Oseltamivir induced sinus bradycardia: an area of potential concern

Oseltamivir was approved for the prevention and treatment of influenza in 1999 by the USFDA (US Food and Drug Administration). The use of Oseltamivir is increasing rapidly all over the world, especially after the 2009 “Swine Flu” pandemic. Less data is published as far as the cardiovascular side effects of Oseltamivir are concerned, but it could be associated with some serious cardiovascular side effects. This study presented a case series of 5 cases suspected to be suffering from seasonal influenza H1N1 (“Swine Flu”), who developed sinus bradycardia while they were on Oseltamivir therapy

Analysis of drug related electrolyte disturbances in emergency medicine department

Background: Electrolytes play an important role in various physiological functions of the body. Electrolyte disturbances are one of the most common problems encountered in critically ill patients. Drugs are also known to cause adverse electrolyte consequences. These drugs could be anti-hypertensive agents, hormones, antipsychotics or steroids. There is paucity of published literature on electrolyte disturbances caused by drugs. The purpose of our study was to evaluate the electrolyte disturbances caused by various drugs in critically ill patients.Methods: Following approval of the Institutional Ethics Committee, data collection was started. Adverse Drug Reactions (ADRs) presenting as an electrolyte disturbance in emergency medicine department or occurring in hospitalized patients in the Intensive care unit (ICU) of our hospital was be collected. ADRs resulting into electrolyte disturbances were identified and analysed in detail for demographic details, types of electrolyte disturbances, seriousness, severity, causality and preventability of ADRs. Fisher's exact test was done to find out the statistical difference between the electrolyte disturbances and different drugs.Results: Total 58 ADRs were reported as an electrolyte disturbance. Mean age of the patients affected was 52.48 years. Highest number of ADRs were observed in the age group of 61 to 70 years. Hypokalemia constituted 32 cases (55.2%) followed by hyponatremia (25.9%), hyperkalemia (6.9%), hypernatremia (6.9%), hypocalcemia (1.7%), hypomagnesemia (1.7%) and hypophosphatemia (1.7%). Insulin was associated with maximum cases of ADRs (27.6%).Conclusions: Electrolyte disturbances constitutes a major chunk of ADRs especially in critically ill patients. The physicians must be well-versed with the dynamics of fluid-electrolyte balance

Evaluation of Current Technologies for Training, Web Apps, and New Technologies

This report details the activities conducted to assess the feasibility of using new technology tools for safety training. Utilizing established research studies, risk frameworks, and vendor quotations, we compared the different attributes of training methods such as Traditional Training (classroom/presentations), LMS (Learning Management System) based gamification, Computer Simulation, Virtual Reality (VR), and Augmented Reality (AR). The anticipated benefits include improved training program development, higher interactivity and long-term retention, and the chance to reduce work zone risk. The project was divided in three phases, and the following are our four key takeaways. (1) Quality of Safety Training: Benchmarking training practices provided strong evidence that participative programs, such as role plays, demonstrations of safety devices, and risk mapping are some of the best practices. Additionally, training engineers on work zone design, auditing, and recording safe work zones can influence project attributes, such as the length and duration of work zone. Including all these aspects during the project planning phase has a greater chance of influencing work zone safety. (2) Effectiveness of New Technology Tools: Our vendor outreach project phase allowed us to determine the different attributes in training course development and customer experience using new technology tools. Established research studies provided significant support to our hypothesis that new technology tools are more effective and interactive compared to traditional learning. (3) Risk-Based Approach to Training: Analyzing the risk index for work zone attributes indicate the degree of risk that a worker faces while performing a task characterizing those attributes. We concluded that implementation of new technology tools should be planned based on this risk index and optimization model. This will ensure better worker performance and perception of the course content in alignment with the severity of that work attribute. (4) Optimizing Selection of Training Tools for Tasks: We provide an optimization model to choose the optimal mix of training tools to attain the desired level of risk reduction. The tool is spreadsheet-based and shows the benefit of using a portfolio of modules across training tools, each targeted at attaining the desired risk reduction by attribute for a task. By using the risk reduction due to training tools from the literature, the cost data from vendors and task characteristics, this tool can enable INDOT managers to manage risk cost efficiently

A molecular quantitative trait locus map for osteoarthritis

Funder: Medical Research Council Centre for Integrated Research into Musculoskeletal Ageing grant (148985)Funder: Versus Arthritis; Tissue Engineering and Regenerative Therapies Centre (21156)Abstract: Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis

A molecular quantitative trait locus map for osteoarthritis

Funder: Medical Research Council Centre for Integrated Research into Musculoskeletal Ageing grant (148985)Funder: Versus Arthritis; Tissue Engineering and Regenerative Therapies Centre (21156)Abstract: Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis

A molecular quantitative trait locus map for osteoarthritis

Funder: Medical Research Council Centre for Integrated Research into Musculoskeletal Ageing grant (148985)Funder: Versus Arthritis; Tissue Engineering and Regenerative Therapies Centre (21156)Abstract: Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study.

BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.Cambridge work was funded by a CRUK programme grant awarded to DEN; Swedish work and tissue collections were funded by grants from the Linne Centre for Breast and Prostate Cancer (CRISP, grant 70867901), Karolinska Institutet, the Swedish Research Council (K2010-70X-20430-04-3), and the Swedish Cancer Society (11-0287).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ebiom.2015.07.01

Integration of copy number and transcriptomics provides risk stratification in prostate cancer : a discovery and validation cohort study

Study data are deposited in NCBI GEO (unique identifier number GSE70770).Background : Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods : In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. Findings : We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer ( MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation : For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.Publisher PDFPeer reviewe