The Effect of Chronic Sleep Deprivation on Tumor Necrosis Factor Alpha and Bone Health in Peri-Menopausal Rats

Post-menopausal osteoporosis is a common syndrome in the United States. The cessation of estrogen signaling coupled with the production of pro-inflammatory cytokines from sleep deprivation leads to an even greater risk of post-menopausal osteoporosis by creating an imbalance between osteoblasts and osteoclasts. With estrogen no longer present to regulate the concentration of osteoclasts and pro-inflammatory cytokines increasing production of osteoclasts, bone is degraded at a faster rate than it is formed. One of the most common treatments for osteoporosis is Zolendronate (a nitrogenous bisphosphonate), which decreases the number of osteoclasts in bone. This preliminary study looked at the effects on the concentration of tumor necrosis factor alpha-type (TNFα), a pro-inflammatory cytokine, and bone strength due to Zolendronate and sleep deprivation in thirty-two ovariectomized Wistar rats. After a five-week sleep deprivation protocol, TNFα concentrations were determined by enzyme-linked immunoassay and bone strengths were determined by a three point bending test. There were no significant differences in bone strength, and the only significant difference in serum concentrations of TNFα (P\u3c.01) was with the group that received Zolendronate. While we expected that the sleep deprived and sleep deprived with Zolendronate groups would have significantly higher TNFα concentrations we purpose an over-exhausted immune system is responsible our low concentrations. The reason the Zolendronate group had a significantly higher TNFα level could have been due to a transient fever caused by the drug. Further research measuring the changes in cytokine concentration throughout a longer sleep deprivation protocol needs to be done

Trends in Opioid Use in Pediatric Patients in US Emergency Departments From 2006 to 2015

Importance The use of opioids to treat pain in pediatric patients has been viewed as necessary; however, this practice has raised concerns regarding opioid abuse and the effects of opioid use. To effectively adjust policy regarding opioids in the pediatric population, prescribing patterns must be better understood. Objective To evaluate opioid prescribing patterns in US pediatric patients and factors associated with opioid prescribing. Design, Setting, and Participants This cross-sectional study used publicly available data from the National Hospital Ambulatory Medical Care Survey from January 1, 2006, to December 31, 2015. Analysis included the use of bivariate and multivariate models to evaluate factors associated with opioid prescribing. Practitioners from emergency departments throughout the United States were surveyed, and data were collected using a representative sample of visits to hospital emergency departments. The study analyzed all emergency department visits included in the National Hospital Ambulatory Medical Care Survey for patients younger than 18 years. All statistical analysis was completed in June of 2018 and updated upon receiving reviewer feedback in October of 2018. Exposures Information regarding participants’ medications was collected at time of visit. Participants who reported taking 1 or more opioids were identified. Main Outcomes and Measures Evaluation of opioid prescribing patterns across demographic factors and pain diagnoses. Results A total of 69 152 visits with patients younger than 18 years (32 727 female) were included, which were extrapolated by the National Hospital Ambulatory Medical Care Survey to represent 293 528 632 visits nationwide, with opioid use representing 21 276 831 (7.25%) of the extrapolated visits. Factors including geographic region, race, age, and payment method were associated with statistically significant differences in opioid prescribing. The Northeast reported an opioid prescribing rate of 4.69% (95% CI, 3.69%-5.70%) vs 8.84% (95% CI, 6.82%-10.86%) in the West (P = .004). White individuals were prescribed an opioid at 8.11% (95% CI, 7.23%-8.99%) of visits vs 5.31% (95% CI, 4.31%-6.32%) for nonwhite individuals (P \u3c .001). Those aged 13 to 17 years were significantly more likely to receive opioid prescriptions (16.20%; 95% CI, 14.29%-18.12%) than those aged 3 to 12 years (6.59%; 95% CI, 5.75%-7.43%) or 0 to 2 years (1.70%; 95% CI, 1.42%-1.98%). Patients using Medicaid for payment were less likely to receive an opioid than those using private insurance (5.47%; 95% CI, 4.79%-6.15% vs 9.73%; 95% CI, 8.56%-10.90%). There was no significant difference in opioid prescription across sexes. Opioid prescribing rates decreased when comparing 2006 to 2010 with 2011 to 2015 (8.23% [95% CI, 6.75%-9.70%] vs 6.30% [95% CI, 5.44%-7.17%]; P \u3c .001); however, opioid prescribing rates remained unchanged in specific pain diagnoses, including pelvic and back pain. Conclusions and Relevance This research demonstrated an overall reduction in opioid use among pediatric patients from 2011 to 2015 compared with the previous 5 years; however, there appear to be variations in factors associated with opioid prescribing. The association of location, race, payment method, and pain diagnoses with rates of prescribing of opioids suggests areas of potential quality improvement and further research

Exploring the Relationship of Digital Information Sources and Medication Adherence

We present a retrospective analysis of data collected in the United States from the 2015 National Consumer Survey on the Medication Experience and Pharmacists’ Role in order to model the relationship between health information sources and medication adherence and perception. Our results indicate that while the digital age has presented prescription users with many non-traditional alternatives for health information, the use of digital content has a significant negative correlation with pharmaceutical adherence and attitudes toward medication. These findings along with previous research suggest that in order to fully realize the potential benefits of the digital age in regards to patient health, positive patient-provider discussions regarding information found online, efforts to improve general health literacy and improvements in the quality and accuracy of the information found are key. Given that higher reliance on digital content is correlated with younger age, the analysis suggests that proactive measures should be taken to educate younger prescription users about the merits and pitfalls of information seeking techniques as they pertain to health literacy

Evaluating Factors Impacting Medication Adherence Among Rural, Urban, and Suburban Populations

Purpose: To evaluate differences in prescription medication adherence rates, as well as influencing factors, in rural and urban adults. Methods: This is a retrospective analysis of the 2015 National Consumer Survey on the Medication Experience and Pharmacists’ Role. A total of 26,173 participants completed the survey and provided usable data. Participants using between 1 and 30 prescription medications and living more than 0 miles and up to 200 miles from their nearest pharmacy were selected for the study, resulting in a total of 15,933 participants. Data from the 2010 US Census and Rural Health Research Center were used to determine the population density of each participant’s ZIP code. Participant adherence to reported chronic medications was measured based on the 8-item Morisky Medication Adherence Scale (MMAS-8). Findings: Overall adherence rates did not differ significantly between rural and urban adults with average adherence based on MMAS-8 scores of 5.58 and 5.64, respectively (P = .253). Age, income, education, male sex, and white race/ethnicity were associated with higher adherence rates. While the overall adherence rates between urban and rural adults were not significantly different, the factors that influenced adherence varied between age-specific population density groupings. Conclusion: These analyses suggest that there is no significant difference in adherence between rural and urban populations; however, the factors contributing to medication adherence may vary based on age and population density. Future adherence intervention methods should be designed with consideration for these individualized factors

Racial and Ethnic Disparities in Opioid Use for Adolescents at US Emergency Departments

Background Racial/ethnic disparities in the use of opioids to treat pain disorders have been previously reported in the emergency department (ED). Further research is needed to better evaluate the impact race/ethnicity may have on the use of opioids in adolescents for the management of pain disorders in the ED. Methods This was a cross-sectional study using data from the National Hospital Ambulatory Medical Care Survey from 2006 to 2016. Multivariate models were used to evaluate the role of race/ethnicity in the receipt of opioid agonists while in the ED. All ED visits with patients aged 11–21 years old were analyzed. Races/ethnicities were stratified as non-Hispanic Whites, non-Hispanic Blacks, and Hispanics. In addition to race, statistical analysis included the following covariates: pain score, pain diagnosis, age, region, sex, and payment method. Results There was a weighted total of 189,256,419 ED visits. Those visits involved 109,826,315 (58%) non-Hispanic Whites, 46,314,977 (24%) non-Hispanic Blacks, and 33,115,127 (18%) Hispanics, with 21.6% (95% CI, 21.1%-22.1), 15.2% (95% CI, 14.6–15.9%), and 17.4% (95% CI, 16.5–18.2%) of those visits reporting use of opioids, respectively. Regardless of age, sex, and region, non-Hispanic Whites received opioids at a higher rate than non-Hispanic Blacks and Hispanics. Based on diagnosis, non-Hispanic Whites received opioids at a higher rate in multiple pain diagnoses. Additionally, non-Hispanic Blacks and Hispanics were less likely to receive an opioid when reporting moderate pain (aOR = 0.738, 95% CI 0.601–0.906, aOR = 0.739, 95% CI 0.578–0.945, respectively) and severe pain (aOR = 0.580, 95% CI 0.500–0.672, aOR = 0.807, 95% CI 0.685–0.951, respectively) compared to non-Hispanic Whites. Conclusions Differences in the receipt of opioid agonists in EDs among the races/ethnicities exist, with more non-Hispanic Whites receiving opioids than their minority counterparts. Non-Hispanic Black women may be an especially marginalized population. Further investigation into sex-based and regional differences are needed

Evaluating the 0–10 Point Pain Scale on Adolescent Opioid Use in US Emergency Departments

Objective: To evaluate trends in national emergency department (ED) adolescent opioid use in relation to reported pain scores. Methods: A retrospective, cross-sectional analysis on National Hospital Ambulatory Medical Care Survey (NHAMCS) data was conducted on ED visits involving patients aged 11–21 from 2008–2017. Crude observational counts were extrapolated to weighted estimates matching total population counts. Multivariate models were used to evaluate the role of a pain score in the reported use of opioids. Anchors for pain scores were 0 (no pain) and 10 (worst pain imaginable). Results: 31,355 observations were captured, which were extrapolated by the NHAMCS to represent 162,515,943 visits nationwide. Overall, patients with a score of 10 were 1.35 times more likely to receive an opioid than patients scoring a 9, 41.7% (CI95 39.7–43.8%) and 31.0% (CI95 28.8–33.3%), respectively. Opioid use was significantly different between traditional pain score cutoffs of mild (1–3) and moderate pain (4–6), where scores of 4 were 1.76 times more likely to receive an opioid than scores of 3, 15.5% (CI95 13.7–17.3%) and 8.8% (CI95 7.1–10.6%), respectively. Scores of 7 were 1.33 times more likely to receive opioids than scores of 6, 24.7% (CI95 23.0–26.3%) and 18.5% (CI95 16.9–20.0%), respectively. Fractures had the highest likelihood of receiving an opioid, as 49.2% of adolescents with a fracture received an opioid (CI95 46.4–51.9%). Within this subgroup, only adolescents reporting a fracture pain score of 10 had significantly higher opioid use than adjacent pain scores, where fracture patients scoring a 10 were 1.4 times more likely to use opioids than those scoring 9, 82.2% (CI95 76.1–88.4%) and 59.8% (CI95 49.0–70.5%), respectively. Conclusions: While some guidelines in the adult population have revised cut-offs and groupings of the traditional tiers on a 0–10 point pain scale, the adolescent population may also require further examination to potentially warrant a similar adjustment

Detection and Tracking of T Cells in Time-lapse Imaging

The effective classification and tracking of cells obtained from modern staining techniques has significant limitations due to the necessity of having to train and utilize a human expert in the field who must manually identify each cell in each slide. Often times these slides are filled with noise cells that are not of particular interest to the researcher. The use of computational methods has the ability to effectively and efficiently enhance image quality, as well as identify and track target cell types over large data sets. Here we present a computational approach to the in vitro tracking of T cells in time-lapse imagery capable of scaling to hundreds of cells and applicable to multiple staining techniques

New Atlas Features Corn Belt Farmers\u27 Perspectives on Agriculture and Climate

The Farmer Perspectives on Agriculture and Weather Variability in the Corn Belt: A Statistical Atlas is a new publication available online at . The atlas includes maps and tables that make it easy for readers to gauge farmer perspectives within the US Corn Belt. Topics covered include farmer beliefs about climate change, attitudes toward actions in response to increased weather variability, risk perceptions, and experiences with weather extremes. This region-specific information on farmers\u27 climate change and risk beliefs is designed to help Extension personnel tailor the climate adaptation and education programming they offer in their region