Genotype-guided prescribing predictors in CYP2C19 intermediate metabolizers receiving percutaneous coronary intervention.

Background: Previous differences in guideline recommendation strength for CYP2C19 intermediate metabolizers may have limited genotype (PGx)-optimal post-percutaneous coronary intervention antiplatelet prescribing. Results: In this single-center retrospective observational cohort study of CYP2C19 intermediate metabolizers, patients prescribed PGx-optimal therapy were younger and less likely on anticoagulation (2 vs 12%; p = 0.006). More patients prescribed PGx-optimal therapy possessed commercial insurance (36 vs 7%; p < 0.001), which was a predictor for PGx-optimal selection (OR: 6.464; 95% CI: 2.386-17.516; p < 0.001). Conclusion: Anticoagulation use was significantly associated with clopidogrel use (OR: 0.138; 95% CI: 0.026-0.730; p = 0.020). No statistical difference in composite major adverse cardiovascular events (5 vs 14%; p = 0.173) or bleeding (8 vs 6%; Not significant) was observed between PGx-optimal and PGx-suboptimal therapy.

Not all CYP2C19 intermediate metabolizers undergoing PCI are prescribed genotype-optimal P2Y12 antiplatelet therapy. Commercial insurance and no anticoagulant were found to be associated with ticagrelor and prasugrel prescribing in this population.

Atypical B cells and impaired SARS-CoV-2 neutralisation following booster vaccination in the elderly.

Age is a major risk factor for hospitalization and death after SARS-CoV-2 infection, even in vaccinees. Suboptimal responses to a primary vaccination course have been reported in the elderly, but there is little information regarding the impact of age on responses to booster third doses. Here we show that individuals 70 or older who received a primary two dose schedule with AZD1222 and booster third dose with mRNA vaccine achieved significantly lower neutralizing antibody responses against SARS-CoV-2 spike pseudotyped virus compared to those younger than 70. One month after the booster neither the concentration of serum binding anti spike IgG antibody, nor the frequency of spike-specific B cells showed differences by age grouping. However, the impaired neutralization potency and breadth post-third dose in the elderly was associated with enrichment of circulating "atypical" spike-specific B cells expressing CD11c and FCRL5. Single cell RNA sequencing confirmed an expansion of TBX21-, ITGAX-expressing B cells in the elderly that enriched for B cell activation/receptor signalling pathway genes. Importantly we also observed impaired T cell responses to SARS-CoV-2 spike peptides in the elderly post-booster, both in terms of IFNgamma and IL2 secretion, as well as a decrease in T cell receptor signalling pathway genes. This expansion of atypical B cells and impaired T cell responses may contribute to the generation of less affinity-matured antibodies, with lower neutralizing capacity post-third dose in the elderly. Altogether, our data reveal the extent and potential mechanistic underpinning of the impaired vaccine responses present in the elderly after a booster dose, contributing to their increased susceptibility to COVID-19 infection.

Use of high-resolution ground conductivity measurements for denitrifying conservation practice placement.

Accurate field-scale maps of soil properties including features such as texture, soil organic matter (SOM) content, and hydraulic conductivity are essential for proper placement of conservation practices that utilize anoxic soil environments for denitrification. However, in many cases, soil maps inaccurately represent subsoil properties and can mislead managers about where to install new practices. Non-invasive methods of subsoil property analysis including electromagnetic induction techniques are a potentially efficient method for improving existing field-scale soil maps. In this study, we quantified the accuracy of existing soil maps in an agricultural field in north-central Iowa. Of 60 soil cores collected and reclassified, 19 were identified as taxadjunct at the soil series level primarily due to hydrologic indicators and soil particle size. We assessed the correlation among physical and chemical soil properties measured in-lab and geophysical responses measured in-field. We identified significant correlation of SOM and sand to electrical conductivity for individual core and mean soil series data. From this analysis, we developed a conservation practice suitability map and evaluated the potential for field-scale geophysical investigations to serve as a new tool for agricultural conservation planning and placement of site-specific denitrifying conservation practices. Study results suggest that incorporating a geophysical conductivity investigation into conservation planning may improve understanding of critical soil properties beyond those ascertained with limited soil borings.

Automating document classification with distant supervision to increase the efficiency of systematic reviews: A case study on identifying studies with HIV impacts on female sex workers.

There remains a limited understanding of the HIV prevention and treatment needs among female sex workers in many parts of the world. Systematic reviews of existing literature can help fill this gap; however, well-done systematic reviews are time-demanding and labor-intensive. Here, we propose an automatic document classification approach to a systematic review to significantly reduce the effort in reviewing documents and optimizing empiric decision making. We first describe a manual document classification procedure that is used to curate a pertinent training dataset and then propose three classifiers: a keyword-guided method, a cluster analysis-based method, and a random forest approach that utilizes a large set of feature tokens. This approach is used to identify documents studying female sex workers that contain content relevant to either HIV or experienced violence. We compare the performance of the three classifiers by cross-validation in terms of area under the curve of the receiver operating characteristic and precision and recall plot, and found random forest approach reduces the amount of manual reading for our example by 80%; in sensitivity analysis, we found that even trained with only 10% of data, the classifier can still avoid reading 75% of future documents (68% of total) while retaining 80% of relevant documents. In sum, the automated procedure of document classification presented here could improve both the precision and efficiency of systematic reviews and facilitate live reviews, where reviews are updated regularly. We expect to obtain a reasonable classifier by taking 20% of retrieved documents as training samples. The proposed classifier could also be used for more meaningfully assembling literature in other research areas and for rapid documents screening with a tight schedule, such as COVID-related work during the crisis.

An Evaluation of Prospective COVID-19 Modeling: From Data to Science Translation

BackgroundInfectious disease modeling can serve as a powerful tool for science-based management of outbreaks, providing situational awareness and decision support for policy makers. Predictive modeling of an emerging disease is challenging due to limited knowledge on its epidemiological characteristics. For COVID-19, the prediction difficulty was further compounded by continuously changing policies, varying behavioral responses, poor availability and quality of crucial datasets, and the variable influence of different factors as the pandemic progresses. Due to these challenges, predictive modeling for COVID-19 has earned a mixed track record. MethodsWe provide a systematic review of prospective, data-driven modeling studies on population-level dynamics of COVID-19 in the US and conduct a quantitative assessment on crucial elements of modeling, with a focus on the aspects of modeling that are critical to make them useful for decision-makers. For each study, we documented the forecasting window, methodology, prediction target, datasets used, geographic resolution, whether they expressed quantitative uncertainty, the type of performance evaluation, and stated limitations. We present statistics for each category and discuss their distribution across the set of studies considered. We also address differences in these model features based on fields of study. FindingsOur initial search yielded 2,420 papers, of which 119 published papers and 17 preprints were included after screening. The most common datasets relied upon for COVID-19 modeling were counts of cases (93%) and deaths (62%), followed by mobility (26%), demographics (25%), hospitalizations (12%), and policy (12%). Our set of papers contained a roughly equal number of short-term (46%) and long-term (60%) predictions (defined as a prediction horizon longer than 4 weeks) and statistical (43%) versus compartmental (47%) methodologies. The target variables used were predominantly cases (89%), deaths (52%), hospitalizations (10%), and Rt (9%). We found that half of the papers in our analysis did not express quantitative uncertainty (50%). Among short-term prediction models, which can be fairly evaluated against truth data, 25% did not conduct any performance evaluation, and most papers were not evaluated over a timespan that includes varying epidemiological dynamics. The main categories of limitations stated by authors were disregarded factors (39%), data quality (28%), unknowable factors (26%), limitations specific to the methods used (22%), data availability (16%), and limited generalizability (8%). 36% of papers did not list any limitations in their discussion or conclusion section. InterpretationPublished COVID-19 models were found to be consistently lacking in some of the most important elements required for usability and translation, namely transparency, expressing uncertainty, performance evaluation, stating limitations, and communicating appropriate interpretations. Adopting the EPIFORGE 2020 guidelines would address these shortcomings and improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. We also discovered that most of the operational models that have been used in real-time to inform decision-making have not yet made it into the published literature, which highlights that the current publication system is not suited to the rapid information-sharing needs of outbreaks. Furthermore, data quality was identified to be one of the most important drivers of model performance, and a consistent limitation noted by the modeling community. The US public health infrastructure was not equipped to provide timely, high-quality COVID-19 data, which is required for effective modeling. Thus, a systematic infrastructure for improved data collection and sharing should be a major area of investment to support future pandemic preparedness.

Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: a multi-model study

BackgroundSARS-CoV-2 vaccination of persons aged 12 years and older has reduced disease burden in the United States. The COVID-19 Scenario Modeling Hub convened multiple modeling teams in September 2021 to project the impact of expanding vaccine administration to children 5-11 years old on anticipated COVID-19 burden and resilience against variant strains. MethodsNine modeling teams contributed state- and national-level projections for weekly counts of cases, hospitalizations, and deaths in the United States for the period September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of: 1) presence vs. absence of vaccination of children ages 5-11 years starting on November 1, 2021; and 2) continued dominance of the Delta variant vs. emergence of a hypothetical more transmissible variant on November 15, 2021. Individual team projections were combined using linear pooling. The effect of childhood vaccination on overall and age-specific outcomes was estimated by meta-analysis approaches. FindingsAbsent a new variant, COVID-19 cases, hospitalizations, and deaths among all ages were projected to decrease nationally through mid-March 2022. Under a set of specific assumptions, models projected that vaccination of children 5-11 years old was associated with reductions in all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios where children were not vaccinated. This projected effect of vaccinating children 5-11 years old increased in the presence of a more transmissible variant, assuming no change in vaccine effectiveness by variant. Larger relative reductions in cumulative cases, hospitalizations, and deaths were observed for children than for the entire U.S. population. Substantial state-level variation was projected in epidemic trajectories, vaccine benefits, and variant impacts. ConclusionsResults from this multi-model aggregation study suggest that, under a specific set of scenario assumptions, expanding vaccination to children 5-11 years old would provide measurable direct benefits to this age group and indirect benefits to the all-age U.S. population, including resilience to more transmissible variants.

COVID-SAFER: Deprescribing Guidance for Nirmatrelvir-ritonavir Drug Interactions in Older Adults

ImportanceOlder adults, at high-risk of developing complications from COVID-19, could benefit from nirmatrelvir-ritonavir, an oral antiviral treatment for outpatients at high risk of complications from COVID-19; however, due to its potent CYP3A4 inhibition, nirmatrelvir-ritonavir is associated with many drug-drug interactions (DDI). ObjectivesIdentify how common DDIs are between nirmatrelvir-ritonavir, common medications, and PIMs in older adults with polypharmacy. Craft anticipatory deprescribing guidance for PIMs that interact with nirmatrelvir-ritonavir to help prioritize deprescribing resources, and increase the proportion of older adults potentially benefitting from treatment. DesignIn this secondary analysis, we retrospectively analyzed all patients in the MedSafer cluster randomized deprescribing trial (N=5698 participants) to investigate the proportion of older adults (age >65) with polypharmacy ([≥]5 usual home medications) who would be ineligible for treatment with nirmatrelvir-ritonavir due to pre-existing DDIs. SettingThe setting of the primary study was in medical inpatient units at 11 Canadian acute care hospitals. ParticipantsHospitalized persons, age 65 years and older, on 5 or more daily home medications, with an expected survival of 3 months or longer were included in this secondary analysis. Main outcomes and measuresWe identified the prevalence of (PIMs), as defined by the MedSafer software. We then developed deprescribing guidance, so clinicians could proactively deprescribe in an effort to increase the proportion of older adults eligible for safe treatment with nirmatrelvir-ritonavir in the event of a SARS-CoV-2 infection. ResultsOf 5698 participants, a total of 3869 (68%) were taking a medication with a known nirmatrelvir-ritonavir DDI, and of these 823 (21%) had at least one PIM. Of 823 PIMs, 627 (76%) were medications with a known high risk DDI and 213 (26%) were considered moderate risk DDIs with nirmatrelvir-ritonavir. Many of the PIMs required "advanced deprescribing" and could not simply be stopped, held, or adjusted at the time of nirmatrelvir-ritonavir receipt. Conclusions and relevanceOlder adults are at high risk of developing severe complications from COVID-19. Deprescribing PIMs in advance of a COVID-19 infection could increase the proportion of older adults who can safely receive nirmatrelvir-ritonavir, in addition to the usual benefits observed with medication management. Impact StatementWe certify that this work is novel. This timely clinical investigation explores the unforeseen consequences of polypharmacy and the use of potentially inappropriate medication in older adults during the COVID-19 pandemic. This manuscript addresses the many drug-drug interactions between nirmatrelvir-ritonavir, an antiviral treatment for COVID-19, and potentially inappropriate medications in older adults with polypharmacy from the MedSafer cluster randomized trial. Our work highlights that the pandemic has created an even greater urgency to examine the medication lists of older adults and proactively deprescribe to improve the safety and tolerability of different COVID-19 treatments. Key PointsO_LIQuestion: How does polypharmacy affect the eligibility of older adults to receive Nirmatrelvir-ritonavir? C_LIO_LIFindings: 68% of older adults in the MedSafer cluster randomized trial had a DDI with nirmatrelvir-ritonavir, and 21% were taking at least 1 potentially inappropriate medication. C_LIO_LIMeaning: Due to its potent CYP3A4 inhibition, nirmatrelvir-ritonavir is associated with many drug-drug interactions (DDI). C_LI

Remdesivir for the Treatment of COVID-19: An Updated Systematic Review and Meta-Analysis

BackgroundThe benefits of remdesivir in the treatment of hospitalized patients with Covid-19 remain debated with the National Institutes of Health and the World Health Organization providing contradictory recommendations for and against use. MethodsWe performed a systematic review of randomized controlled trials (RCTs) of remdesivir for the treatment of hospitalized patients with COVID-19. The primary outcome was mortality, stratified by oxygen use (none, supplemental oxygen without mechanical ventilation, and mechanical ventilation). We conducted a frequentist random effects meta-analysis on the risk ratio (RR) scale and, to better contextualize the probabilistic benefits, we also performed a bayesian random effects meta-analysis on the risk difference scale. ResultsWe identified 8 randomized trials, totaling 9157 participants. The RR for mortality comparing remdesivir versus control was 0.71 (95% confidence interval [CI] 0.42-1.22; I2=0.0%) in the patients who did not require supplemental oxygen; 0.83 (95%CI 0.73-0.95; I2=0.0%) for nonventilated patients requiring oxygen; and 1.19 (95%CI 0.98-1.44 I2=0.0%) in the setting of mechanical ventilation. Using neutral priors, the probabilities that remdesivir reduces mortality were 74.7%, 96.9% and 8.9%, respectively. The probability that remdesivir reduced mortality by more than 1% was 88.1% for nonventilated patients requiring oxygen. ConclusionBased on this meta-analysis, there is a high probability that remdesivir reduces mortality for nonventilated patients with COVID-19 requiring supplemental oxygen therapy.

Sample Size Calculations for Variant Surveillance in the Presence of Biological and Systematic Biases

As demonstrated during the SARS-CoV-2 pandemic, detecting and tracking the emergence and spread of pathogen variants is an important component of monitoring infectious disease outbreaks. Pathogen genome sequencing has emerged as the primary tool for variant characterization, so it is important to consider the number of sequences needed when designing surveillance programs or studies, both to ensure accurate conclusions and to optimize use of limited resources. However, current approaches to calculating sample size for variant monitoring often do not account for the biological and logistical processes that can bias which infections are detected and which samples are ultimately selected for sequencing. In this manuscript, we introduce a framework that models the full process-- including potential sources of bias--from infection detection to variant characterization, and we demonstrate how to use this framework to calculate appropriate sample sizes for sequencing-based surveillance studies. We consider both cross-sectional and continuous sampling, and we have implemented our method in a publicly available tool that allows users to estimate necessary sample sizes given a specific aim (e.g., variant detection or measuring variant prevalence) and sampling method. Our framework is designed to be easy to use, while also flexible enough to be adapted to other pathogens and surveillance scenarios.

Diagnostic accuracy of Serum 1,5-anhydroglucitol as a surrogate measure of Glycemic variability among adult Filipinos with Type 2 Diabetes Mellitus: A retrospective cross-sectional study

Background@#Among the various glycemic indices in current use, glycemic variability has the greatest contribution in the development of microvascular and macrovascular complications in Type 2 Diabetes mellitus (T2DM). Most metrics that are currently used to measure glycemic variability are derived from continuous glucose monitoring (CGM) data. However, CGM is burdensome to the patient due to its relatively high cost as well as the need for multiple visits with the health care provider. With the use of serum 1,5-anhydroglucitol (1,5-AG) as a biomarker of glucose fluctuations, physicians and patients alike could have an easier surrogate measure of glycemic variability thus aiding in achieving target glucose control. This study aims to determine the diagnostic accuracy of 1,5-AG as compared to the glycemic variability metrics derived from CGM as a surrogate measure of glycemic variability among adult Filipinos with T2DM.@*Methods@#Retrospective analysis of data of adult patients aged 20 years old and above diagnosed with T2DM referred for CGM at the Diabetes, Endocrine, Metabolic, and Nutrition Center of Cardinal Santos Medical Center from January 2017 to October 2021 who underwent serum 1,5-AG level determination within 2 weeks of CGM were collected. Diagnostic accuracy was obtained by computing the sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and Youden index. Pearson correlation coefficient was used to determine the correlation of 1,5-AG and the different metrics. Analysis of variance (ANOVA) was used to check for statistical significance with 99% confidence interval and a p < 0.05 considered as statistically significant.@*Results@#This study involving 37 subjects showed a good diagnostic accuracy of serum 1,5-AG levels with the different measures of glycemic variability derived from CGM namely mean amplitude of glycemic excursion (MAGE), continuous overlapping net glycemic action at 1-hour intervals (CONGA-1), and mean of daily differences (MODD) with significant correlation among patients with HbA1c ≤ 7%. Subjects were on CGM for approximately 6 ± 1 day with statistically significant difference between the good and poor glucose control group (p<0.05). Determination of diagnostic accuracy between 1,5- AG and MAGE showed good accuracy (Sensitivity = 95.3%, Specificity = 100%, PPV = 100%, NPV = 75.43%, Diagnostic accuracy 96%, and a Youden Index of 92.3) with a statistically significant correlation among subjects with HbA1c level ≤ 7% (p=0.021). There is likewise good diagnostic accuracy between CONGA-1 and 1,5-AG level (Sensitivity = 99%, Specificity = 75.29%, PPV = 89.1%, NPV = 97%, Accuracy = 89.50% and Youden index of 58.41) with a statistically significant correlation among subjects with HbA1c ≤ 7% (p=0.038). Comparison with interday glycemic variability showed fair diagnostic accuracy between MODD and 1,5-AG (Sensitivity = 79.17%, Specificity = 78%, PPV = 97%, NPV = 32%, Accuracy = 76.89%, and Youden index of 49.07) and a statistically significant correlation among subjects with HbA1c ≤ 7% (p=0.009).@*Conclusion@#There is good diagnostic accuracy of serum 1,5-AG levels with the different measures of glycemic variability derived from CGM namely MAGE, CONGA-1, and MODD with significant correlation among patients with HbA1c ≤ 7%. Among diabetics with HbA1c ≤7%, 1,5-AG could be used as a surrogate measure of glycemic variability and excursions.

Evaluation and treatment of facial feminization surgery: part II. lips, midface, mandible, chin, and laryngeal prominence

Facial feminization surgery (FFS) refers to a set of procedures aimed at altering the features of a masculine face to achieve a more feminine appearance. In the second part of this twopart series, assessment and operations involving the midface, mandible, and chin, as well as soft tissue modification of the nasolabial complex and chondrolaryngoplasty, are discussed. Finally, we provide a review of the literature on patient-reported outcomes in this population following FFS and suggest a path forward to optimize care for FFS patients.

Fluvoxamine for Outpatient COVID-19 to Prevent Hospitalization: A Systematic Review and Meta-Analysis

ImportanceWidely available and affordable options for the outpatient management of COVID-19 are needed, particularly therapies that prevent hospitalization. ObjectivePerform a meta-analysis of the available randomized clinical trial evidence for fluvoxamine in the outpatient management of COVID-19. Data SourcesWorld Health Organization International Clinical Trials Registry Platform and ClinicalTrials.gov. Study SelectionCompleted outpatient trials with available results which compared fluvoxamine to placebo. Data Extraction and SynthesisWe followed the PRISMA 2020 guidelines. We extracted study details in terms of inclusion criteria, trial demographics and the pre-specified outcome of all-cause hospitalization. Risk of bias was assessed by the Cochrane Risk of Bias 2 tool. We conducted a frequentist random effects meta-analysis, as well as two sensitivity analyses using a Bayesian random effects meta-analysis with different estimates of prior probability: a weakly neutral prior (50% chance of efficacy with 95% confidence interval for Risk Ratio [RR] between 0.5 and 2) and a moderately optimistic prior (85% chance of efficacy). We contextualized the results by estimating the probability of any effect (RR [≤]1) and moderate effect (RR [≤]0.9) on reducing hospitalization. Main Outcome(s) and Measure(s)All cause hospitalization. Results2196 participants were included from 3 identified trials. The risk ratios for hospitalization were 0.75 (95%CI, 0.57-0.97) for the frequentist analysis, 0.78 (95%CI 0.58-1.08) for the Bayesian weakly neutral prior, and 0.73 (95%CI, 0.53-1.01) for the Bayesian moderately optimistic prior. Depending on the scenario, the probability of any effect on hospitalization ranged from 94.1% to 98.3% and a moderate effect from 81.6% to 91.1%. Conclusions and RelevanceUnder a variety of assumptions, fluvoxamine shows a high probability of preventing hospitalization in outpatients with COVID-19. While ongoing randomized trials are important to evaluate alternative doses, explore the effectiveness in vaccinated patients, and provide further refinement to these estimates, fluvoxamine could be recommended as a treatment option, particularly in resource-limited settings or persons without access to SARS-CoV-2 monoclonal antibody therapy or direct antivirals. Key PointsO_ST_ABSQuestionC_ST_ABSDoes early administration of fluvoxamine prevent hospitalization in symptomatic adult outpatients with confirmed COVID-19? FindingsIn this meta-analysis with Bayesian sensitivity analyses that accounted for varying prior probabilities, there was a high probability (94.1% to 98.3%) that fluvoxamine reduces hospitalization with frequentist risk ratio of 0.75 (95%CI 0.57-0.97). MeaningFluvoxamine is a widely available and inexpensive option that prevents hospitalization in patients with early COVID-19 based on randomized controlled trial evidence to date.

Outpatient therapies for COVID-19: How do we choose?

BackgroundSeveral outpatient COVID-19 therapies have reduced hospitalization in randomized controlled trials. The choice of therapy may depend on drug efficacy, toxicity, pricing, availability, and access to administration infrastructure. To facilitate comparative decision making, we evaluated the efficacy of each treatment in clinical trials and then estimated the associated cost per hospitalization prevented. MethodsWherever possible, we obtained relative risk for hospitalization from published randomized controlled trials. Otherwise, we extracted data from press releases, conference abstracts, government submissions, or preprints. If more than one study was published, the results were meta-analyzed. Using relative risk, we estimated the number needed to treat (NNT), assuming a baseline hospitalization risk of 5%. Drug pricing was based on Canadian formularies, government purchases, or manufacturer estimates. Administrative and societal costs were not included. Results will be updated online as new studies emerge or final publication numbers become available. ResultsAt a 5% risk of hospitalization the estimated NNTs were: 87 for colchicine, 80 for fluvoxamine, 72 for inhaled corticosteroids, 24 for nirmatrelvir/ritonavir, 25 for sotrovimab, 24 for remdesivir, 29 for casirivimab/imdevimab, 29 for bamlanivimab/etesevimab and 52 for molnupiravir. Colchicine, fluvoxamine, inhaled corticosteroids, and nirmatrelvir/ritonavir had cost per hospitalization prevented point estimates below the CIHI estimated cost of hospitalization ($23000). InterpretationCanada is fortunate to have access to several effective outpatient therapies to prevent COVID-19 hospitalization. Given differences in efficacy, toxicity, cost and administration complexities, this assessment serves as one tool to help guide policy makers and clinicians in their treatment selection.

COVID-19 booster vaccine attitudes and behaviors among university students and staff: the USC Trojan Pandemic Research Initiative

IntroductionAlthough COVID-19 vaccines significantly reduce morbidity and mortality, recent evidence suggests that immunity wanes after 6-9 months, and that a third vaccine dose could further reduce COVID-19 transmission and severe illness. However, previous studies have not assessed attitudes about getting booster doses. This study examined COVID-19 booster vaccine attitudes and behaviors among university students and staff in the fall of 2021. MethodsParticipants responded to an email invitation and completed electronic surveys. Results. In our sample, 96.2% of respondents indicated willingness to get a COVID-19 booster shot at least once per year. In both bivariate and multivariate analyses higher trust in science was associated with having higher odds of booster willingness. Those who identify as Black, on average, reported trusting science less than other racial/ethnic groups. ConclusionsOur findings demonstrate high willingness to receive a COVID-19 booster shot and highlight the importance of educational and motivational messages that focus on trust in science to increase willingness to get the COVID-19 booster. More research is needed to better understand the impact of cultural beliefs on booster willingness and vaccine hesitancy. This understanding will help determine what messages and populations to target to increase booster willingness in the future.

Transmission potential of vaccinated and unvaccinated persons infected with the SARS-CoV-2 Delta variant in a federal prison, July-August 2021

BackgroundThe extent to which vaccinated persons who become infected with SARS-CoV-2 contribute to transmission is unclear. During a SARS-CoV-2 Delta variant outbreak among incarcerated persons with high vaccination rates in a federal prison, we assessed markers of viral shedding in vaccinated and unvaccinated persons. MethodsConsenting incarcerated persons with confirmed SARS-CoV-2 infection provided mid-turbinate nasal specimens daily for 10 consecutive days and reported symptom data via questionnaire. Real-time reverse transcription-polymerase chain reaction (RT-PCR), viral whole genome sequencing, and viral culture was performed on these nasal specimens. Duration of RT-PCR positivity and viral culture positivity was assessed using survival analysis. ResultsA total of 978 specimens were provided by 95 participants, of whom 78 (82%) were fully vaccinated and 17 (18%) were not fully vaccinated. No significant differences were detected in duration of RT-PCR positivity among fully vaccinated participants (median: 13 days) versus those not fully vaccinated (median: 13 days; p=0.50), or in duration of culture positivity (medians: 5 days and 5 days; p=0.29). Among fully vaccinated participants, overall duration of culture positivity was shorter among Moderna vaccine recipients versus Pfizer (p=0.048) or Janssen (p=0.003) vaccine recipients. ConclusionsAs this field continues to develop, clinicians and public health practitioners should consider vaccinated persons who become infected with SARS-CoV-2 to be no less infectious than unvaccinated persons. These findings are critically important, especially in congregate settings where viral transmission can lead to large outbreaks.

Antibody decay, T cell immunity and breakthrough infections following two SARS-CoV-2 vaccine doses in infliximab- and vedolizumab-treated patients

We report SARS-CoV-2 vaccine-induced immunity and risk of breakthrough infections in patients with inflammatory bowel disease treated with infliximab, a commonly used anti-TNF drug and those treated with vedolizumab, a gut-specific antibody targeting integrin a4b7 that does not impact systemic immunity. In infliximab-treated patients, the magnitude of anti-SARS-CoV2 antibodies was reduced 4-6-fold. One fifth of both infliximab- and vedolizumab-treated patients did not mount a T cell response. Antibody half-life was shorter in infliximab-treated patients. Breakthrough SARS-CoV-2 infections occurred more frequently in infliximab-treated patients and the risk was predicted by the level of antibody response after second vaccine dose. Overall, recipients of two doses of the BNT162b2 vaccine had higher anti-SARS-CoV-2 antibody concentrations, higher seroconversion rates, shorter antibody half-life and less breakthrough infections compared to ChAdOx1 nCoV-19 vaccine recipients. Irrespective of biologic treatment, higher, more sustained antibody levels were observed in patients with a history of SARS-CoV-2 infection prior to vaccination. Patients treated with anti-TNF therapy should be offered third vaccine doses.

Inhaled Corticosteroids for Outpatients with Covid-19: A Meta-Analysis

The role of inhaled corticosteroids for outpatient COVID-19 is evolving. We meta-analyzed reported clinical trials and estimated probability of any effect and number needed to treat of 50 or 20 for symptom resolution by day 14 [100%, 99.8%, 93.1%] and hospitalization [89.3%, 72.9%, 26.7%] respectively.

Multiscale geometry and mechanics of lipid monolayer collapse.

Langmuir monolayers at gas/liquid interfaces provide a rich framework to investigate the interplay between multiscale geometry and mechanics. Monolayer collapse is investigated at a topological and geometric level by building a scale space M from experimental imaging data. We present a general lipid monolayer collapse phase diagram, which shows that wrinkling, folding, crumpling, shear banding, and vesiculation are a continuous set of mechanical states that can be approached by either tuning monolayer composition or temperature. The origin of the different mechanical states can be understood by investigating the monolayer geometry at two scales: fluorescent vs atomic force microscopy imaging. We show that an interesting switch in continuity occurs in passing between the two scales, CAFM∈MAFM≠CFM∈M. Studying the difference between monolayers that fold vs shear band, we show that shear banding is correlated to the persistence of a multi-length scale microstructure within the monolayer at all surface pressures. A detailed analytical geometric formalism to describe this microstructure is developed using the theory of structured deformations. Lastly, we provide the first ever finite element simulation of lipid monolayer collapse utilizing a direct mapping from the experimental image space M into a simulation domain P. We show that elastic dissipation in the form of bielasticity is a necessary and sufficient condition to capture loss of in-plane stability and shear banding.

Diagnosis and Acute Management of COVID-19 and Multisystem Inflammatory Syndrome in Children.

ABSTRACT: Most children with coronavirus disease 2019 (COVID-19) infection are asymptomatic or have mild disease. About 5% of infected children will develop severe or critical disease. Rapid identification and treatment are essential for children who are critically ill with signs and symptoms of respiratory failure, septic shock, and multisystem inflammatory syndrome in children. This article is intended for pediatricians, pediatric emergency physicians, and individuals involved in the emergency care of children. It reviews the current epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in children, summarizes key aspects of clinical assessment including identification of high-risk patients and manifestations of severe disease, and provides an overview of COVID-19 management in the emergency department based on clinical severity.

Understanding the onset of hot streaks across artistic, cultural, and scientific careers.

Across a range of creative domains, individual careers are characterized by hot streaks, which are bursts of high-impact works clustered together in close succession. Yet it remains unclear if there are any regularities underlying the beginning of hot streaks. Here, we analyze career histories of artists, film directors, and scientists, and develop deep learning and network science methods to build high-dimensional representations of their creative outputs. We find that across all three domains, individuals tend to explore diverse styles or topics before their hot streak, but become notably more focused after the hot streak begins. Crucially, hot streaks appear to be associated with neither exploration nor exploitation behavior in isolation, but a particular sequence of exploration followed by exploitation, where the transition from exploration to exploitation closely traces the onset of a hot streak. Overall, these results may have implications for identifying and nurturing talents across a wide range of creative domains.