The Impact of the COVID-19 Pandemic on Patient Disparities in Long-Term Opioid Therapy.

BACKGROUND: The COVID-19 pandemic disrupted how primary care patients with chronic pain received care. Our study sought to understand how long-term opioid therapy (LtOT) for chronic pain changed over the course of the pandemic overall and for different demographic subgroups. METHODS: We used data from electronic health records of 64 primary care clinics across Washington state and Idaho to identify patients who had a chronic pain diagnosis and were receiving long-term opioid therapy. We defined 10-month periods in 2019 to 2021 as prepandemic, early pandemic and late pandemic and used generalized estimating equations analysis to compare across these time periods and demographic characteristics. RESULTS: We found a proportional decrease in LtOT for chronic pain in the early months of the pandemic (OR = 0.94, P = .007) followed by an increase late pandemic (OR = 1.08, P = .002). Comparing late pandemic to prepandemic, identifying as Asian or Black, having fewer comorbidities, or living in an urban area were associated with higher likelihood of being prescribed LtOT. DISCUSSION: The use of LtOT for chronic pain in primary care has increased from before to after the COVID-19 pandemic with racial/ethnic and geographic disparities. Future research is needed to understand these disparities in LtOT and their effect on patient outcomes.

Chemical speciation and environmental risk assessment of heavy metals in ash from smouldering combustion of oily sludge.

Smouldering combustion of oily sludge (OS) was carried out to learn the characteristics of heavy metals (HMs) in ash products. Ash collected from four different height layers of the column reactor was analysed for the chemical speciation and environmental risk of six HMs, including Cr, Ni, Cu, Zn, As, and Pb. The results showed that after smouldering combustion, only 21.3-32.2 % of the total HMs was remained in the ash products. The retention of HMs in ash was closely relevant to the carbonaceous destruction efficiency of OS. Smouldering combustion led to the decrease of HMs in acid-soluble/exchangeable fraction from 21.5-49.3 to 0.8-19.8% and oxidizable fraction from 22.6-49.6 to 5.3-21.3, and the increase of reducible fraction from 13.6-38.0 to 30.5-89.1% and residue fraction from 7.8-27.3 to 24.1-63.6%. Upward migration of HMs during smouldering was evidenced by their occurrence in the top clean sand layer, which was dominated in acid-soluble/exchangeable and reducible fractions, accounting for 89.7-99.1% in total. Toxicity extraction and environmental risk studies indicated that smouldering combustion would effectively reduce the toxicity and pollution risk of HMs; however, attention should be paid to the disposal of the top sand layer after smouldering operation due to its high pollution risk of HMs according to the evaluation of Risk assessment code.

TIPS: trajectory inference of pathway significance through pseudotime comparison for functional assessment of single-cell RNAseq data.

Recent advances in bioinformatics analyses have led to the development of novel tools enabling the capture and trajectory mapping of single-cell RNA sequencing (scRNAseq) data. However, there is a lack of methods to assess the contributions of biological pathways and transcription factors to an overall developmental trajectory mapped from scRNAseq data. In this manuscript, we present a simplified approach for trajectory inference of pathway significance (TIPS) that leverages existing knowledgebases of functional pathways and other gene lists to provide further mechanistic insights into a biological process. TIPS identifies key pathways which contribute to a process of interest, as well as the individual genes that best reflect these changes. TIPS also provides insight into the relative timing of pathway changes, as well as a suite of visualizations to enable simplified data interpretation of scRNAseq libraries generated using a wide range of techniques. The TIPS package can be run through either a web server or downloaded as a user-friendly GUI run in R, and may serve as a useful tool to help biologists perform deeper functional analyses and visualization of their single-cell data.