Citations

Abstract Venomous snakebite is an important cause of preventable death. The World Health Organization (WHO) set a goal to halve snakebite mortality by 2030. We used verbal autopsy and vital registration data to model the proportion of venomous animal deaths due to snakes by location, age, year, and sex, and applied these proportions to venomous animal contact mortality estimates from the Global Burden of Disease 2019 study. In 2019, 63,400 people (95% uncertainty interval 38,900–78,600) died globally from snakebites, which was equal to an age-standardized mortality rate (ASMR) of 0.8 deaths (0.5–1.0) per 100,000 and represents a 36% (2–49) decrease in ASMR since 1990. India had the greatest number of deaths in 2019, equal to an ASMR of 4.0 per 100,000 (2.3-5.0). We forecast mortality will continue to decline, but not sufficiently to meet the WHO’s goals. Improved data collection should be prioritized to help target interventions, improve burden estimation, and monitor progress.

IMPORTANCE: At the start of the coronavirus disease 2019 pandemic, medications repurposed for management of coronavirus disease 2019 were used in the absence of clinical trial evidence. OBJECTIVES: To describe the variation and evolution in use of repurposed medications for coronavirus disease 2019. DESIGN, SETTING, AND PARTICIPANTS: Observational cohort study of adults hospitalized with coronavirus disease 2019 between February 15, 2020, and April 12, 2021, across 76 United States and international hospitals within the Society of Critical Care Medicine’s Discovery Viral Infection and Respiratory Illness Universal Study coronavirus disease 2019 registry. MAIN OUTCOMES AND MEASURES: Hospital variation was quantified using multivariable adjusted random effects logistic regression models and unsupervised clustering. Repurposed medications included antivirals, corticosteroids, hydroxychloroquine, immunomodulators, and therapeutic dose anticoagulants. RESULTS: Among 7,069 adults hospitalized with coronavirus disease 2019, 1,979 (28%) received antivirals, 2,876 (41%) received corticosteroids, 1,779 (25%) received hydroxychloroquine, 620 (9%) received immunomodulators, and 2,154 (31%) received therapeutic dose anticoagulants. Contribution of hospital site to risk-adjusted variation was 46% for antivirals, 30% for corticosteroids, 48% for hydroxychloroquine, 46% for immunomodulators, and 52% for therapeutic dose anticoagulants. Compared with the early pandemic, the later pandemic practice phenotypes converged with increased use of antivirals (odds ratio, 3.14; 95% CI, 2.40–4.10) and corticosteroids (odds ratio, 5.43; 95% CI, 4.23–6.97), with decreased use of hydroxychloroquine (odds ratio, 0.02; 95% CI, 0.01–0.04) and immunomodulators (odds ratio, 0.49; 95% CI, 0.34–0.70). There was no clinically significant change in the use of therapeutic dose anticoagulants (odds ratio, 1.01; 95% CI, 1.01–1.02). There were no differences in risk-adjusted mortality between hospitals with high rates of repurposed medication use compared with hospitals with low rates of use. CONCLUSIONS AND RELEVANCE: Hospital variation in the use of repurposed medications varied widely across hospitals early in the pandemic and later converged with the emergence of randomized clinical trials. Platforms developed for rapid activation and enrollment in clinical trials of repurposed medications are needed prior to the next pandemic to expedite effective, evidence-based practice.

Digital mammography has seen an explosion in the number of radiomic features used for risk-assessment modeling. However, having more features is not necessarily beneficial, as some features may be overly sensitive to imaging physics (contrast, noise, and image sharpness). To measure the effects of imaging physics, we analyzed the feature variation across imaging acquisition settings (kV, mAs) using an anthropomorphic phantom. We also analyzed the intra-woman variation (IWV), a measure of how much a feature varies between breasts with similar parenchymal patterns—a woman’s left and right breasts. From 341 features, we identified “robust” features that minimized the effects of imaging physics and IWV. We also investigated whether robust features offered better case-control classification in an independent data set of 575 images, all with an overall BI-RADS® assessment of 1 (negative) or 2 (benign); 115 images (cases) were of women who developed cancer at least one year after that screening image, matched to 460 controls. We modeled cancer occurrence via logistic regression, using cross-validated area under the receiver-operating-characteristic curve (AUC) to measure model performance. Models using features from the most-robust quartile of features yielded an AUC = 0.59, versus 0.54 for the least-robust, with p < 0.005 for the difference among the quartiles.

OBJECTIVE To describe the impact of obesity on disease severity and outcomes of coronavirus disease 2019 (COVID-19) among hospitalized children. METHODS This retrospective cohort study from the Society of Critical Care Medicine Viral Respiratory Illness Universal Study registry included all children hospitalized with COVID-19 from March 2020 to January 2021. Obesity was defined by Centers for Disease Control and Prevention BMI or World Health Organization weight for length criteria. Critical illness definition was adapted from National Institutes of Health criteria of critical COVID. Multivariate mixed logistic and linear regression was performed to calculate the adjusted odds ratio of critical illness and the adjusted impact of obesity on hospital length of stay. RESULTS Data from 795 patients (96.4% United States) from 45 sites were analyzed, including 251 (31.5%) with obesity and 544 (68.5%) without. A higher proportion of patients with obesity were adolescents, of Hispanic ethnicity, and had other comorbidities. Those with obesity were also more likely to be diagnosed with multisystem inflammatory syndrome in children (35.7% vs 28.1%, P = .04) and had higher ICU admission rates (57% vs 44%, P &lt; .01) with more critical illness (30.3% vs 18.3%, P &lt; .01). Obesity had more impact on acute COVID-19 severity than on multisystem inflammatory syndrome in children presentation. The adjusted odds ratio for critical illness with obesity was 3.11 (95% confidence interval: 1.8–5.3). Patients with obesity had longer adjusted length of stay (exponentiated parameter estimate 1.3; 95% confidence interval: 1.1–1.5) compared with patients without obesity but did not have increased mortality risk due to COVID-19 (2.4% vs 1.5%, P = .38). CONCLUSION In a large, multicenter cohort, a high proportion of hospitalized children from COVID-19 had obesity as comorbidity. Furthermore, obesity had a significant independent association with critical illness.

Abstract Background Myocarditis following coronavirus disease 2019 (COVID-19) mRNA vaccines (Pfizer-BioNTech and Moderna) has been increasingly reported. Incidence rates in the general population are lacking, with pericarditis rather than myocarditis diagnostic codes being used to estimate background rates. This comparison is critical for balancing the risk of vaccination with the risk of no vaccination. Methods A retrospective case series was performed using the Mayo Clinic COVID-19 Vaccine Registry. We measured the incidence rate ratio (IRR) for myocarditis temporally related to COVID-19 mRNA vaccination compared with myocarditis in a comparable population from 2016 through 2020. Clinical characteristics and outcomes of the affected patients were collected. A total of 21 individuals were identified, but ultimately 7 patients met the inclusion criteria for vaccine-associated myocarditis. Results The overall IRR of COVID-19–related myocarditis was 4.18 (95% confidence interval [CI], 1.63–8.98), which was entirely attributable to an increased IRR among adult males (IRR, 6.69; 95% CI, 2.35–15.52) compared with females (IRR 1.41; 95% CI, .03–8.45). All cases occurred within 2 weeks of a dose of the COVID-19 mRNA vaccine, with the majority occurring within 3 days (range, 1–13) following the second dose (6 of 7 patients, 86%). Overall, cases were mild, and all patients survived. Conclusions Myocarditis is a rare adverse event associated with COVID-19 mRNA vaccines. It occurs in adult males with significantly higher incidence than in the background population. Recurrence of myocarditis after a subsequent mRNA vaccine dose is not known at this time.

Adult-onset Still’s disease (AOSD) is characterised by a constellation of systemic inflammatory symptoms and typical laboratory findings like hyperferritinaemia. A high index of suspicion is needed to identify patients as diagnosis is primarily clinical and significant morbidity can result from delayed diagnosis. While AOSD may be self-limited, some patients experience flares over years and require more aggressive treatment approaches. Aetiology is unknown but can be triggered by viral infections and other environmental factors in a susceptible genetic host. We present a case of AOSD triggered after exposure to a sap-like liquid while working in Africa. This inciting event occurred as part of a hostile act towards the patient and involved medicinal practices traditional to the area. Our case highlights the more chronic course of AOSD, which requires escalating biological treatment to avoid long-term corticosteroids, as well as the juncture between traditional and modern medical practices.

Abstract Background Adipose-derived mesenchymal stromal cells (AMSCs) represent attractive cellular therapeutics for treatment of various diseases including osteoarthritis and bone degeneration. Preparation and characterization of AMSCs show donor-to-donor variability that indicating that AMSCs are heterogeneous populations of cells. Cell surface markers to identify MSCs, such as CD44, CD90, and CD105, are relatively invariable among AMSCs and do not reflect the heterogeneity of AMSC populations. CD36, a multifunctional surface receptor associated with transport of oxidized low-density lipoproteins and fatty acids, is also expressed by AMSCs but this marker is considerable more variable. Therefore, we assessed whether CD36 can be used to identify subpopulations in AMSCs. Methods Clinical-grade AMSCs were isolated from patient fat biopsies, cultured under xenobiotic-free conditions using human platelet lysate and sorted by flow cytometry or magnetic cell sorting to characterize CD36 expression. CD36 enriched, CD36 depleted, and unsorted AMSCs were characterized using cellular and molecular techniques including proliferation, multilineage potential, RNA-sequencing and bioinformatics, metabolomics, and sensitivity to the CD36 inhibitor sulfosuccinimidyl oleate (SSO). Results CD36 exhibited biphasic expression on AMSCs grown in human platelet lysate. Enrichment of CD36+ AMSCs showed that CD36+ expression identifies a stable subpopulation. Transcriptomic analysis revealed enhancement of calcium transporter genes. Osteogenic differentiation of CD36+ enriched, CD36+ depleted, and unsorted AMSCs showed strikingly enhanced osteogenic calcium deposition and enhanced expression of alkaline phosphatase (ALPL) and osteoprotegrin (TNFRSF11B) in the CD36+ population. While lipid droplets were not altered, adipogenic differentiation showed upregulated gene expression of key adipogenic markers, including fatty acid-binding protein 4 (FABP4) and Adiponectin (ADIPOQ), with CD36+ enrichment. Treatment of CD36+ enriched AMSCs with the SSO showed reduced calcium deposition whereas CD36+ depleted AMSCs were unaffected. Conclusions CD36 exhibits variable expression amongst AMSCs. CD36+ enriched AMSCs are a stable subpopulation with enhanced osteogenic potential that linked to CD36 receptor function. These results may further refine production and clinical application of AMSC cellular therapeutics. Furthermore, the enhanced osteogenic potential of CD36+ AMSCs may be considered for therapeutic regeneration of bone.

Abstract Background Cardiovascular disease (CVD) has been identified as a major threat to maternal health in the US and UK with cardiomyopathy being one of the most common acquired CVD in the pregnant and postpartum period. Diagnosing cardiomyopathy in pregnancy is challenging due to an overlap of cardiovascular symptoms with normal pregnancy symptoms. Purpose The purpose of this study was to evaluate the effectiveness of an ECG based deep learning model in identifying cardiomyopathy among pregnant and postpartum women. Methods We utilized an ECG based deep learning model to detect cardiomyopathy in a cohort of pregnant or postpartum women seen at multiple hospital sites. Model performance was evaluated using area under the curve (AUC), accuracy, sensitivity, and specificity. We compared the diagnostic probabilities of the deep learning model with natriuretic peptides and a multivariable model consisting of demographic and clinical parameters. Results 1,807 women were included. 7%, 10% and 13% had LVEF ≤35%, &lt;45% and &lt;50% respectively. The ECG based deep learning model identified cardiomyopathy with an AUC of 0.92 for left ventricular ejection fraction (LVEF) ≤35%, 0.89 for LVEF &lt;45% and 0.87 for LVEF &lt;50%. For LVEF ≤35%, AUC was higher in Black (0.95) and Hispanic (0.98) women compared to white (0.91). Natriuretic peptides and the multivariable model had AUCs of 0.85 and 0.72 respectively. Conclusions A deep learning model effectively identifies cardiomyopathy in pregnant or postpartum women, outperforms natriuretic peptides and traditional clinical parameters with the potential to become a powerful initial screening tool for cardiomyopathy in the obstetric care setting. Funding Acknowledgement Type of funding sources: Other. Main funding source(s): This study was made possible using resources supported by the Mayo Clinic Women's Health Research Center and the Mayo Clinic Building Interdisciplinary Research Careers in Women's Health (BIRCWH) Program funded by the National Institutes of Health (NIH), grant number K12 HD065987. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.