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.     

Prior surgical fixation of proximal humerus fractures is associated with increased complications following subsequent reverse shoulder arthroplasty

BackgroundThe objective of this study was to compare complication rates between patients undergoing reverse shoulder arthroplasty (RSA) after a prior open reduction and internal fixation (ORIF) for proximal humerus fracture (PHF) to those undergoing RSA as a primary treatment for PHFs, glenohumeral osteoarthritis, or rotator cuff tear arthropathy (CTA).MethodsPatients who underwent RSA between 2015 and 2020 were identified in the Mariner database. Patients were separated into 3 mutually exclusive groups: (1) RSA for osteoarthritis, rotator cuff tear, or CTA (Control-RSA); (2) RSA as a primary treatment for PHF (PHF-RSA); and (3) RSA for patients with prior ORIF of PHFs (ORIF-RSA). Ninety-day medical and 2-year postoperative surgical complications were identified. In addition, patients in the PHF-RSA group were subdivided into those undergoing RSA for PHF within 3 months of the fracture (acute) vs. those treated greater than 3 months from diagnosis (delayed). Multivariate regression was performed to control for differences in comorbidities and demographics.ResultsA total of 30,824 patients underwent primary RSA for arthritis or CTA, 5389 patients underwent RSA as a primary treatment for a PHF, and 361 patients underwent RSA after ORIF of a PHF. ORIF before RSA was associated with an increased risk of overall revision (odds ratio [OR] 2.45, P = .002), infection (OR 2.40, P < .001), instability (OR 2.43, P < .001), fracture (OR 3.24, P = .001), minor medical complications (OR 1.59, P = .008), and readmission (OR 2.55, P = .001) compared with the Control-RSA cohort. RSA as a primary treatment for PHF was associated with an increased risk of 2-year revision (OR 1.60, P < .001), infection (OR 1.51, P < .001), instability (OR 2.84, P < .001), and fracture (OR 2.54, P < .001) in addition to major medical complications (OR 2.02, P < .001), minor medical complications (OR 1.92, P < .001), 90-day emergency department visits (OR 1.26, P < .001) and 90-day readmission (OR 2.03, P < .001) compared with the Control-RSA cohort. The ORIF-RSA group had an increased risk of periprosthetic infection (OR 1.94, P = .002) when compared with the PHF-RSA cohort. There were no differences in medical or surgical complications in the RSA-PHF cohort between patients treated in an acute or delayed fashion.ConclusionRSA following ORIF of a PHF is associated with increased complications compared with patients undergoing RSA for nonfracture indications. Prior ORIF of a PHF is also an independent risk factor for postoperative infection after RSA compared with patients who undergo RSA as a primary operation for fracture. The timing of RSA as a primary operation for PHF does not appear to impact the rates of postoperative medical and surgical complications.     

Reference values of postural balance in preschoolers: Age and gender differences for 4–5 years old Tunisian children

BackgroundPreschool age is a critical stage of postural balance development. Posturography normative data during this age are crucial for surveillance of postural balance and for the timely diagnosis of any dysfunction. The aim of this study was to provide normative data, specific to Tunisian preschoolers, according to age and gender, and to examine gender- and age-related differences in postural balance.Research questionAre there postural balance gender- and age-related differences in Tunisian preschoolers?MethodsThe study included 410 (205 boys and 205 girls) preschool children aged between 4- and 5-year-old selected within a large geographic area of Tunisia. Postural balance was assessed using a stabilometric platform under 4 sensory conditions. The mean center of pressure velocity (CoP-V) parameter was selected for analysis. Differences between gender and age groups were analysed using the Mann–Whitney U. Normative data were expressed in percentiles.ResultsSignificant gender effect was found in conditions where sensory inputs are most challenged with a significantly smaller mean CoP-V in girls compared to boys (p < 0.05). Moreover, 5-year-old children had significantly better postural balance than 4-year-old ones in almost all conditions (p < 0.05).SignificanceThe normative data established for Tunisian preschoolers provide useful comparative data for pediatricians, teachers and coaches for the early evaluation and monitoring of postural balance during this age. Gender and age-related differences should be considered in this population.     

科研评价导向的改变对中文科技期刊的机遇与挑战

【目的】 值此《中国科技期刊研究》创刊30周年之际,思考科研评价体系的改变给中文科技期刊带来的影响,为中文期刊探寻发展路径。【方法】 结合对中文科技期刊困境的研究,提出应对策略。【结果】 近期国家陆续出台的纠偏评价导向的政策文件,为中文科技期刊既带来了发展机遇,也提出了挑战。【结论】 在重构符合中文科技期刊发展特点的评价体系的基础上,中文科技期刊应明确目标定位,面向国家需求,提升知识服务能力,建立品牌特色。     

A Perioperative Care Display for Understanding High Acuity Patients

Background  The data visualization literature asserts that the details of the optimal data display must be tailored to the specific task, the background of the user, and the characteristics of the data. The general organizing principle of a concept-oriented display is known to be useful for many tasks and data types. Objectives  In this project, we used general principles of data visualization and a co-design process to produce a clinical display tailored to a specific cognitive task, chosen from the anesthesia domain, but with clear generalizability to other clinical tasks. To support the work of the anesthesia-in-charge (AIC) our task was, for a given day, to depict the acuity level and complexity of each patient in the collection of those that will be operated on the following day. The AIC uses this information to optimally allocate anesthesia staff and providers across operating rooms. Methods  We used a co-design process to collaborate with participants who work in the AIC role. We conducted two in-depth interviews with AICs and engaged them in subsequent input on iterative design solutions. Results  Through a co-design process, we found (1) the need to carefully match the level of detail in the display to the level required by the clinical task, (2) the impedance caused by irrelevant information on the screen such as icons relevant only to other tasks, and (3) the desire for a specific but optional trajectory of increasingly detailed textual summaries. Conclusion  This study reports a real-world clinical informatics development project that engaged users as co-designers. Our process led to the user-preferred design of a single binary flag to identify the subset of patients needing further investigation, and then a trajectory of increasingly detailed, text-based abstractions for each patient that can be displayed when more information is needed.     

Quantile regression and empirical likelihood for the analysis of longitudinal data with monotone missing responses due to dropout,with applications to quality of life measurements from clinical trials

The analysis of quality of life (QoL) data can be challenging due to the skewness of responses and the presence of missing data. In this paper, we propose a new weighted quantile regression method for estimating the conditional quantiles of QoL data with responses missing at random. The proposed method makes use of the correlation information within the same subject from an auxiliary mean regression model to enhance the estimation efficiency and takes into account of missing data mechanism. The asymptotic properties of the proposed estimator have been studied and simulations are also conducted to evaluate the performance of the proposed estimator. The proposed method has also been applied to the analysis of the QoL data from a clinical trial on early breast cancer, which motivated this study.     

Genetic variation of 17 autosomal STR loci in the Lahu population from Yunnan and phylogenetic structure exploration among 28 populations

This study evaluated the genetic variation of 17 autosomal short tandem repeat (STR) loci included in the PowerPlex® 18D Kit. Samples of 562 unrelated healthy Lahu individuals living in Yunnan Province in southwestern China were investigated. The data were analyzed to provide information on allele frequencies and other statistical parameters relevant to the forensic population. Of the 17 loci, 16 reached the Hardy–Weinberg equilibrium after Bonferroni correction. A total of 176 alleles were identified in 17 STR loci, and allele frequencies ranged from 0.000 890 to 0.578 292. The combined discrimination power (CPD) and probability of excluding paternity (CPE) of the 17 STR loci were 0.999 999 999 999 999 999 489 and 0.999 998 301 753 122. The genetic relationships among 28 populations were also estimated.     

Patient-Centered Framework for Rehabilitation Research in Outpatient Settings

Conducting high-quality clinical research is dependent on merging scientific rigor with the clinical environment. This is often a complex endeavor that may include numerous barriers and competing interests. Overcoming these challenges and successfully integrating clinical research programs into clinical practice settings serving rehabilitation outpatients is beneficial from both a logistical perspective (eg, supports efficient and successful research procedures) and the establishment of a truly patient-centered research approach. Leveraging our experience with navigating this research-clinical care relationship, this article (1) proposes the Patient-Centered Framework for Rehabilitation Research, a model for integrating patient-centered research in an outpatient clinical setting that incorporates a collaborative, team-based model encompassing patient-centered values, as well as strategies for recruitment and retention, with a focus on populations living with disabilities or chronic diseases; (2) describes application of this framework in a comprehensive specialty multiple sclerosis center with both general strategies and specific examples to guide adaptation and implementation in other settings; and (3) discusses the effect of the framework as a model in 1 center, as well as the need for additional investigation and adaptation for other populations. The 5 interconnected principles incorporated in the Framework and which prioritize patient-centeredness include identifying shared values, partnering with the clinical setting, engaging with the population, building relationships with individuals, and designing accessible procedures. The Patient-Centered Framework for Rehabilitation Research is a model presented as an adaptable roadmap to guide researchers in hopes of not only improving individual patients’ experiences but also the quality and relevance of rehabilitation research as a whole. Future investigation is needed to test the Framework in other settings.     

Determinants of Regional Variation in Health Expenditures in Germany

Health care expenditure in Germany shows clear regional differences. Such geographic variations are often seen as an indicator for inefficiency. With its homogeneous health care system, low co‐payments and uniform prices, Germany is a particularly suited example to analyse regional variations. We use data for the year 2011 on expenditure, utilization of health services and state of health in Germany's statutory health insurance system. This data, which originate from a variety of administrative sources and cover about 90% of the population, are enriched with a wealth of socio‐economic variables, data on pollutants, prices and individual preferences. State of health and demography explains 55% of the differences as measured by the standard deviation while all control variables account for a total of 72% of the differences at county level. With other measures of variation, we can account for an even greater proportion. A higher proportion of variation than usually supposed can thus be explained. Whilst this study cannot quantify inefficiencies, our results contradict the thesis that regional variations reflect inefficiency. Copyright © 2015 John Wiley & Sons, Ltd.