Respiratory viral pathogens among Singapore military servicemen 2009 - 2012: Epidemiology and clinical characteristics

10.1186/1471-2334-14-204BMC Infectious Diseases141-BIDM

A cost-effectiveness analysis evaluating endoscopic surveillance for gastric cancer for populations with low to intermediate risk

10.1371/journal.pone.0083959PLoS ONE812-POLN

Global delivery models: the role of talent, speed and time zones in the global outsourcing industry

Global delivery models (GDMs) are transforming the global IT and business process outsourcing industry. GDMs are a new form of client-specific investment promoting service integration with clients by combining client proximity with time-zone spread for 24/7 service operations. We investigate antecedents and contingencies of setting up GDM structures. Based on comprehensive data we show that providers are likely to establish GDM location configurations when clients value access to globally distributed talent and speed of service delivery, in particular when services are highly commoditized. Findings imply that coordination across time zones increasingly affects international operations in business-to-business and born-global industries

Mechanisms and models of somatic cell reprogramming

Whitehead Institute for Biomedical Research (Jerome and Florence Brill Graduate Student Fellowship)National Institutes of Health (U.S.) (US NIH grant RO1-CA087869)National Institutes of Health (U.S.) (US NIH grant R37-CA084198)National Science Foundation (U.S.) (NSF Graduate Research Fellowship)National Institutes of Health (U.S.) ((NIH) Kirschstein National Research Service Award,1 F32 GM099153-01A1)Vertex Pharmaceuticals Incorporated (Vertex Scholar

Business ethics and finance in Greater China:Synthesis and future directions in sustainability, CSR, and fraud

Following the financial crisis and recent recession, the center of gravity of global economic growth and competitiveness is shifting toward emerging economies. As a leading and increasingly influential emerging economy, China is currently attracting the attention of academics, practitioners, and policy makers. There is a rise of research interest in and publications on issues relating to China within high-quality international academic journals. We therefore organized a special issue conference in conjunction with the Journal of Business Ethics (JBE) in Lhasa, Tibet, on May 19-20, 2014, on the topic of Business Ethics in Greater China: Past, Present and Future. The papers for the special issue were at the intersection of ethics and finance, and fit within one of three themes: environment and sustainability, corporate social responsibility, and fraud. Within these themes, issues of intellectual capital protection, gender equality, political connections, regional development, investor protection, corporate stewardship, trust and corruption, and corporate transparency each play a significant role. In this paper, we survey these studies and the related literature to provide a comprehensive coverage of business ethics and finance issues that affect China

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Risk factors for severe hand foot mouth disease in Singapore: a case control study

BACKGROUND: Hand foot mouth disease (HFMD) is a common childhood infection that can potentially lead to serious complications. The aim of this study is to identify risk factors of acquiring severe HFMD in our population. METHODS: We performed a case control study using patients admitted to our hospital from August 2004 to July 2014. Cases were patients with severe HFMD disease while controls were age-matched patients obtained from the same year, in a 2:1 ratio. Data comprising demographic characteristics, clinical symptoms and signs, and lab findings were collected. Conditional univariable logistic regression was performed to determine risk factors for severe disease. RESULTS: A total of 24 cases of severe HFMD were identified and matched with 48 controls. Seventeen (70.8 %) cases had central nervous system complications. Seven (29.2 %) had cardiovascular complications without evidence of myocarditis. One patient died of encephalitis. The overall mortality of severe disease is 4 %. Evidence of hypoperfusion, seizure, altered mentation, meningeal irritation, tachycardia, tachypnea, raised absolute neutrophil count and EV-A71 (Enterovirus A71) positivity were significantly associated with a severe course of HFMD. CONCLUSION: In managing children with HFMD, physicians should consider these factors to help identify patients at risk for severe disease

Longitudinal seroepidemiologic study of the 2009 pandemic influenza A (H1N1) infection among health care workers in a children's hospital

<p>Abstract</p> <p>Background</p> <p>To probe seroepidemiology of the 2009 pandemic influenza A (H1N1) among health care workers (HCWs) in a children's hospital.</p> <p>Methods</p> <p>From August 2009 to March 2010, serum samples were drawn from 150 HCWs in a children's hospital in Taipei before the 2009 influenza A (H1N1) pandemic, before H1N1 vaccination, and after the pandemic. HCWs who had come into direct contact with 2009 influenza A (H1N1) patients or their clinical respiratory samples during their daily work were designated as a high-risk group. Antibody levels were determined by hemagglutination inhibition (HAI) assay. A four-fold or greater increase in HAI titers between any successive paired sera was defined as seroconversion, and factors associated with seroconversion were analyzed.</p> <p>Results</p> <p>Among the 150 HCWs, 18 (12.0%) showed either virological or serological evidence of 2009 pandemic influenza A (H1N1) infection. Of the 90 unvaccinated HCWs, baseline and post-pandemic seroprotective rates were 5.6% and 20.0%. Seroconversion rates among unvaccinated HCWs were 14.4% (13/90), 22.5% (9/40), and 8.0% (4/50) for total, high-risk group, and low-risk group, respectively. Multivariate analysis revealed being in the high-risk group is an independent risk factor associated with seroconversion.</p> <p>Conclusion</p> <p>The infection rate of 2009 pandemic influenza A (H1N1) in HCWs was moderate and not higher than that for the general population. The majority of unvaccinated HCWs remained susceptible. Direct contact of influenza patients and their respiratory samples increased the risk of infection.</p

Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective

Background: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. Methods: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning. Results: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10–12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63–0.83. Conclusion: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology