multiple regression analysis was used to compare and evaluate differences in various factors related to patient satisfaction among the subgroups. Results Survey respondent rate was 55.7% (1305 patients). CHAID analysis showed that patients, in particular those warded in surgery departments, tended to place a higher value on technical skills, although paediatric and rehabilitation patients also placed a high value on interpersonal skills. While it has been shown that non‐surgical patients tended to prioritize interpersonal skills, our results revealed that patients warded in the surgery department who did not undergo operations still prioritized technical skills. These variation patterns among patient subgroups were further supported by regression analysis of overall patient satisfaction. In surgical patients, the 40‐ to 79‐year‐old subgroup regarded technical skills to be more important and the role of the doctor was found to be more associated with overall satisfaction. However, even among surgical patients, older patients placed higher values on interpersonal skills, and overall satisfaction was found to be more associated with health care professionals (besides doctors) and living arrangements. Conclusions We conclude that differences in patient satisfaction levels could be influenced by different perspectives on prioritized skills.     

Item Reduction of the Boston Carpal Tunnel Questionnaire Using Decision Tree Modeling

ObjectiveTo produce an electronic decision tree version of the Boston Carpal Tunnel Questionnaire (DT-BCTQ) using the chi-squared automatic interaction detection (CHAID) algorithm to reduce questionnaire length of the Boston Carpal Tunnel Questionnaire (BCTQ) while minimizing the loss of measurement properties.DesignCriterion standard study. All BCTQs completed between January 2012 and September 2016 by patients who were treated for carpal tunnel syndrome (CTS) were randomly divided into a development and a validation dataset at a 3-to-1 ratio. Optimization of the CHAID algorithm was performed in the development dataset to determine the most optimal DT-BCTQ.SettingPrivate hand clinic providing both surgical and nonsurgical (orthosis and exercise therapy) treatment for hand and wrist disorders.ParticipantsPatients with CTS (N=4470) completed a total of 10,055 BCTQs.InterventionsNot applicable.Main Outcome MeasuresThe intraclass correlation coefficient (ICC) was calculated between the original BCTQ scores and the scores predicted by the DT-BCTQ in the validation dataset. Bland-Altman plots visualized the agreement between the BCTQ and the DT-BCTQ.ResultsThe DT-BCTQ reduced the number of questions needed to ask a patient from 11 to a maximum of 3 for the symptom severity scale domain and from 8 to maximum of 3 for the functional status scale domain. The ICC between the original BCTQ and DT-BCTQ was 0.94. The mean difference between the BCTQ and DT-BCTQ was 0.05 on the 0-5 scale (95% confidence interval [CI], -0.48 to 0.57) for the symptom severity scale; 0.02 (95% CI, -0.45 to 0.49) for the functional status scale; and 0.04 (95% CI, -0.31 to 0.39) for the total BCTQ score.ConclusionBy creating the DT-BCTQ, we diminished the number of questions needed to ask a patient from 18 to a maximum of 6 questions (3 for each subscore) when administering the BCTQ while maintaining an ICC of 0.94 with the original BCTQ.     

Incorporating the sampling design in weighting adjustments for panel attrition

We review weighting adjustment methods for panel attrition and suggest approaches for incorporating design variables, such as strata, clusters, and baseline sample weights. Design information can typically be included in attrition analysis using multilevel models or decision tree methods such as the chi‐square automatic interaction detection algorithm. We use simulation to show that these weighting approaches can effectively reduce bias in the survey estimates that would occur from omitting the effect of design factors on attrition while keeping the resulted weights stable. We provide a step‐by‐step illustration on creating weighting adjustments for panel attrition in the Galveston Bay Recovery Study, a survey of residents in a community following a disaster, and provide suggestions to analysts in decision‐making about weighting approaches. Copyright © 2015 John Wiley & Sons, Ltd.