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Introduction: This study surveyed adult emergency department (ED) patients and the adult companions of pediatric patients to determine whether rates of coronavirus disease 2019 (COVID-19) vaccination were comparable to that of the general population in the region. This study also sought to identify self-reported barriers to vaccination and possible areas for intervention.Methods: A survey was administered to 607 adult ED patients or the adult companions of pediatric patients from three different regional hospitals to assess their COVID-19 vaccination status, COVID-19 vaccine barriers, and demographic information.Results: Of the 2,267 adult patients/companions considered for enrollment, we approached 730 individuals about participating in the study. Of the individuals approached, 607 (41% male; mean age 47.0+17.4 years) consented to participate. A total of 403 (66.4%) participants had received at least one vaccine dose as compared to 70% of the adult population in the county where the three hospitals were located. Of those, 382 (94.8%) were fully vaccinated and among the individuals who were partially vaccinated the majority (17 of 21) had an appointment for their second dose. Of those approached, 204 (33.6%) were not vaccinated, with 66 (10.9% of the total population) expressing an interest in becoming vaccinated while the remaining 138 did not want to be vaccinated. Of those who wanted to be vaccinated 32% were waiting for more safety data, and of those who did not want to be vaccinated 26% were concerned about side effects and risks and 28% were waiting for more safety data.Conclusion: Adult ED patients and adult companions of pediatric ED patients were vaccinated at a slightly lower rate than the general population in our county. A small but significant proportion of those who were unvaccinated expressed the desire to be vaccinated, indicating that the ED may be a suitable location to introduce a COVID-19 vaccination program.

Background Inhaled nitric oxide (iNO) is being increasingly used in preterm infants

In clinical studies focusing on paired body parts, diseases can manifest on either both sides (bilateral) or just one side (unilateral) of the organs. Consequently, the data in these studies may consist of records from both bilateral and unilateral cases. There are two different methods of analyzing the data. One of the methods is assuming that the pair of measurements from the same subject are independent, while the other considers the correlation between paired organs. In terms of the homogeneity test of proportions, asymptotic methods have been proposed given the moderate size of data. This article extends the existing work by proposing exact methods to deal with the scenarios when the sample size is small and asymptotic methods perform poorly. The impact of the correlation assumption is also explored. Among the proposed methods, calculating p-values by replacing unknown parameters with estimated values while accounting for the correlation is recommended based on its satisfactory type I error controls and statistical powers. The proposed methods are applied to three real examples for illustration. [ABSTRACT FROM AUTHOR]

Engineered Escherichia coli (E. coli) strains have been widely used to produce isotopically labeled peptides for NMR characterization on their structures and interactions. However, production of antimicrobial peptides (AMPs) by E. coli is still challenging, because AMPs are toxic to E. coli host and would lead to cell death after induction. On the other hand, expression of short peptides in E. coli host often encounter problems of the short in vivo lifetime of the peptides, which were rapidly degraded by endogenous enzymes during expression and purification steps. This report presents a practical method for overcoming these bottlenecks to enable E. coli to express AMPs and peptides that have short in vivo lifetime. This design uses the fusion of thioredoxin tags at both the N‐ and C‐termini of the target peptides. The steric effect of the large soluble tags at both ends of the peptide reduces peptide accessibility, thereby enhancing their in vivo stability and eliminating the toxicity associated with AMPs. The approach was validated using an AMP A3K/L7K‐LAH4 (K3K7) and a membrane fusion peptide (FP), which is a segment of the spike protein of SARS‐CoV‐2 and functions in fusing viral membranes and host cell membranes. Fusion expression of K3K7 with a thioredoxin tag only at the N‐terminal resulted in high toxicity to the host cells, leading to impaired cell growth and a failure to obtain expressed fusion protein. In contrast, the fusion proteins from both termini were successfully expressed and purified. In the case of the FP, the fusion of thioredoxin at both termini significantly enhanced its stability, protecting it from enzymatic degradation during expression and purification steps. On the contrary, the FP with thioredoxin fused only at the N‐terminal was found to be unstable in E. coli host strains. As stable isotope labeling on peptide is essentially important in NMR‐based structure and interaction studies, we also demonstrated that the developed approach enables efficient 15N labeling for NMR studies. This strategy may also be extended to produce other challenging peptides. [ABSTRACT FROM AUTHOR]

Intraclass correlation in bilateral data has been investigated in recent decades with various statistical methods. In practice, stratifying bilateral data by some control variables will provide more sophisticated statistical results to satisfy different research proposed in randomized clinical trials. In this article, we propose three test statistics (the likelihood ratio test, score test, and Wald-type test statistics) to evaluate the homogeneity of proportion ratios for stratified bilateral correlated data under an equal correlation assumption. Monte Carlo simulations of Type I error and power are performed, and the score test yields a robust outcome based on empirical Type I error and power. Lastly, two real data examples are conducted to illustrate the proposed three tests. [ABSTRACT FROM AUTHOR]

In clinical research, data are commonly collected bilaterally from paired organs or bodily parts within individual subjects. However, unilateral data arise when constraints or limiting factors impede the collection of complete bilateral data. In this article, we propose three large-sample tests and five confidence interval methods for making inferences on the common treatment effect, measured by the odds ratio, in a stratified design under integrated bilateral and unilateral data. Our simulation results show that the likelihood ratio-based and score-based tests, along with their associated confidence interval methods, demonstrate robust control of type I error and close-to-nominal coverage probabilities. We apply the proposed methods to real-world datasets of acute otitis media and myopic eyes to showcase their validity and applicability in clinical practice. [ABSTRACT FROM AUTHOR]

Abstract Background Batch effect is one type of variability that is not of primary interest but ubiquitous in sizable genomic experiments. To minimize the impact of batch effects, an ideal experiment design should ensure the even distribution of biological groups and confounding factors across batches. However, due to the practical complications, the availability of the final collection of samples in genomics study might be unbalanced and incomplete, which, without appropriate attention in sample-to-batch allocation, could lead to drastic batch effects. Therefore, it is necessary to develop effective and handy tool to assign collected samples across batches in an appropriate way in order to minimize the impact of batch effects. Results We describe OSAT (Optimal Sample Assignment Tool), a bioconductor package designed for automated sample-to-batch allocations in genomics experiments. Conclusions OSAT is developed to facilitate the allocation of collected samples to different batches in genomics study. Through optimizing the even distribution of samples in groups of biological interest into different batches, it can reduce the confounding or correlation between batches and the biological variables of interest. It can also optimize the homogeneous distribution of confounding factors across batches. It can handle challenging instances where incomplete and unbalanced sample collections are involved as well as ideally balanced designs.

Objective  This study aimed to compare short-term respiratory outcomes of three steroids (dexamethasone, hydrocortisone, and methylprednisolone) to facilitate extubation by improving respiratory status in preterm infants. Study Design  This is a retrospective, single-center, cohort study of 98 intubated preterm infants ≤34 6/7  weeks' gestation, admitted to a 64-bed, level III neonatal intensive care unit at the Women & Children's Hospital of Buffalo, Buffalo, NY, between 2006 and 2012, who received a short course of low-dose steroids for lung disease after first week of life. Results  Study infants received dexamethasone (34%), hydrocortisone (44%), or methylprednisolone (22%) based on clinical team preference. By day 7 after initiation of steroids, extubation occurred in 59, 44, and 41%, respectively, in infants on dexamethasone, hydrocortisone, and methylprednisolone (p  = 0.3). The mean respiratory severity score (RSS = fraction of inspired oxygen × mean airway pressure), a quantitative measure of respiratory status, decreased by 44% for all infants and by 59% in the dexamethasone group by day 7. Conclusion  Steroids improved short-term respiratory outcomes in all infants (RSS and extubation); by day 7, dexamethasone treatment was associated with the greatest decrease in RSS. Additional prospective, randomized trials of short-course low-dose steroids are warranted to substantiate these findings to guide clinical decision making and in evaluating differential steroid effects on long-term neurodevelopmental outcomes. [ABSTRACT FROM AUTHOR]

Byline: Changxing Ma, Kai-Tai Fang The uniform design is one of space filling designs and has been widely used in computer and industrial experiments. Many methods for construction of uniform designs or nearly uniform designs, such as the glp method, optimisation method etc., have been proposed. A nearly uniform design is a design with low-discrepancy, where the discrepancy is a measure of uniformity. Various discrepancies have been suggested. To find a uniform design for n runs and s factors under a given discrepancy is a NP hard problem in the sense of computation complexity when n → ∞ and s > 1. In this paper, we propose a new method, called the cutting method, for construction of nearly uniform designs. It shows that the computation load of the new method is light and designs obtained by the new approach have better uniformity.

OBJECTIVE. The purpose of this study is to provide a race-and gender-specific model for predicting 1-year survival rates for extremely low birth weight (ELBW) infants by using population-based data. METHODS. Birth and death certificates were analyzed for all children (N = 5076) with birth weights between 300 g and 1000 g who were born in Florida between 1996 and 2000. Semiparametric, multivariate, logistic regression analysis was used to model 1-year survival probabilities as a function of birth weight, gestational age, mother's race, and infant's gender. Estimated survival rates among different race/gender groups were compared by using odds ratios (ORs). RESULTS. One-year survival rates for 5076 ELBW infants born between 1996 and 2000 did not change during the 5-year period (60-62%). The survival rate at [less than or equal to]500 g was [less than or equal to]14% (n = 716). Survival rates at 501 to 600 g and 601 to 700 g were 36% and 62%, respectively. The survival rate reached >85% for infants of >800 g. Modeling indicated a survival advantage for female infants, compared with male infants (OR: 1.7; 95% confidence interval: 1.5-1.9), and for black infants, compared with white infants (OR: 1.3; 95% confidence interval: 1.1-1.5). Black female infants had 2.1 greater odds of survival than did white male infants. CONCLUSIONS. This population-based study highlights the significant race and gender differences in 1-year survival rates for ELBW infants, as well as the interactions of these 2 factors. These findings can assist obstetricians and neonatologists not only in the care of ELBW infants but also in frank discussions with families. KEY WORDS. birth weight-specific mortality rate, low birth weight infant, infant death. URL: www.pediatrics.org/cgi/doi/10.1542/peds.2005-1286

The activity of a new treatment in clinical trials with binary endpoints can be assessed by comparing the observed response rate to the target response rate. Traditionally, a one-sided hypothesis is used to make statistical inference, and the actual Type I error rate has to be computed over the parameter space of the null hypothesis. The monotonicity property is a fundamental property that guarantees the actual Type I error rate occurring at the boundary. One-arm two-stage designs are considered in this article. We theoretically proved this important property when the final threshold value of a design is less than the first-stage sample size together with another weak condition being satisfied. The method used in this article may finally lead to the final complete proof of this property in the future. We also numerically proved that the monotonicity property is satisfied for designs with the first-stage and the second-stage sample sizes from 10 to 100. [ABSTRACT FROM PUBLISHER]