Growth of the Social #RadOnc Network on Twitter

PurposeTwitter is an increasingly popular social media platform within the health care community. The objective of this analysis is to characterize the profile of radiation oncology–related tweets and Twitter users over the past 6 years.Methods and MaterialsUsing the web-based social media analytics platform Symplur Signals, we filtered tweets containing at least 1 of the following hashtags or key words: #radonc, #radiationoncology, "rad onc," or "radiation oncology." We evaluated radiation oncology–related Twitter activity between October 2014 and March 2020 for tweet frequency, tweet content, and individuals or groups posting tweets. We identified the most influential Twitter users contributing to radiation oncology–related tweets.ResultsFrom 2014 to 2020, the quarterly volume of radiation oncology–related tweets increased from 5027 to 29,763. Physicians contributed the largest growth in tweet volume. Academic radiation oncologists comprise 60% of the most influential Twitter accounts responsible for radiation oncology–related content. The number of radiation-oncology resident physicians on Twitter increased from 25 to 328 over the past 6 years, and 20% of radiation-oncology residency programs have a Twitter account. Seventy-one percent of radiation oncology–related tweets generated direct communication via mentions, and 59% of tweets contain links to external sources, including scientific articles.ConclusionsThe number of physicians contributing radiation oncology–related Twitter content has increased significantly in recent years. Academic radiation oncologists are the primary influencers of radiation oncology–related Twitter activity. Twitter is used by radiation oncologists to both professionally network and discuss findings related to the field. There remains the opportunity for radiation oncologists to broaden their audience on Twitter to encompass a more diverse community, including patients.     

The technological imperative in tuberculosis care and prevention in Vietnam

ABSTRACT

A monocausal bacteriological understanding of infectious disease orients tuberculosis control efforts towards antimicrobial interventions. A bias towards technological solutions can leave multistranded public health and social interventions largely neglected. In the context of globalising biomedical approaches to infectious disease control, this ethnography-inspired review article reflects upon the implementation of rapid diagnostic technology in low- and middle-income countries. Fieldwork observations in Vietnam provided a stimulus for a critical review of the global rollout of tuberculosis diagnostic technology. To address local needs in tuberculosis control, health managers in resource-poor settings are readily cooperating with international donors to deploy novel diagnostic technologies throughout national tuberculosis programme facilities. Increasing investment in new diagnostic technologies is predicated on the supposition that these interventions will ameliorate disease outcomes. However, suboptimal treatment control persists even when accurate diagnostic technologies are available, suggesting that promotion of singular technological solutions can distract from addressing systemic change, without which disease susceptibility, propagation of infection, detection gaps, diagnostic delays, and treatment shortfalls persist.     

Association Between Patient and Physician Sex and Physician-Estimated Stroke and Bleeding Risks in Atrial Fibrillation

Background

Physicians treating nonvalvular atrial fibrillation (AF) assess stroke and bleeding risks when deciding on anticoagulation. The agreement between empirical and physician-estimated risks is unclear. Furthermore, the association between patient and physician sex and anticoagulation decision-making is uncertain.

The Presence of Portal Vein Thrombosis Alters the Classic Enhancement Associated with Diagnosis of Hepatocellular Carcinoma

Digestive Diseases and Sciences - To determine whether the presence of portal vein thrombosis (PVT) where venous flow within the liver may be altered may delay the diagnosis of HCC and be...     

Isolation and characterization of fifteen microsatellite loci for the giant clam Tridacna maxima

Conservation Genetics Resources - Fifteen polymorphic microsatellite markers were developed for Tridacna maxima in order to assess self-recruitment and larval dispersal within and among MPAs in New...     

Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: A prospective study of 3,057 matched case–control sets from EPIC

Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case–control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR_1SD) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR_1SD = 0.77, 95% confidence interval 0.66–0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR_1SD = 0.72, 0.57–0.90), or lysophosphatidylcholines (OR_1SD = 0.81, 0.69–0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR_1SD = 0.77, 0.61–0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.