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BACKGROUND: Many states in the United States have progressed towards legalization of marijuana including decriminalization, medicinal and/or recreational use. We studied the impact of legalization on cannabis-related emergency department visits in states with varying degrees of legalization. METHODS: Seventeen healthcare institutions in fifteen states (California, Colorado, Connecticut, Florida, Iowa, Kentucky, Maryland, Massachusetts, Missouri, New Hampshire, Oregon, South Carolina, Tennessee, Texas, Washington) participated. Cannabinoid immunoassay results and cannabis-related International Classification of Diseases (ninth and tenth versions) codes were obtained for emergency department visits over a 3- to 8-year period during various stages of legalization: no state laws, decriminalized, medical approval before dispensaries, medical dispensaries available, recreational approval before dispensaries and recreational dispensaries available. Trends and monthly rates of cannabinoid immunoassay and cannabis-related International Classification of Diseases code positivity were determined during these legalization periods. RESULTS: For most states, there was a significant increase in both cannabinoid immunoassay and International Classification of Diseases code positivity as legalization progressed; however, positivity rates differed. The availability of dispensaries may impact positivity in states with medical and/or recreational approval. In most states with no laws, there was a significant but smaller increase in cannabinoid immunoassay positivity rates. CONCLUSIONS: States may experience an increase in cannabis-related emergency department visits with progression toward marijuana legalization. The differences between states, including those in which no impact was seen, are likely multifactorial and include cultural norms, attitudes of local law enforcement, differing patient populations, legalization in surrounding states, availability of dispensaries, various ordering protocols in the emergency department, and the prevalence of non-regulated cannabis products.

Electronic health records (EHRs) and linked biobanks have tremendous potential to advance biomedical research and ultimately improve the health of future generations. Repurposing EHR data for research is not without challenges, however. In this paper, we describe the processes and considerations necessary to successfully access and utilize a data warehouse for research. Although imperfect, data warehouses are a powerful tool for harnessing a large amount of data to phenotype disease. They will have increasing relevance and applications in clinical research with growing sophistication in processes for EHR data abstraction, biobank integration, and cross-institutional linkage.

Introduction: Biorepositories lack diversity both demographically and with regard to the clinical complaints of patients enrolled. The Emergency Medicine Specimen Bank (EMSB) seeks to enroll a diverse cohort of patients for discovery research in acute care conditions. Our objective in this study was to determine the differences in demographics and clinical complaints between participants in the EMSB and the overall emergency department (ED) population. Methods: This was a retrospective analysis of participants of the EMSB and the entire UCHealth at University of Colorado Anschutz Medical Center (UCHealth AMC) ED population across three periods: peri-EMSB; post-EMSB; and COVID-19. We compared patients consented to the EMSB to the entire ED population to determine differences in age, gender, ethnicity, race, clinical complaints, and severity of illness. We used chi-square tests to compare categorical variables and the Elixhauser Comorbidity Index to determine differences in the severity of illness between the groups.  Results: Between February 5, 2018–January 29, 2022, there were 141,670 consented encounters in the EMSB, representing 40,740 unique patients and over 13,000 blood samples collected. In that same time, the ED saw approximately 188,402 unique patients for 387,590 encounters. The EMSB had significantly higher rates of participation from the following: patients 18-59 years old (80.3% vs 77.7%); White patients (52.3% vs 47.8%), and women (54.8% vs 51.1%) compared to the overall ED population. The EMSB had lower rates of participation from patients ≥70 years, Hispanic patients, Asian patients, and men. The EMSB population had higher mean comorbidity scores. During the six months after Colorado’s first COVID-19 case, the rate of consented patients and samples collected increased. The odds of consent during the COVID-19 study period were 1.32 (95% CI 1.26-1.39), and the odds of sample capture were 2.19 (95% CI 2.0-2.41). Conclusion: The EMSB is representative of the overall ED population for most demographics and clinical complaints.

BackgroundAlthough biological males and females are equally likely to become infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), evidence has mounted that males experience higher severity and fatality compared to females. MAIN: The objective of this review is to examine the existing literature on biological mechanisms underlying sex-based differences that could contribute to SARS-CoV-2 infection clinical outcomes. Sex-based differences in immunologic response and hormonal expression help explain the differences in coronavirus disease 2019 (COVID-19) outcomes observed in biological males and females. X inactivation facilitates a robust immune response to COVID-19 in females, who demonstrate a more profound antibody response and faster recovery when compared to males. Low testosterone levels also help explain the dysregulated inflammatory response and poor outcomes observed in some males with COVID-19. Gender differences in health expression and behaviors further compound these observed differences.ConclusionUnderstanding the biology of sex-based differences in COVID-19 severity and mortality could help inform preventative measures, treatment decisions, and development of personalized, sex-specific therapies.

RT-PCR is the foremost clinical test for diagnosis of COVID-19. Unfortunately, PCR-based testing has limitations and may not result in a positive test early in the course of infection before symptoms develop. Enveloped RNA viruses, such as coronaviruses, alter peripheral blood methylation and DNA methylation signatures may characterize asymptomatic versus symptomatic infection. We used Illumina's Infinium MethylationEPIC BeadChip array to profile peripheral blood samples from 164 patients who tested positive for SARS-CoV-2 by RT-PCR, of whom 8 had no symptoms. Epigenome-wide association analysis identified 10 methylation sites associated with infection and a quantile-quantile plot showed little inflation. These preliminary results suggest that differences in methylation patterns may distinguish asymptomatic from symptomatic infection.

The new Pharmacogenomics Global Research Network (PGRN) is an independent society that builds on the National Institutes of Health (NIH)–funded Pharmacogenomics Research Network that was established in 2000. Leveraging the original PGRN’s previous success, the new network continues to be a leader in the field of personalized medicine focusing on research, discovery, and translation of genomic variation influencing drug efficacy and adverse events, while simultaneously increasing inclusion in the field and expanding globally.

BackgroundSince the onset of the SARS-CoV-2 pandemic, most clinical testing has focused on RT-PCR1. Host epigenome manipulation post coronavirus infection2-4 suggests that DNA methylation signatures may differentiate patients with SARS-CoV-2 infection from uninfected individuals, and help predict COVID-19 disease severity, even at initial presentation.MethodsWe customized Illumina's Infinium MethylationEPIC array to enhance immune response detection and profiled peripheral blood samples from 164 COVID-19 patients with longitudinal measurements of disease severity and 296 patient controls.ResultsEpigenome-wide association analysis revealed 13,033 genome-wide significant methylation sites for case-vs-control status. Genes and pathways involved in interferon signaling and viral response were significantly enriched among differentially methylated sites. We observe highly significant associations at genes previously reported in genetic association studies (e.g. IRF7, OAS1). Using machine learning techniques, models built using sparse regression yielded highly predictive findings: cross-validated best fit AUC was 93.6% for case-vs-control status, and 79.1%, 80.8%, and 84.4% for hospitalization, ICU admission, and progression to death, respectively.ConclusionsIn summary, the strong COVID-19-specific epigenetic signature in peripheral blood driven by key immune-related pathways related to infection status, disease severity, and clinical deterioration provides insights useful for diagnosis and prognosis of patients with viral infections.

Background and aimsThe Psychoactive Surveillance Consortium and Analysis Network (PSCAN) is a national network of academic emergency departments (ED), analytical toxicologists and pharmacologists that collects clinical data paired with biological samples to identify and improve treatments of medical conditions arising from use of new psychoactive substances (NPS). The aim of this study was to gather clinical data with paired drug identification from NPS users who presented to EDs within PSCAN during its first year (2016-17).DesignObservational study involving patient records and biological samples.SettingSeven academic emergency medical centers across the United States.ParticipantsED patients (n = 127) > 8 years of age with possible NPS use who were identified and enrolled in PSCAN by clinical providers or research personnel.MeasurementsClinical signs, symptoms and treatments were abstracted from the patients' health records. Biological samples were collected from leftover urine, serum and whole blood. Biological and drug samples, when available, were tested for drugs and drug metabolites via liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS).FindingsPatients in whom synthetic opioids were detected (n = 9) showed higher rates of intubation (four of nine), impaired mental status (four of nine) and respiratory acidosis (five of nine) compared with the rest of the cohort (nine of 118, P-value

For a variety of reasons including cheap computing, widespread adoption of electronic medical records, digitalization of imaging and biosignals, and rapid development of novel technologies, the amount of health care data being collected, recorded, and stored is increasing at an exponential rate. Yet despite these advances, methods for the valid, efficient, and ethical utilization of these data remain underdeveloped. Emergency care research, in particular, poses several unique challenges in this rapidly evolving field. A group of content experts was recently convened to identify research priorities related to barriers to the application of data science to emergency care research. These recommendations included: 1) developing methods for cross-platform identification and linkage of patients; 2) creating central, deidentified, open-access databases; 3) improving methodologies for visualization and analysis of intensively sampled data; 4) developing methods to identify and standardize electronic medical record data quality; 5) improving and utilizing natural language processing; 6) developing and utilizing syndrome or complaint-based based taxonomies of disease; 7) developing practical and ethical framework to leverage electronic systems for controlled trials; 8) exploring technologies to help enable clinical trials in the emergency setting; and 9) training emergency care clinicians in data science and data scientists in emergency care medicine. The background, rationale, and conclusions of these recommendations are included in the present article.

Introduction: Staphylococcus aureus bacteremia (SAB) is the second-most common cause of community-onset (CO) bacteremia. The incidence of methicillin-resistant S. aureus (MRSA) has recently decreased across much of the United States, and we seek to describe risk factors for COMRSA bacteremia, which will aid emergency providers in their choice of empiric antibiotics.Methods: This is a retrospective cohort study of all patients with SAB at a 500-bed safety net hospital. The proportion of S. aureus isolates that were MRSA ranged from 32-35% during the study period. Variables of interest included age, comorbid medical conditions, microbiology results, antibioticadministration, duration of bacteremia, duration of hospital admission, suspected source of SAB, and Elixhauser comorbidity score. The primary outcome was to determine risk factors for CO-MRSA bacteremia as compared to methicillin-susceptible S. aureus (MSSA) bacteremia in patients admittedto the hospital through the emergency department.Results: We identified 135 consecutive patients with CO-SAB. In comparison to those with MSSA bacteremia, patients with MRSA bacteremia were younger (odds ratio [OR] 0.5, 95% confidence interval [CI], 0.4-0.7) with higher Elixhauser comorbidity scores (OR 1.4, 95% CI, 1.1-1.7). Additionally, these patients were more likely to have a history of MRSA infection or colonization (OR 8.9, 95% CI,2.7-29.7) and intravenous drug use (OR 2.4, 95% CI, 1.0-5.7).Conclusion: SAB continues to be prevalent in our urban community with CO-MRSA accounting for almost one-third of SAB cases. Previous MRSA colonization was the strongest risk factor for current MRSA infection in this cohort of patients with CO-SAB.

The OPRM1 gene codes for the mu opioid receptor (MOR) and polymorphisms are associated with complex patient clinical responses. The most studied single nucleotide polymorphism (SNP) in OPRM1 is adenine (A) substituted by guanine (G) at position 118 (118A>G, rs1799971) leading to a substitution of asparagine (Asn) for aspartic acid (Asp) at position 40 in the N terminus of the resulting protein. To date, no structural explanation for the associated clinical responses resulting from the 118A>G polymorphism has been proposed. We utilized computational modeling paired with functional cellular assays to predict unstructured N‐ and C‐terminal regions of MOR‐1. Using molecular docking and post‐docking energy minimizations with morphine, we show that the extracellular substitution of Asn at position 40 alters the cytoplasmic C‐terminal conformation, while leaving the G‐protein binding interface unaffected. A real‐time BRET assay measuring G‐protein and β‐arrestin association with MOR r generated data that tested this prediction. Consistent with this in silico prediction, we show changes in morphine‐mediated β‐arrestin association with receptor variants with little change in morphine‐mediated G‐protein association comparing MOR‐1 wild type (WT) to MOR‐1118A>G. We tested the system with different opioid agonists, the OPRM1 118A>G SNP, and different MOR splice variants (MOR‐1 and MOR‐1O). These results are consistent with the observation that patients with the 118A>G OPRM1 allele respond more readily to fentanyl than to morphine. In conclusion, the 118A>G substitution alters receptor responses to opioids through variable C‐terminal domain movements that are agonist and splice variant dependent. [ABSTRACT FROM AUTHOR]

Book details Cobert B Cobert's Manual of Drug Safety and Pharmacovigilance: Second Edition Sudbury: Jones & Bartlett Learning; 2012 408 pages, ISBN-13: 978–0763791599