Assessing the Impact of Salt Reduction Initiatives on the Chronic Disease Burden of Singapore

Globally, many countries are facing an increasing burden of chronic disease due to ageing populations, of which cardiovascular disease forms a large proportion. Excess dietary sodium contributes to cardiovascular disease risk and requires intervention at a population level. This study aimed to quantify the impact of several salt reduction initiatives on population health over a 30-year horizon using GeoDEMOS, a population model from Singapore. Four interventions were modelled in four demographic groups in 2020 for a total of 16 intervention scenarios. The effect of 0.5, 2.0, and 4.0 g/day reductions in daily salt consumption, along with adherence to the World Health Organization guidelines of a maximum of 5.0 g of salt each day, was modelled in the entire population, including the overweight and obese, the elderly, and diabetics. In each scenario, the number of averted incident cases of acute myocardial infarction and stroke, along with the disability-adjusted life years up to 2050, was monitored. We found 4.0 g/day reductions in salt consumption were the most effective when implemented across the entire population, resulting in 24,000 averted incident cases of cardiovascular disease and 215,000 disability-adjusted life years over 30 years. This is a large figure when compared with the 29,200 projected annual incident cases of cardiovascular disease in 2050. When targeted at specific high-risk demographic groups, the largest effects were observed in the overweight and obese, with the same intervention yielding 10,500 averted incident cases of cardiovascular disease and 91,500 disability-adjusted life years. Quantifying the benefits of salt reduction initiatives revealed a significant impact when administered across the entire population or the overweight and obese. Health promotion efforts directed toward sustainably reducing salt consumption will help to lower the chronic disease burden on the healthcare system in years to come.     

Association of Opioid Use Disorder With 2016 Presidential Voting Patterns: Cross-sectional Study in New York State at Census Tract Level

BackgroundOpioid overdose-related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP) and opioid use disorder (OUD).ObjectiveWe aimed to discover geospatial patterns in nonmedical opioid use and its correlations with demographic features related to despair and economic hardship, most notably the US presidential voting patterns in 2016 at census tract level in New York State.MethodsThis cross-sectional analysis used data from New York Statewide Planning and Research Cooperative System claims data and the presidential voting results of 2016 in New York State from the Harvard Election Data Archive. We included 63,958 patients who had at least one OUD diagnosis between 2010 and 2016 and 36,004 patients with at least one OP diagnosis between 2012 and 2016. Geospatial mappings were created to compare areas of New York in OUD rates and presidential voting patterns. A multiple regression model examines the extent that certain factors explain OUD rate variation.ResultsSeveral areas shared similar patterns of OUD rates and Republican vote: census tracts in western New York, central New York, and Suffolk County. The correlation between OUD rates and the Republican vote was .38 (P<.001). The regression model with census tract level of demographic and socioeconomic factors explains 30% of the variance in OUD rates, with disability and Republican vote as the most significant predictors.ConclusionsAt the census tract level, OUD rates were positively correlated with Republican support in the 2016 presidential election, disability, unemployment, and unmarried status. Socioeconomic and demographic despair-related features explain a large portion of the association between the Republican vote and OUD. Together, these findings underscore the importance of socioeconomic interventions in combating the opioid epidemic.     

Machine Learning Algorithms to Predict Mortality and Allocate Palliative Care for Older Patients With Hip Fracture

ObjectivesTo evaluate a machine learning model designed to predict mortality for Medicare beneficiaries aged >65 years treated for hip fracture in Inpatient Rehabilitation Facilities (IRFs).DesignRetrospective design/cohort analysis of Centers for Medicare & Medicaid Services Inpatient Rehabilitation Facility–Patient Assessment Instrument data.Setting and ParticipantsA total of 17,140 persons admitted to Medicare-certified IRFs in 2015 following hospitalization for hip fracture.MeasuresPatient characteristics include sociodemographic (age, gender, race, and social support) and clinical factors (functional status at admission, chronic conditions) and IRF length of stay. Outcomes were 30-day and 1-year all-cause mortality. We trained and evaluated 2 classification models, logistic regression and a multilayer perceptron (MLP), to predict the probability of 30-day and 1-year mortality and evaluated the calibration, discrimination, and precision of the models.ResultsFor 30-day mortality, MLP performed well [acc = 0.74, area under the receiver operating characteristic curve (AUROC) = 0.76, avg prec = 0.10, slope = 1.14] as did logistic regression (acc = 0.78, AUROC = 0.76, avg prec = 0.09, slope = 1.20). For 1-year mortality, the performances were similar for both MLP (acc = 0.68, AUROC = 0.75, avg prec = 0.32, slope = 0.96) and logistic regression (acc = 0.68, AUROC = 0.75, avg prec = 0.32, slope = 0.95).Conclusion and ImplicationsA scoring system based on logistic regression may be more feasible to run in current electronic medical records. But MLP models may reduce cognitive burden and increase ability to calibrate to local data, yielding clinical specificity in mortality prediction so that palliative care resources may be allocated more effectively.     

Is Mandatory Vaccination for COVID-19 Constitutional under Brazilian Law?

Mandatory vaccination for COVID-19 has been the object of heated debate in Brazil. This article discusses the legality and constitutionality of such a policy. First, it analyzes the laws, regulations, and Supreme Court decisions that provide for the possibility of mandatory COVID-19 vaccination. Subsequently, it analyzes the constitutionality of a mandatory vaccination policy through the proportionality method to address the conflict between, on one side, the right to individual autonomy, which includes the right to refuse a medical intervention, and, on the other, health policies that interfere with individual autonomy to protect the rights to life and health. The application of this method allows for the identification of key questions that need to be answered to determine the constitutionality of a mandatory vaccination program. These questions cannot be answered a priori and in the abstract because they depend on the concrete circumstances of the pandemic, on the characteristics of the vaccine(s) against COVID-19, and on how a mandatory vaccination policy might be designed and implemented by authorities.     

骨骼形态计算机测量和经典方法的比较

目的减少下颌骨形态测量的偶然性误差,提高测量精度.方法对比经典方法与计算机自动读取下颌骨各个测量点的测量精度和重复性.结果测量精度和重复性大为提高,用经典方法测量最大值为5格,标准差的最大值为1.4,而计算机测量分别为1.0和0.3,经t检验其P值分别为1.008×10-9和1.960×10-10,均小于0.01.结论用计算机测量下颌骨形态其精度和重复性均优于经典方法.     

Study of the mechanism of essential garlic oil inhibiting lnterleukin-1 α-induced monocyte adhesion to endothelial cells

Objective  

To observe the effects of essential garlic oil (EGO) on vascular cell adhesive molecule-1 (VCAM-1) expression of endothelial cells and monocyte-endothelial cell adhesion rate induced by interleukin-l_α(IL-l_α).     

口腔修复科进修医师接诊前培训探析

为了提高进修医师的教学质量和医疗水平,我们在2006届进修医师教学工作中加强和细化了进修医师接诊前的培训,取得了良好的效果.实践证明,实施接诊前培训对于提高进修医师的医疗水平和自信心,实施规范化操作,克服诊疗中的盲目性,减少或避免医疗纠纷,进而提高进修医师的教学质量具有重要意义,值得推广和借签.