Improving medication safety and diabetes management in Hong Kong: A multidisciplinary approach

published_or_final_versio

Superscan: Superiority of xSPECT/CT over OSEM SPECT/CT in bone scans of prostate cancer patients.

Prostate cancer is one of the most common cancers affecting men. Bone scan is part of the staging modality commonly used to evaluate bone metastasis. A bone scan with diffused increased skeletal tracer uptake relative to soft tissue, combined with faint renal activity is known as a superscan. However, a primary concern are false negatives associated with bone scans, where diffuse metastasis is indistinguishable on superscans. In this study, we performed xSPECT/CT Bone and standard OSEM SPECT/CT reconstruction algorithm in ten prostate cancer patients with high PSA levels, where they initially seem relatively unremarkable on planar images. All patients with extensive bone metastases showed either relatively unremarkable scans or did not demonstrate the true extent of metastatic burden as seen on planar images. Uptake was further confirmed by the correlative diffuse bone lesions on CT images. Our reports also indicated that xSPECT/CT reconstructed images were far superior in delineating focal areas of osteoblastic bone metastasis, when compared with whole body planar images or SPECT/CT images. The extent of metastatic evidence is delineated with excellent clarification by xSPECT/CT images. We propose that whole body xSPECT/CT image reconstruction, or at least SPECT/CT, should be performed in patients with high PSA levels, along with planar imaging, to improve diagnostic accuracy of bone scans in prostate cancer staging

Trends in lipid-modifying agent use in 83 countries

Background and aims: Lipid-modifying agents (LMAs) are increasingly used to reduce lipid levels and prevent cardiovascular events but the magnitude of their consumption in different world regions is unknown. We aimed to describe recent global trends in LMA consumption and to explore the relationship between country-level LMA consumption and cholesterol concentrations. / Methods: This cross-sectional and ecological study used monthly pharmaceutical sales data from January 2008 to December 2018 for 83 countries from the IQVIA Multinational Integrated Data Analysis System and total and non-high-density lipoprotein (non-HDL) cholesterol concentrations from the NCD Risk Factor Collaboration. Compound annual growth rate (CAGR) was used to assess changes in LMA consumption over time. / Results: From 2008 to 2018, use of LMAs increased from 7,468 to 11,197 standard units per 1000 inhabitants per year (CAGR 4.13%). An estimated 173 million people used LMAs in 2018. Statins were the most used class of LMA and their market share increased in 75% of countries between 2008 and 2018. From 2013 to 2018, consumption of low-density lipoprotein lowering therapies increased (statins 3.99%; ezetimibe 4.01%; proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors 104.47%). Limited evidence supports a clear relationship between country-level changes in LMA consumption and mean total and non-HDL cholesterol concentrations in 2008 versus 2018. / Conclusions: Since 2008, global access to LMAs, especially statins, has improved. In line with international lipid guideline recommendations, recent trends indicate growth in the use of statins, ezetimibe, and PCSK9 inhibitors. Country-level patterns of LMA use and total and non-HDL cholesterol varied considerably

Risk assessment for the spread of Serratia marcescens within dental-unit waterline systems using Vermamoeba vermiformis

Vermamoeba vermiformis is associated with the biofilm ecology of dental-unit waterlines (DUWLs). This study investigated whether V. vermiformis is able to act as a vector for potentially pathogenic bacteria and so aid their dispersal within DUWL systems. Clinical dental water was initially examined for Legionella species by inoculating it onto Legionella selective-medium plates. The molecular identity/profile of the glassy colonies obtained indicated none of these isolates were Legionella species. During this work bacterial colonies were identified as a non-pigmented Serratia marcescens. As the water was from a clinical DUWL which had been treated with Alpron™ this prompted the question as to whether S. marcescens had developed resistance to the biocide. Exposure to Alpron™ indicated that this dental biocide was effective, under laboratory conditions, against S. marcescens at up to 1x108 colony forming units/millilitre (cfu/ml). V. vermiformis was cultured for eight weeks on cells of S. marcescens and Escherichia coli. Subsequent electron microscopy showed that V. vermiformis grew equally well on S. marcescens and E. coli (p = 0.0001). Failure to detect the presence of S. marcescens within the encysted amoebae suggests that V. vermiformis is unlikely to act as a vector supporting the growth of this newly isolated, nosocomial bacterium

Enzyme‐assisted aqueous extraction of Kalahari melon seed oil: optimization using response surface methodology

Enzymatic extraction of oil from Kalahari melon seeds was investigated and evaluated by response surface methodology (RSM). Two commercial protease enzyme products were used separately: Neutrase® 0.8 L and Flavourzyme® 1000 L from Novozymes (Bagsvaerd, Denmark). RSM was applied to model and optimize the reaction conditions namely concentration of enzyme (20–50 g kg−1 of seed mass), initial pH of mixture (pH 5–9), incubation temperature (40–60 °C), and incubation time (12–36 h). Well fitting models were successfully established for both enzymes: Neutrase 0.8 L (R 2 = 0.9410) and Flavourzyme 1000 L (R 2 = 0.9574) through multiple linear regressions with backward elimination. Incubation time was the most significant reaction factor on oil yield for both enzymes. The optimal conditions for Neutrase 0.8 L were: an enzyme concentration of 25 g kg−1, an initial pH of 7, a temperature at 58 °C and an incubation time of 31 h with constant shaking at 100 rpm. Centrifuging the mixture at 8,000g for 20 min separated the oil with a recovery of 68.58 ± 3.39%. The optimal conditions for Flavourzyme 1000 L were enzyme concentration of 21 g kg−1, initial pH of 6, temperature at 50 °C and incubation time of 36 h. These optimum conditions yielded a 71.55 ± 1.28% oil recovery

Predicting the Risk of Rheumatoid Arthritis and Its Age of Onset through Modelling Genetic Risk Variants with Smoking

The improved characterisation of risk factors for rheumatoid arthritis (RA) suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA). Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymorphisms (SNPs) and ever-smoking status in males to determine risk using computer simulation and confidence interval based risk categorisation. Only males were evaluated in our models incorporating smoking as ever-smoking is a significant risk factor for RA in men but not women. We developed multiple models to evaluate each risk factor's impact on prediction. Each model's ability to discriminate anti-citrullinated protein antibody (ACPA)-positive RA from controls was evaluated in two cohorts: Wellcome Trust Case Control Consortium (WTCCC: 1,516 cases; 1,647 controls); UK RA Genetics Group Consortium (UKRAGG: 2,623 cases; 1,500 controls). HLA and smoking provided strongest prediction with good discrimination evidenced by an HLA-smoking model area under the curve (AUC) value of 0.813 in both WTCCC and UKRAGG. SNPs provided minimal prediction (AUC 0.660 WTCCC/0.617 UKRAGG). Whilst high individual risks were identified, with some cases having estimated lifetime risks of 86%, only a minority overall had substantially increased odds for RA. High risks from the HLA model were associated with YORA (P<0.0001); ever-smoking associated with older onset disease. This latter finding suggests smoking's impact on RA risk manifests later in life. Our modelling demonstrates that combining risk factors provides clinically informative RA prediction; additionally HLA and smoking status can be used to predict the risk of younger and older onset RA, respectively

Fast Computing Betweenness Centrality with Virtual Nodes on Large Sparse Networks

Betweenness centrality is an essential index for analysis of complex networks. However, the calculation of betweenness centrality is quite time-consuming and the fastest known algorithm uses time and space for weighted networks, where and are the number of nodes and edges in the network, respectively. By inserting virtual nodes into the weighted edges and transforming the shortest path problem into a breadth-first search (BFS) problem, we propose an algorithm that can compute the betweenness centrality in time for integer-weighted networks, where is the average weight of edges and is the average degree in the network. Considerable time can be saved with the proposed algorithm when , indicating that it is suitable for lightly weighted large sparse networks. A similar concept of virtual node transformation can be used to calculate other shortest path based indices such as closeness centrality, graph centrality, stress centrality, and so on. Numerical simulations on various randomly generated networks reveal that it is feasible to use the proposed algorithm in large network analysis

Patient Safety in Orthopedics and Traumatology

Surgical specialties have a higher risk of errors and adverse events as represented in literature Orthopedics is one such specialty in which the clinical risk is more conspicuous and, consequently, it has a high exposure to medical-legal disputes . The aim of this work is to analyze the clinical risk and alleged malpractice in medical practice, in order to map professional risk and identify recurrent pitfalls

Prediction model and prognostic index to estimate clinically relevant pelvic organ prolapse in a general female population

Introduction and hypothesis: Estimation on prevalence and distribution of pelvic organ prolapse (POP) signs in a general female population is difficult. We therefore developed and validated