MATERIALS AND METHODS: A search of relevant literature from 2014 to 2016 concerning targeted therapies in RA was conducted. The RA Update Working Group evaluated the evidence and proposed updated recommendations using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach, to describe the quality of evidence and strength of recommendations. Recommendations were finalized through consensus using the Delphi technique.
RESULTS: This update provides 16 RA treatment recommendations based on current best evidence and expert clinical opinion. Recommendations 1-3 deal with the use of conventional synthetic disease-modifying antirheumatic drugs. The next three recommendations (4-6) cover the need for screening and management of infections and comorbid conditions prior to starting targeted therapy, while the following seven recommendations focus on use of these agents. We address choice of targeted therapy, switch, tapering and discontinuation. The last three recommendations elaborate on targeted therapy for RA in special situations such as pregnancy, cancer, and major surgery.
CONCLUSION: Rheumatoid arthritis remains a significant health problem in the Asia-Pacific region. Patients with RA can benefit from the availability of effective targeted therapies, and these updated recommendations provide clinicians with guidance on their use.
OBJECTIVES: In this paper, the Advanced Human-Robot Collaboration Model (AHRCM) approach is to enhance the risk assessment and to make the workplace involving security robots. The robots use perception cameras and generate scene diagrams for semantic depictions of their environment. Furthermore, Artificial Intelligence (AI) and Information and Communication Technology (ICT) have utilized to develop a highly protected security robot based risk management system in the workplace.
RESULTS: The experimental results show that the proposed AHRCM method achieves high performance in human-robot mutual adaption and reduce the risk.
CONCLUSION: Through an experiment in the field of human subjects, demonstrated that policies based on the proposed model improved the efficiency of the human-robot team significantly compared with policies assuming complete human-robot adaptation.
METHODS: A prospective pre- and post-intervention study was conducted among medical inpatients in a Malaysian secondary care hospital. DVT and bleeding risks were stratified using validated Padua Risk Assessment Model (RAM) and International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) Bleeding Risk Assessment Model. Pharmacist-driven DRAT was developed and implemented post-interventional phase. DVT prophylaxis use was determined and its appropriateness was compared between pre and post study using multivariate logistic regression with IBM SPSS software version 21.0.
RESULTS: Overall, 286 patients (n=142 pre-intervention versus n=144 post-intervention) were conveniently recruited. The prevalence of DVT prophylaxis use was 10.8%. Appropriate thromboprophylaxis prescribing increased from 64.8% to 68.1% post-DRAT implementation. Of note, among high DVT risk patients, DRAT intervention was observed to be a significant predictor of appropriate thromboprophylaxis use (14.3% versus 31.3%; adjusted odds ratio=2.80; 95% CI 1.01 to 7.80; p<0.05).
CONCLUSION: The appropriateness of DVT prophylaxis use was suboptimal but doubled after implementation of DRAT intervention. Thus, an integrated risk stratification checklist is an effective approach for the improvement of rational DVT prophylaxis use.