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.     

Preparing IR for COVID-19: The Singapore Experience

This paper describes country-wide special measures undertaken for interventional radiology staff during the current coronavirus disease 2019 (COVID-19) pandemic. Although each interventional radiology service around the world faces unique challenges, the principles outlined in this article will be useful when designing or strengthening individual practices and integrating them within wider hospital and national measures. Moving beyond the current outbreak, these measures will be useful for any future infectious diseases which are likely to arise.     

Utility of whole-cell repetitive extragenic palindromic sequence-based PCR (REP-PCR) for the rapid detection of nosocomial outbreaks of multidrug resistant organisms: Experience at a tertiary care center in North India

Background: There is a huge need to develop molecular typing methods which are simple to perform, rapid and cost effective to confirm clonality of nosocomial isolates in outbreak situations. Objectives: The aim of the study was to investigate a hospital outbreak of multi-drug resistant (MDR) Klebsiellapneumoniae septicemia in a paediatric surgery intensive care unit (PSICU) using a repetitive extragenic palindromic polymerase chain reaction (REP-PCR). Materials and Methods: MDR Klebsiella pneumoniae isolates from an outbreak of nosocomial sepsis were typed byREP-PCR using consensus primers. Isolates from different intensive care units (ICUs) but with similar antibiogram were also genotyped for comparison. Results and Conclusion: A cluster of twelve MDR K Pneumoniae septicemia cases was identified at the PSICU by genotyping using REP-PCR. Surveillance cultures failed to pick up any source of infection. REP-PCR was found to be a rapid and simple tool for investigation outbreaks in hospitals. Due to early detection we could initiate infection control practices with focus on hand washing and prevent the further transmission of the organism.     

Statistical analysis of gait patterns of persons with cerebral palsy

Patients at Boston's Children's Hospital diagnosed as having cerebral palsy were filmed walking. These films were digitized and translated into measurements associated with leg motion. In this paper we use the gait measurements of 128 such patients to illustrate that the kth nearest neighbour clustering procedure results in a gait typology for patients with cerebral palsy. The procedure identifies four subpopulations from the sample data; the membership of a patient within this typology is mostly determined by the patient's motor control. The developed typology differs from the present diagnostic system which classifies a cerebral palsy patient as either quadriplegic, diaplegic or hemiplegic.     

Hospital outbreak caused by a carbapenem-resistant strain of Acinetobacter baumannii: patient prognosis and risk-factors for colonisation and infection

Between October 2001 and August 2002, 30 hospital patients became infected or colonised by a multiresistant (including to carbapenems) epidemic strain of Acinetobacter baumannii (AbMR) in a hospital outbreak. This study analysed the risk-factors associated with acquisition of this epidemic strain and investigated the prognosis of patients infected by AbMR, with the aim of elucidating factors which lead to mortality. A case-control study of the acquisition of AbMR in patients infected or colonised in the hospital outbreak was performed. Independent risk-factors leading to death were studied by logistic regression analysis. Multivariate analysis of the risk-factors for colonisation/infection with AbMR revealed an independent association with the presence of an arterial catheter (OR, 1.13; 95% CI, 1.03-1.25) and administration of imipenem as monotherapy (OR, 11.12; 95% CI, 2.33-53.09). Multivariate analysis of the prognostic features leading to mortality revealed a significant association with hypotension or shock (OR, 24.63; 95% CI, 1.56-387.56) at the time of bacterial isolation.     

Clustering of autoimmune disease in parents of siblings from the Type 1 diabetes Warren repository.

AIMS: Autoimmune disorders co-exist in the same individuals and in families, implying a shared aetiology. The aim of this study was to compare the prevalence of the common autoimmune diseases in the parents of siblings from the Type 1 diabetes Warren repository with the general population. METHODS: Between 1989 and 1996, 505 British families with at least two siblings affected by Type 1 diabetes were recruited. Clinical information was collected regarding the presence of autoimmune disease in the parents and the prevalence of disease in the parents was compared with that expected in the general population. RESULTS: The prevalence of autoimmune disease in the parents was significantly higher in the repository compared with that expected in the general population [P-value = 1.98 x 10(-5) (female), P-value = 1.1 x 10(-8) (male)]. Type 1 diabetes was recorded in 63/1010 (6.2%) parents with a marked paternal preponderance (9.5 vs. 3%P = 0.002). Other autoimmune diseases affected 27% of parents with diabetes and 13.2% of parents without diabetes (P < 0.01). CONCLUSION: These data confirm the importance of family history as a significant risk factor for the development of Type 1 diabetes and support the hypothesis that the common autoimmune diseases share at least some aetiological mechanisms.     

基于实验均方误差F值的基因表达数据最佳聚类评判方法研究

目的 近年来产生了一些用于分析基因表达数据的聚类算法，却很少有关于评价聚类算法方法的研究。本研究的目的是尝试建立一个定量的评价基因表达数据聚类结果的方法。方法 本研究提供了一个系统的评价聚类结果的方法，利用我们提出的实验均方误差F值对几个常见的聚类算法进行比较。结果 利用F值对类质量的评价和利用已有的生物学知识对类进行分析的结果一致。结论 实验均方误差F值可以定量地评判用于基因表达数据的聚类算法。     

An outbreak of Pneumocystis carinii pneumonia in children with malignancy

An outbreak of Pneumocystis carinii pneumonia (PCP) in three patients within a 6 week period was reported. Two patients had acute lymphoblastic leukaemia and one had brain-stem glioma. They shared common features of immuno-suppression and absence of cotrimoxazole prophylaxis and had been nursed in the same room. The severity of PCP and its response to treatment may be related to the degree of immunosuppression. Because of the morbidity and mortality of PCP, chemoprophylaxis should be given to all at-risk cases. Furthermore, isolation of patients with PCP should be considered in view of increasing evidence of nosocomial transmission.     

山东省中小学生麻疹爆发原因的病例对照研究

为探讨山东省中小学生麻疹爆发的原因 ,采用 1∶2配比的病例对照方法对中小学生麻疹疫苗 (MV)效力进行了研究 ,同时对近年来中小学生MV接种率进行了估算。结果显示 :中小学生MV效力为 74 % ,95 %可信区间为4 7%～ 88% ;小学生MV效力明显高于中学生 ,分别为 82 %和 6 8% ;1999～ 2 0 0 1年学龄儿童的估算接种率分别为75 4 %、75 6 %和 5 5 7%。较低的MV效力和接种率是计划免疫工作薄弱地区中小学生麻疹爆发的主要原因。     

Unsupervised fuzzy clustering analysis supports behavioral cutoff criteria in an animal model of posttraumatic stress disorder.

BACKGROUND: Unsupervised fuzzy clustering (UFC) analysis is a mathematical technique that groups together objects in the multidimensional feature space according to a specified similarity measurement, thereby yielding clusters of similar data points that can be represented by a set of prototypes or centroids. METHODS: Since clinical studies of mental disorders distinguish between affected and unaffected individuals, we designed an inclusion/exclusion criteria (cutoff behavioral criteria [CBC]) approach for animal behavioral studies. The effect of classifying the study population into clearly affected versus clearly unaffected individuals according to behaviors on two behavioral paradigms was statistically significant. RESULTS: Here the raw data from previous studies were subjected to UFC algorithms as a means of objectively testing the validity of the concept of the CBC for our experimental model. The first UFC algorithm yielded two clearly discrete clusters, found to consist almost exclusively of the exposed animals in the one and unexposed animals in the other. The second algorithm yielded three clusters corresponding to animals designated as clearly affected, partially affected, and clearly unaffected. The algorithm for physiological data in addition to behavioral data failed to elicit discrete clusters. CONCLUSIONS: The UFC analysis yielded data that support the conceptual contention of the CBC and lends additional validity to our previous behavioral studies.