Inhaled Corticosteroids and the Risk of Lung Cancer in Chronic Obstructive Pulmonary Disease Patients: A Systematic Review and Meta-Analysis

BACKGROUND: The global prevalence of chronic obstructive pulmonary disease (COPD) is increasing, and the risk of lung cancer in these patients is high. The use of inhaled corticosteroids (ICSs) in COPD patients could help to decrease potential lung cancer risk. We planned to conduct this systematic review and meta-analysis to determine the role of ICS in the risk of lung cancer among COPD patients. METHODS: A comprehensive search of PubMed, Science Direct, Google Scholar, and Cochrane library and a manual search of the list of references were conducted. Studies with cohort, case-control, and randomized clinical trial designs for any ICS use reporting the incidence/hazard ratio (HR) of lung cancer were included. The random-effects model was used to pool hazard ratios. Subgroup analysis and metaregression analysis were employed. Funnel plot and Egger regression test were used to assess publication bias. RESULTS: Combining the results of 14 observations, the pooled HR for cancer risk reduction was 0.69 (95% CI 0.59-0.79), p value ≤ 0.001. The use of ICS in COPD patients showed a 31% reduction in the risk of lung cancer. Subgroup meta-analysis showed a significant reduction in the risk of lung cancer as well. CONCLUSION: The use of ICS in COPD patients reduces the risk of lung cancer. The risk reduction was independent of smoking status and latency period. Future studies should focus on the optimum dose and controlling confounders like asthma

Emergency logistics for wildfire suppression based on forecasted disaster evolution

This paper aims to develop a two-layer emergency logistics system with a single depot and multiple demand sites for wildfire suppression and disaster relief. For the first layer, a fire propagation model is first built using both the flame-igniting attributes of wildfires and the factors affecting wildfire propagation and patterns. Second, based on the forecasted propagation behavior, the emergency levels of fire sites in terms of demand on suppression resources are evaluated and prioritized. For the second layer, considering the prioritized fire sites, the corresponding resource allocation problem and vehicle routing problem (VRP) are investigated and addressed. The former is approached using a model that can minimize the total forest loss (from multiple sites) and suppression costs incurred accordingly. This model is constructed and solved using principles of calculus. To address the latter, a multi-objective VRP model is developed to minimize both the travel time and cost of the resource delivery vehicles. A heuristic algorithm is designed to provide the associated solutions of the VRP model. As a result, this paper provides useful insights into effective wildfire suppression by rationalizing resources regarding different fire propagation rates. The supporting models can also be generalized and tailored to tackle logistics resource optimization issues in dynamic operational environments, particularly those sharing the same feature of single supply and multiple demands in logistics planning and operations (e.g., allocation of ambulances and police forces). © 2017 The Author(s

Factors associated with low bone mass in the hemodialysis patients – a cross-sectional correlation study

<p>Abstract</p> <p>Background</p> <p>Low bone mass is common in end-stage renal disease patients, especially those undergoing hemodialysis. It can lead to serious bone health problems such as fragility fractures. The purpose of this study is to investigate the risk factors of low bone mass in the hemodialysis patients.</p> <p>Methods</p> <p>Sixty-three subjects on hemodialysis for at least 6 months were recruited from a single center for this cross-sectional study. We collected data by questionnaire survey and medical records review. All subjects underwent a bone mineral density (BMD) assay with dual-energy x-ray absorptiometry at the lumbar spine and right hip. Data were statistically analyzed by means of descriptive analysis, independent t test and one way analysis of variance for continuous variables, Pearson product-moment correlation to explore the correlated factors of BMD, and stepwise multiple linear regression to identify the predictors of low bone mass.</p> <p>Results</p> <p>Using WHO criteria as a cutoff point, fifty-one subjects (81%) had a T-score lower than -1, of them 8 subjects (13%) had osteoporosis with the femoral neck most commonly affected. Regarding risk factors, age, serum alkaline phosphatase (ALP) level, and intact parathyroid hormone (iPTH) level had significant negative correlations with the femoral neck and lumbar spine BMD. On the other hand, serum albumin level, effective exercise time, and body weight (BW) had significant positive correlations with the femoral neck and lumbar spine BMD. Age, effective exercise time, and serum albumin level significantly predicted the femoral neck BMD (R²× 0.25), whereas BW and the ALP level significantly predicted the lumbar spine BMD (R²× 0.20).</p> <p>Conclusion</p> <p>This study showed that advanced age, low BW, low serum albumin level, and high ALP and iPTH levels were associated with a low bone mass in the hemodialysis patients. We suggest that regular monitoring of the femoral neck BMD, maintaining an adequate serum albumin level and BW, and undertaking an exercise program are important to improve bone health in the patients undergoing hemodialysis.</p

Global, regional, and national burden of low back pain, 1990–2020, its attributable risk factors, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021

Background: Low back pain is highly prevalent and the main cause of years lived with disability (YLDs). We present the most up-to-date global, regional, and national data on prevalence and YLDs for low back pain from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021. Methods: Population-based studies from 1980 to 2019 identified in a systematic review, international surveys, US medical claims data, and dataset contributions by collaborators were used to estimate the prevalence and YLDs for low back pain from 1990 to 2020, for 204 countries and territories. Low back pain was defined as pain between the 12th ribs and the gluteal folds that lasted a day or more; input data using alternative definitions were adjusted in a network meta-regression analysis. Nested Bayesian meta-regression models were used to estimate prevalence and YLDs by age, sex, year, and location. Prevalence was projected to 2050 by running a regression on prevalence rates using Socio-demographic Index as a predictor, then multiplying them by projected population estimates. Findings: In 2020, low back pain affected 619 million (95% uncertainty interval 554–694) people globally, with a projection of 843 million (759–933) prevalent cases by 2050. In 2020, the global age-standardised rate of YLDs was 832 per 100 000 (578–1070). Between 1990 and 2020, age-standardised rates of prevalence and YLDs decreased by 10·4% (10·9–10·0) and 10·5% (11·1–10·0), respectively. A total of 38·8% (28·7–47·0) of YLDs were attributed to occupational factors, smoking, and high BMI. Interpretation: Low back pain remains the leading cause of YLDs globally, and in 2020, there were more than half a billion prevalent cases of low back pain worldwide. While age-standardised rates have decreased modestly over the past three decades, it is projected that globally in 2050, more than 800 million people will have low back pain. Challenges persist in obtaining primary country-level data on low back pain, and there is an urgent need for more high-quality, primary, country-level data on both prevalence and severity distributions to improve accuracy and monitor change. Funding: Bill and Melinda Gates Foundation

High-performance and stable photoelectrochemical water splitting cell with organic-photoactive-layer-based photoanode

Considering their superior charge-transfer characteristics, easy tenability of energy levels, and low production cost, organic semiconductors are ideal for photoelectrochemical (PEC) hydrogen production. However, organic-semiconductor-based photoelectrodes have not been extensively explored for PEC water-splitting because of their low stability in water. Herein, we report high-performance and stable organic-semiconductors photoanodes consisting of p-type polymers and n-type non-fullerene materials, which is passivated using nickel foils, GaIn eutectic, and layered double hydroxides as model materials. We achieve a photocurrent density of 15.1 mA cm???2 at 1.23 V vs. reversible hydrogen electrode (RHE) with an onset potential of 0.55 V vs. RHE and a record high half-cell solar-to-hydrogen conversion efficiency of 4.33% under AM 1.5 G solar simulated light. After conducting the stability test at 1.3 V vs. RHE for 10 h, 90% of the initial photocurrent density are retained, whereas the photoactive layer without passivation lost its activity within a few minutes