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.     

Pre-COVID-19 Social Determinants of Health Among Mexican Migrants in Los Angeles and New York City and Their Increased Vulnerability to Unfavorable Health Outcomes During the COVID-19 Pandemic

Journal of Immigrant and Minority Health - COVID-19 has disproportionally affected underrepresented minorities (URM) and low-income immigrants in the United States. The aim of the study is to...     

Buscando o motivo da instabilidade hemodinâmica: relato de caso sobre o papel do ultrassom intraoperatório

Background and objectives

A prompt and effective management of trauma patient is necessary. The aim of this case report is to highlight the importance of intraoperative echocardiography as a useful tool in patients suffering from refractory hemodynamic instability no otherwise explained.

The chondrocyte channelome: A narrative review

Chondrocytes are the main cells in the extracellular matrix (ECM) of articular cartilage and possess a highly differentiated phenotype that is the hallmark of the unique physiological functions of this specialised load-bearing connective tissue. The plasma membrane of articular chondrocytes contains a rich and diverse complement of membrane proteins, known as the membranome, which defines the cell surface phenotype of the cells. The membranome is a key target of pharmacological agents and is important for chondrocyte function. It includes channels, transporters, enzymes, receptors, and anchors for intracellular, cytoskeletal and ECM proteins and other macromolecular complexes. The chondrocyte channelome is a sub-compartment of the membranome and includes a complete set of ion channels and porins expressed in these cells. Many of these are multi-functional proteins with “moonlighting” roles, serving as channels, receptors and signalling components of larger molecular assemblies. The aim of this review is to summarise our current knowledge of the fundamental aspects of the chondrocyte channelome, discuss its relevance to cartilage biology and highlight its possible role in the pathogenesis of osteoarthritis (OA). Excessive and inappropriate mechanical loads, an inflammatory micro-environment, alternative splicing of channel components or accumulation of basic calcium phosphate crystals can result in an altered chondrocyte channelome impairing its function. Alterations in Ca²⁺ signalling may lead to defective synthesis of ECM macromolecules and aggravated catabolic responses in chondrocytes, which is an important and relatively unexplored aspect of the complex and poorly understood mechanism of OA development.     

Association of Early Kidney Allograft Failure with Preformed IgA Antibodies to β2-Glycoprotein I

In the current immunosuppressive therapy era, vessel thrombosis is the most common cause of early graft loss after renal transplantation. The prevalence of IgA anti–β₂-glycoprotein I antibodies (IgA-aB2GPI-ab) in patients on dialysis is elevated (>30%), and these antibodies correlate with mortality and cardiovascular morbidity. To evaluate the effect of IgA-aB2GPI-ab in patients with transplants, we followed all patients transplanted from 2000 to 2002 in the Hospital 12 de Octubre prospectively for 10 years. Presence of IgA-aB2GPI-ab in pretransplant serum was examined retrospectively. Of 269 patients, 89 patients were positive for IgA-aB2GPI-ab (33%; group 1), and the remaining patients were negative (67%; group 2). Graft loss at 6 months post-transplant was significantly higher in group 1 (10 of 89 versus 3 of 180 patients in group 2; P=0.002). The most frequent cause of graft loss was thrombosis of the vessels, which was observed only in group 1 (8 of 10 versus 0 of 3 patients in group 2; P=0.04). Multivariate analysis showed that the presence of IgA-aB2GPI-ab was an independent risk factor for early graft loss (P=0.04) and delayed graft function (P=0.04). There were no significant differences regarding patient survival between the two groups. Graft survival was similar in both groups after 6 months. In conclusion, patients with pretransplant IgA-aB2GPI-ab have a high risk of early graft loss caused by thrombosis and a high risk of delayed graft function. Therefore, pretransplant IgA-aB2GPI-ab may have a detrimental effect on early clinical outcomes after renal transplantation.