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    Community: From an Ecological Stoichiometry Perspective

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    Development of an evidence evaluation and synthesis system for drug-drug interactions, and its application to a systematic review of HIV and malaria co-infection

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    In all settings, there are challenges associated with safely treating patients with multimorbidity and polypharmacy. The need to characterise, understand and limit harms resulting from medication use is therefore increasingly important. Drug-drug interactions (DDIs) are prevalent in patients taking antiretrovirals (ARVs) and if unmanaged, may pose considerable risk to treatment outcome. One of the biggest challenges in preventing DDIs is the substantial gap between theory and clinical practice. There are no robust methods published for formally assessing quality of evidence relating to DDIs, despite the diverse sources of information. We defined a transparent, structured process for developing evidence quality summaries in order to guide therapeutic decision making. This was applied to a systematic review of DDI data with considerable public health significance: HIV and malaria.This was a systematic review of DDI data between antiretrovirals and drugs used in prophylaxis and treatment of malaria. The data comprised all original research in humans that evaluated pharmacokinetic data and/or related adverse events when antiretroviral agents were combined with antimalarial agents, including healthy volunteers, patients with HIV and/or malaria, observational studies, and case reports. The data synthesis included 36 articles and conference presentations published via PubMed and conference websites/abstract books between 1987-August 2016. There is significant risk of DDIs between HIV protease inhibitors, or NNRTIs and artemesinin-containing antimalarial regimens. For many antiretrovirals, DDI studies with antimalarials were lacking, and the majority were of moderate to very low quality. Quality of evidence and strength of recommendation categories were defined and developed specifically for recommendations concerning DDIs.There is significant potential for DDIs between antiretrovirals and antimalarials. The application of quality of evidence and strength of recommendation criteria to DDI data is feasible, and allows the assessment of DDIs to be robust, consistent, transparent and evidence-based

    Does Tai Chi relieve fatigue? A systematic review and meta-analysis of randomized controlled trials

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    Fatigue is not only a familiar symptom in our daily lives, but also a common ailment that affects all of our bodily systems. Several randomized controlled trials (RCTs) have proven Tai Chi to be beneficial for patients suffering from fatigue, however conclusive evidence is still lacking. A systematic review and meta-analysis was performed on all RCTs reporting the effects of Tai Chi for fatigue.In the end of April 2016, seven electronic databases were searched for RCTs involving Tai Chi for fatigue. The search terms mainly included Tai Chi, Tai-ji, Taiji, fatigue, tiredness, weary, weak, and the search was conducted without language restrictions. Methodological quality was assessed using the Cochrane Risk of Bias tool. RevMan 5.3 software was used for meta-analysis. Publication bias was estimated with a funnel plot and Egger’s test. We also assessed the quality of evidence with the GRADE system.Ten trials (n = 689) were included, and there was a high risk of bias in the blinding. Two trials were determined to have had low methodological quality. Tai Chi was found to have improved fatigue more than conventional therapy (standardized mean difference (SMD): -0.45, 95% confidence interval (CI): -0.70, -0.20) overall, and have positive effects in cancer-related fatigue (SMD:-0.38, 95% CI: -0.65, -0.11). Tai Chi was also more effective on vitality (SMD: 0.63, 95% CI: 0.20, 1.07), sleep (SMD: -0.32, 95% CI: -0.61, -0.04) and depression (SMD: -0.58, 95% CI: -1.04, -0.11). However, no significant difference was found in multiple sclerosis-related fatigue (SMD: -0.77, 95% CI: -1.76, 0.22) and age-related fatigue (SMD: -0.77, 95% CI: -1.78, 0.24). No adverse events were reported among the included studies. The quality of evidence was moderate in the GRADE system.The results suggest that Tai Chi could be an effective alternative and /or complementary approach to existing therapies for people with fatigue. However, the quality of the evidence was only moderate and may have the potential for bias. There is still absence of adverse events data to evaluate the safety of Tai Chi. Further multi-center RCTs with large sample sizes and high methodological quality, especially carefully blinded design, should be conducted in future research.PROSPERO CRD4201603306

    Incidence, risk, and associated factors of depression in adults with physical and sensory disabilities: A nationwide population-based study

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    Physical disability has been associated with the risk of depression. We examined the incidence, risk, and associated factors of depression in Taiwanese adults with physical/sensory disabilities.Two national databases were used to retrospectively analyze 749,491 ≥20-year-old Taiwanese with physical/sensory disabilities in 2002–2008. The incidence of depression was analyzed by univariate Poisson regression. Risk factors of depression were followed up through 2014 and examined with a Cox proportional hazards model.Among the study subjects, the incidence of depression was 6.29 per 1000 person-years, with 1.83 per 1000 person-years corresponding to major depression. The subjects’ depression risk was affected by disability type, disability severity, gender, age, education, marital status, aboriginal status, monthly salary, residence urbanization level, and Charlson comorbidity index (CCI). Subjects with rare diseases, mild disability, female gender, age 35–44 years, a high school education level, divorced/widowed status, non-aboriginal status, a NT$22,801–28,800 monthly salary, a highly urbanized residence area, or a CCI≥3 were at higher risk for depression.Adults with physical/sensory disabilities have a 3.7-fold higher incidence of depression than the general population. Social services departments and family members should take extra measures toward preventing and treating depression in this subpopulation

    Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation

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    Genetic determinants of drug response remain stable throughout life and offer great promise to patient-tailored drug therapy. The adoption of pharmacogenetic (PGx) testing in patient care requires accurate, cost effective and rapid genotyping with clear guidance on the use of the results. Hence, we evaluated a 32 SNPs panel for implementing PGx testing in clinical laboratories.We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants were selected using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB) and include polymorphisms of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 genes. The CYP2D6 gene allele quantification was determined simultaneously with TaqMan copy number assays targeting intron 2 and exon 9 regions. The genotyping results showed high call rate accuracy according to concordance with genotypes identified by independent analyses on Sequenome massarray and droplet digital PCR. Furthermore, 506 genomic samples across three major ethnic groups of Singapore (Malay, Indian and Chinese) were analysed on our workflow.We found that 98% of our study subjects carry one or more CPIC actionable variants. The major alleles detected include CYP2C9*3, CYP2C19*2, CYP2D6*10, CYP2D6*36, CYP2D6*41, CYP3A5*3 and VKORC1*2. These translate into a high percentage of intermediate (IM) and poor metabolizer (PM) phenotypes for these genes in our population.Genotyping may be useful to identify patients who are prone to drug toxicity with standard doses of drug therapy in our population. The simplicity and robustness of this PGx panel is highly suitable for use in a clinical laboratory

    Efficiency and optimal size of hospitals: Results of a systematic search

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    National Health Systems managers have been subject in recent years to considerable pressure to increase concentration and allow mergers. This pressure has been justified by a belief that larger hospitals lead to lower average costs and better clinical outcomes through the exploitation of economies of scale. In this context, the opportunity to measure scale efficiency is crucial to address the question of optimal productive size and to manage a fair allocation of resources.This paper analyses the stance of existing research on scale efficiency and optimal size of the hospital sector. We performed a systematic search of 45 past years (1969–2014) of research published in peer-reviewed scientific journals recorded by the Social Sciences Citation Index concerning this topic. We classified articles by the journal’s category, research topic, hospital setting, method and primary data analysis technique. Results showed that most of the studies were focussed on the analysis of technical and scale efficiency or on input / output ratio using Data Envelopment Analysis. We also find increasing interest concerning the effect of possible changes in hospital size on quality of care.Studies analysed in this review showed that economies of scale are present for merging hospitals. Results supported the current policy of expanding larger hospitals and restructuring/closing smaller hospitals. In terms of beds, studies reported consistent evidence of economies of scale for hospitals with 200–300 beds. Diseconomies of scale can be expected to occur below 200 beds and above 600 beds

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