Study Objective: We sought to determine the overall rates of traumatic injuries and whether the rates of traumatic injuries and various clinical outcomes differed among older patients presenting to a tertiary-care emergency department (ED) after a ground-level fall (GLF) and who underwent whole-body computed tomography.

Methods: We conducted a retrospective cohort study of patients ≥65 years of age who presented to the ED with a GLF and received a whole-body CT from January 1–December 31, 2021. Age was stratified into age groups: 65–74; 75–84; and 85+. We presented a descriptive analysis of traumatic injuries, intensive care unit (ICU) admissions, and all-cause mortality rates. We used multivariable logistic regression to determine the association between increasing age, traumatic injuries, and clinical outcomes.

Results: Of 638 patients in the cohort, 120 (18.9%) sustained thoracic injuries and 80 (12.5%) sustained intracranial hemorrhages. Only five (0.8%) patients sustained an intra-abdominal injury, while 134 (21.0%) were admitted to the ICU, and 31 (4.8%) died during their index hospitalization. Head injuries (odds ratio [OR] 6.21, 95% CI 3.65–10.6, P < 0.001) and thoracic injuries (OR 5.25, 95% CI 3.30–8.36, P < 0.001) were associated with increased odds of ICU admission, whereas head injuries (OR 3.21, 95%CI 1.41–7.31, P < 0.01) and cervical injuries (OR 3.37, 95% CI 1.08–10.5, P < 0.05) were associated with increased odds of in-hospital, all-cause mortality. There were no statistically significant differences in the rates of injuries sustained between the respective age groups. There was no association between increasing age and ICU admissions or in-hospital, all-cause mortality rates.

Conclusion: Among patients aged ≥65 years of age who presented to the ED after a ground-level fall and underwent whole-body CT, thoracic injuries and intracranial hemorrhages were associated with increased odds of ICU admissions. We found no significant differences in injury rates or outcomes across age groups, indicating that age alone should not guide ICU admission decisions. These findings suggest that the use of whole-body CT in this population should be selective and guided by clinical judgment rather than applied universally.

Myalgic encephalomyelitis, or chronic fatigue syndrome (ME/CFS) is a serious disease whose cause has yet to be identified. Objective markers of the disease are also not well understood and would serve as important tools in diagnosis and management. One potential biomarker or transmitter of immune signals in ME/CFS is the extracellular vesicle (EV) compartment. These small, membrane bound particles have been shown to play a key role in intercellular signaling. Our laboratory has focused on methods of detection of EVS in clinical samples. In this study we explored whether the prevalence of EVs in the plasma of participants with mild or severe ME/CFS differed from the plasma of healthy control participants. By staining for multiple cell surface molecules, plasma EVs could be fingerprinted as to their cell of origin. Our study revealed a significant correlation between severe ME/CSF and levels of EVs bearing the B cell marker CD19 and the platelet marker CD41a, though these changes were not significant after correction for multiple comparisons. These findings point to potential dysregulation of B cell and platelet activation or homeostasis in ME/CFS, which warrants validation in a replication cohort and further exploration of potential mechanisms underlying the association.

Background

Standard testing fails to identify a pathogen in most patients with febrile neutropenia (FN). We evaluated the ability of the Karius microbial cell-free DNA sequencing test (KT) to identify infectious etiologies of FN and its impact on antimicrobial management.

Methods

This prospective study (ClinicalTrials.gov; NCT02912117) enrolled and analyzed 55 patients with FN. Up to 5 blood samples were collected per subject within 24 hours of fever onset (T1) and every 2 to 3 days. KT results were compared with blood culture (BC) and standard microbiological testing (SMT) results.

Results

Positive agreement was defined as KT identification of ≥1 isolate also detected by BC. At T1, positive and negative agreement were 90% (9/10) and 31% (14/45), respectively; 61% of KT detections were polymicrobial. Clinical adjudication by 3 independent infectious diseases specialists categorized Karius results as: unlikely to cause FN (N = 0); definite (N = 12): KT identified ≥1 organism also found by SMT within 7 days; probable (N = 19): KT result was compatible with a clinical diagnosis; possible (N = 10): KT result was consistent with infection but not considered a common cause of FN. Definite, probable, and possible cases were deemed true positives. Following adjudication, KT sensitivity and specificity were 85% (41/48) and 100% (14/14), respectively. Calculated time to diagnosis was generally shorter with KT (87%). Adjudicators determined real-time KT results could have allowed early optimization of antimicrobials in 47% of patients, by addition of antibacterials (20%) (mostly against anaerobes [12.7%]), antivirals (14.5%), and/or antifungals (3.6%); and antimicrobial narrowing in 27.3% of cases.

Clinical trials registration

NCT02912117.

Conclusion

KT shows promise in the diagnosis and treatment optimization of FN.

Objective

To describe the participation of racial and ethnic minority groups (REMGs) in gynecologic oncology trials.

Methods

Gynecologic oncology studies registered on ClinicalTrials.gov between 2007 and 2020 were identified. Trials with published results were analyzed based on reporting of race/ethnicity in relation to disease site and trial characteristics. Expected enrollment by race/ethnicity was calculated and compared to actual enrollment, adjusted for 2010 US Census population data.

Results

2146 gynecologic oncology trials were identified. Of published trials (n = 252), 99 (39.3%) reported race/ethnicity data. Recent trials were more likely to report these data (36% from 2007 to 2009; 51% 2013-2015; and 53% from 2016 to 2018, p = 0.01). Of all trials, ovarian cancer trials were least likely to report race/ethnicity data (32.1% vs 39.3%, p = 0.011). Population-adjusted under-enrollment for Blacks was 7-fold in ovarian cancer, Latinx 10-fold for ovarian and 6-fold in uterine cancer trials, Asians 2.5-fold in uterine cancer trials, and American Indian and Alaska Native individuals 6-fold in ovarian trials. Trials for most disease sites have enrolled more REMGs in recent years - REMGs made up 19.6% of trial participants in 2007-2009 compared to 38.1% in 2016-2018 (p < 0.0001).

Conclusion

Less than half of trials that published results reported race/ethnicity data. Available data reveals that enrollment of REMGs is significantly below expected rates based on national census data. These disparities persisted even after additionally adjusting for population size. Despite improvement in recent years, additional recruitment of REMGs is needed to achieve more representative and equitable participation in gynecologic cancer clinical trials.

BACKGROUND: Long-term symptoms following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are a major concern, yet their prevalence is poorly understood. METHODS: We conducted a prospective cohort study comparing adults with SARS-CoV-2 infection (coronavirus disease-positive [COVID+]) with adults who tested negative (COVID-), enrolled within 28 days of a Food and Drug Administration (FDA)-approved SARS-CoV-2 test result for active symptoms. Sociodemographic characteristics, symptoms of SARS-CoV-2 infection (assessed with the Centers for Disease Control and Prevention [CDC] Person Under Investigation Symptom List), and symptoms of post-infectious syndromes (ie, fatigue, sleep quality, muscle/joint pains, unrefreshing sleep, and dizziness/fainting, assessed with CDC Short Symptom Screener for myalgic encephalomyelitis/chronic fatigue syndrome) were assessed at baseline and 3 months via electronic surveys sent via text or email. RESULTS: Among the first 1000 participants, 722 were COVID+ and 278 were COVID-. Mean age was 41.5 (SD 15.2); 66.3% were female, 13.4% were Black, and 15.3% were Hispanic. At baseline, SARS-CoV-2 symptoms were more common in the COVID+ group than the COVID- group. At 3 months, SARS-CoV-2 symptoms declined in both groups, although were more prevalent in the COVID+ group: upper respiratory symptoms/head/eyes/ears/nose/throat (HEENT; 37.3% vs 20.9%), constitutional (28.8% vs 19.4%), musculoskeletal (19.5% vs 14.7%), pulmonary (17.6% vs 12.2%), cardiovascular (10.0% vs 7.2%), and gastrointestinal (8.7% vs 8.3%); only 50.2% and 73.3% reported no symptoms at all. Symptoms of post-infectious syndromes were similarly prevalent among the COVID+ and COVID- groups at 3 months. CONCLUSIONS: Approximately half of COVID+ participants, as compared with one-quarter of COVID- participants, had at least 1 SARS-CoV-2 symptom at 3 months, highlighting the need for future work to distinguish long COVID. CLINICAL TRIALS REGISTRATION: NCT04610515.

Clinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial coinfection, and determining illness severity since current practices require separate workflows. Here, we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and bacterial coinfections and predicting clinical severity of COVID-19. A total of 161 patients with PCR-confirmed COVID-19 (52.2% female; median age, 50.0 years; 51% hospitalized; 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene blood RNA), and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter. The IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrollment, and the remaining patients oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial coinfection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e., Clostridioides difficile colitis (n = 1), urinary tract infection (n = 1), and clinically diagnosed bacterial infections (n = 3), for a specificity of 99.4%. Two of 101 (2.8%) patients in the IMX-SEV-3 "Low" severity classification and 7/60 (11.7%) in the "Moderate" severity classification died within 30 days of enrollment. IMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19 and bacterial coinfections and predicted patients' risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management, including more accurate treatment decisions and optimized resource utilization. IMPORTANCE We assay the utility of the single-test IMX-BVN-3/IMX-SEV-3 classifiers that require just 2.5 mL of patient blood in concurrently detecting viral and bacterial infections as well as predicting the severity and 30-day outcome from the infection. A point-of-care device, in development, will circumvent the need for blood culturing and drastically reduce the time needed to detect an infection. This will negate the need for empirical use of broad-spectrum antibiotics and allow for antibiotic use stewardship. Additionally, accurate classification of the severity of infection and the prediction of 30-day severe outcomes will allow for appropriate allocation of hospital resources.

Background

The determinants of coronavirus disease 2019 (COVID-19) disease severity and extrapulmonary complications (EPCs) are poorly understood. We characterized relationships between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNAemia and disease severity, clinical deterioration, and specific EPCs.

Methods

We used quantitative and digital polymerase chain reaction (qPCR and dPCR) to quantify SARS-CoV-2 RNA from plasma in 191 patients presenting to the emergency department with COVID-19. We recorded patient symptoms, laboratory markers, and clinical outcomes, with a focus on oxygen requirements over time. We collected longitudinal plasma samples from a subset of patients. We characterized the role of RNAemia in predicting clinical severity and EPCs using elastic net regression.

Results

Of SARS-CoV-2-positive patients, 23.0% (44 of 191) had viral RNA detected in plasma by dPCR, compared with 1.4% (2 of 147) by qPCR. Most patients with serial measurements had undetectable RNAemia within 10 days of symptom onset, reached maximum clinical severity within 16 days, and symptom resolution within 33 days. Initially RNAemic patients were more likely to manifest severe disease (odds ratio, 6.72 [95% confidence interval, 2.45-19.79]), worsening of disease severity (2.43 [1.07-5.38]), and EPCs (2.81 [1.26-6.36]). RNA loads were correlated with maximum severity (r = 0.47 [95% confidence interval, .20-.67]).

Conclusions

dPCR is more sensitive than qPCR for the detection of SARS-CoV-2 RNAemia, which is a robust predictor of eventual COVID-19 severity and oxygen requirements, as well as EPCs. Because many COVID-19 therapies are initiated on the basis of oxygen requirements, RNAemia on presentation might serve to direct early initiation of appropriate therapies for the patients most likely to deteriorate.

Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions, and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes, and biogeochemical cycling. We also compare studies of natural snow gradients with snow experimental manipulation studies to assess time scale difference of these approaches. The number of tundra snow studies has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. Specifically, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by snow addition and snow removal manipulations (average 7.9 days advance and 5.5 days delay, respectively) were substantially lower than the temporal variation over natural spatial gradients within a given year (mean range 56 days) or among years (mean range 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates.

Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale.

Background

The coronavirus disease 2019 (COVID-19) pandemic has adversely affected diagnosis and treatment of noncommunicable diseases. Its effects on delivery of diagnostic care for cardiovascular disease, which remains the leading cause of death worldwide, have not been quantified.

Objectives

The study sought to assess COVID-19's impact on global cardiovascular diagnostic procedural volumes and safety practices.

Methods

The International Atomic Energy Agency conducted a worldwide survey assessing alterations in cardiovascular procedure volumes and safety practices resulting from COVID-19. Noninvasive and invasive cardiac testing volumes were obtained from participating sites for March and April 2020 and compared with those from March 2019. Availability of personal protective equipment and pandemic-related testing practice changes were ascertained.

Results

Surveys were submitted from 909 inpatient and outpatient centers performing cardiac diagnostic procedures, in 108 countries. Procedure volumes decreased 42% from March 2019 to March 2020, and 64% from March 2019 to April 2020. Transthoracic echocardiography decreased by 59%, transesophageal echocardiography 76%, and stress tests 78%, which varied between stress modalities. Coronary angiography (invasive or computed tomography) decreased 55% (p < 0.001 for each procedure). In multivariable regression, significantly greater reduction in procedures occurred for centers in countries with lower gross domestic product. Location in a low-income and lower-middle-income country was associated with an additional 22% reduction in cardiac procedures and less availability of personal protective equipment and telehealth.

Conclusions

COVID-19 was associated with a significant and abrupt reduction in cardiovascular diagnostic testing across the globe, especially affecting the world's economically challenged. Further study of cardiovascular outcomes and COVID-19-related changes in care delivery is warranted.