Mortality from opioid abuse has risen dramatically in the United States over the last two decades and has become a national health crisis. Bernstein and Chisesi explore whether revised pain management standards for hospitals contributed to this epidemic.
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Maternal mortality rates in the United States correlated with social determinants of health
This article helps in understanding the effect of various social determinants on maternal mortality in the United States. It explains the relationship between maternal mortality rates and factors like race, income, education, and health insurance access.
Read More...The relationship between income inequality and maternal mortality for black and white mothers
In this study, the authors measure the relationship between the Gini coefficient, a common measure of income inequality, and Black and White maternal mortality rates by state and year.
Read More...The effect of microplastics on the speed, mortality rate, and swimming patterns of Daphnia Magna
In this study, the authors investigate the effects that microplastics (which pollute fresh and saltwater ecosystems) have on plankton species Daphnia Magna by measuring their movement and viability.
Read More...Differences in the effect of copper sulfate on the mortality rate of Ostracod and Daphnia
Chemical pollution can have significant effects on freshwater organisms. In this study, the effect of copper sulfate on the survival of Daphnia pulex and Ostracoda was investigated.
Read More...Survival analysis in cardiovascular epidemiology: nexus between heart disease and mortality
In 2021, over 20 million people died from cardiovascular diseases, highlighting the need for a deeper understanding of factors influencing heart failure outcomes. This study examined multiple variables affecting mortality after heart failure, using random forest models to identify time, serum creatinine, and ejection fraction as key predictors. These findings could contribute to personalized medicine, improving survival rates by tailoring treatment strategies for heart failure patients.
Read More...Development and Implementation of Enzymatic and Volatile Compound-based Approaches for Instantaneous Detection of Pathogenic Staphylococcus aureus
Staphylococcus aureus (S. aureus) has a mortality rate of up to 30% in developing countries. The purpose of this experiment was to determine if enzymatic and volatile compound-based approaches would perform more quickly in comparison to existing S. aureus diagnostic methods and to evaluate these novel methods on accuracy. Ultimately, this device provided results in less than 30 seconds, which is much quicker than existing methods that take anywhere from 10 minutes to 48 hours based on approach. Statistical analysis of accuracy provides preliminary confirmation that the device based on enzymatic and volatile compound-based approaches can be an accurate and time-efficient tool to detect pathogenic S. aureus.
Read More...The Effect of Neem on Common Nosocomial Infection-Causing Organisms
Nosocomial infections acquired in hospitals pose a risk to patients, a risk compounded by resistant microorganisms. To combat this problem, researchers have turned to bioactive compounds from medicinal plants such as the widely used neem. In the present study, researchers sought to determine the effectiveness of different neem preparations against several hospital acquired human pathogens. Neem powder in water successfully inhibited microorganism growth making it a potential agent to combat these infections.
Read More...The correlation between bacteria and colorectal cancer
The authors looked at abundance of bacteria in stool samples from patients with colorectal cancer compared to controls. They found different bacteria that was more prevalent in patients with colorectal cancer as well as bacteria in control patients that may indicate a beneficial gut microbiome.
Read More...Determining the best convolutional neural network for identifying tuberculosis and pneumonia in chest x-rays
To best identify tuberculosis and pneumonia diagnoses in chest x-rays, the authors compare different deep learning convolution neural networks.
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