Measuring the acceptability of EQ-5D-3L health states for different ages: a new adaptive survey methodology

Background Acceptable health and sufficientarianism are emerging concepts in health resource allocation. We defined acceptability as the proportion of the general population who consider a health state acceptable for a given age. Previous studies surveyed the acceptability of health problems separately per EQ-5D-3L domain, while the acceptability of health states with co-occurring problems was barely explored. Objective To quantify the acceptability of 243 EQ-5D-3L health states for six ages from 30 to 80 years: 1458 health state–age combinations (HAcs), denoted as the acceptability set of EQ-5D-3L. Methods In 2019, an online representative survey was conducted in the Hungarian general population. We developed a novel adaptive survey algorithm and a matching statistical measurement model. The acceptability of problems was evaluated separately per EQ-5D-3L domain, followed by joint evaluation of up to 15 HAcs. The selection of HAcs depended on respondents’ previous responses. We used an empirical Bayes measurement model to estimate the full acceptability set. Results 1375 respondents (female: 50.7%) were included with mean (SD) age of 46.7 (14.6) years. We demonstrated that single problems that were acceptable separately for a given age were less acceptable when co-occurring jointly (p < 0.001). For 30 years of age, EQ-5D-3L health states of ‘11112’ (11.9%) and ‘33333’ (1%), while for 80 years of age ‘21111’ (93.3%) and ‘33333’ (7.4%) had highest and lowest acceptability (% of population), respectively. Conclusion The acceptability set of EQ-5D-3L quantifies societal preferences concerning age and disease severity. Its measurement profiles and potential role in health resource allocation needs further exploration.

Insights Into Comparative Analyses and Phylogenomic Implications of Acer (Sapindaceae) Inferred From Complete Chloroplast Genomes

Acer L. (Sapindaceae) is one of the most diverse and widespread plant genera in the Northern Hemisphere. It comprises 124–156 recognized species, with approximately half being native to Asia. Owing to its numerous morphological features and hybridization, this genus is taxonomically and phylogenetically ranked as one of the most challenging plant taxa. Here, we report the complete chloroplast genome sequences of five Acer species and compare them with those of 43 published Acer species. The chloroplast genomes were 149,103–158,458 bp in length. We conducted a sliding window analysis to find three relatively highly variable regions (psbN-rps14, rpl32-trnL, and ycf1) with a high potential for developing practical genetic markers. A total of 76–103 SSR loci were identified in 48 Acer species. The positive selection analysis of Acer species chloroplast genes showed that two genes (psaI and psbK) were positively selected, implying that light level is a selection pressure for Acer species. Using Bayes empirical Bayes methods, we also identified that 20 cp gene sites have undergone positive selection, which might result from adaptation to specific ecological niches. In phylogenetic analysis, we have reconfirmed that Acer pictum subsp. mono and A. truncatum as sister species. Our results strongly support the sister relationships between sections Platanoidea and Macrantha and between sections Trifoliata and Pentaphylla. Moreover, series Glabra and Arguta are proposed to promote to the section level. The chloroplast genomic resources provided in this study assist taxonomic and phylogenomic resolution within Acer and the Sapindaceae family.

Safety Evaluation of Pedestrian Countdown Signals: Definitive Results from Two Cities in the United States

The pedestrian countdown signals (PCS) treatment involves the display of a numerical countdown that shows how many seconds are left in the flashing DON’T WALK interval. Although many studies have attempted to evaluate the safety of PCS, the results have been inconsistent for many reasons, including inadequate sample size and the inability to control for possible bias from regression to the mean and from exposure. This study performed a before-after empirical Bayes analysis using data from 115 treated intersections in Charlotte, North Carolina and 218 treated intersections in Philadelphia, Pennsylvania to evaluate the safety effects of PCS. The evaluation also included 136 reference intersections in Charlotte, and 597 reference intersections in Philadelphia. Following the implementation of PCS, total crashes decreased by approximately 8% and rear-end crashes decreased by approximately 12%, and these reductions were statistically significant at the 95% confidence level. Pedestrian crashes decreased by about 9% and this reduction was statistically significant at the 90% confidence level. Economic analysis revealed a benefit-cost ratio of 23 with a low of 13 and a high of 32.

Kidney Injury Following Ibuprofen and Acetaminophen: A Real-World Analysis of Post-Marketing Surveillance Data

Background: Although kidney injury has been reported as a serious adverse effect in patients treated with ibuprofen or acetaminophen (APAP), there are still few real-world studies to compare the specific differences in the adverse effects of nephrotoxicity.Methods: Disproportionality analysis and Bayesian analysis were devoted to data-mining of the suspected kidney injury after using ibuprofen and APAP based on the FDA’s Adverse Event Reporting System (FAERS) from January 2004 to March 2021. The times to onset, fatality, and hospitalization rates of ibuprofen-associated kidney injury and APAP-associated kidney injury were also investigated.Results: 2,453 reports of ibuprofen-associated kidney injury and 1,288 reports of APAP-associated kidney injury were identified. Ibuprofen appeared to affected more middle-aged patients than elderly ones (27.76 vs 16.53%) while APAP appeared to affected more young patients than middle-aged patients (45.24 vs 29.10%) and elderly patients were fewer (13.99%). Compared to ibuprofen, APAP had the higher association with renal injury based on the higher reporting odds ratio (ROR = 2.45, 95% two-sided CI = 2.36–2.56), proportional reporting ratio (PRR = 2.39, χ2 = 2002.94) and empirical Bayes geometric mean (EBGM = 2.38, 95% one-sided CI = 2.3). In addition, APAP-associated kidney injury had earlier onset (32.74 vs 115.82 days, p &lt; 0.0001) and a higher fatality rate (44.43 vs 7.36%, p &lt; 0.001) than those of ibuprofen-associated kidney injury.Conclusion: The analysis of FAERS data provides a more accurate profile on the incidence and prognosis of kidney injury after ibuprofen and acetaminophen treatment, enabling continued surveillance and timely intervention in patients at risk of kidney injury using these drugs.

Credible School Value-Added with Undersubscribed School Lotteries

We introduce two empirical strategies harnessing the randomness in school assignment mechanisms to measure school value-added. The first estimator controls for the probability of school assignment, treating take-up as ignorable. We test this assumption using randomness in assignments. The second approach uses assignments as instrumental variables (IVs) for low-dimensional models of value-added and forms empirical Bayes posteriors from these IV estimates. Both strategies solve the underidentification challenge arising from school undersubscription. Models controlling for assignment risk and lagged achievement in Denver and New York City yield reliable value-added estimates. Estimates from models with lower-quality achievement controls are improved by IV.

Batch effect reduction of microarray data with dependent samples using an empirical Bayes approach (BRIDGE)

Batch-effects present challenges in the analysis of high-throughput molecular data and are particularly problematic in longitudinal studies when interest lies in identifying genes/features whose expression changes over time, but time is confounded with batch. While many methods to correct for batch-effects exist, most assume independence across samples; an assumption that is unlikely to hold in longitudinal microarray studies. We propose Batch effect Reduction of mIcroarray data with Dependent samples usinG Empirical Bayes (BRIDGE), a three-step parametric empirical Bayes approach that leverages technical replicate samples profiled at multiple timepoints/batches, so-called “bridge samples”, to inform batch-effect reduction/attenuation in longitudinal microarray studies. Extensive simulation studies and an analysis of a real biological data set were conducted to benchmark the performance of BRIDGE against both ComBat and longitudinal ComBat. Our results demonstrate that while all methods perform well in facilitating accurate estimates of time effects, BRIDGE outperforms both ComBat and longitudinal ComBat in the removal of batch-effects in data sets with bridging samples, and perhaps as a result, was observed to have improved statistical power for detecting genes with a time effect. BRIDGE demonstrated competitive performance in batch effect reduction of confounded longitudinal microarray studies, both in simulated and a real data sets, and may serve as a useful preprocessing method for researchers conducting longitudinal microarray studies that include bridging samples.

Looking from the top: enhanced top-down sensorimotor processing in somatic anxiety

BackgroundFunctional neuroimaging research on anxiety has traditionally focused on brain networks associated with the complex psychological aspects of anxiety. In this study, instead, we target the somatic aspects of anxiety. Motivated by the growing recognition that top-down cortical processing plays crucial roles in perception and action, we investigate effective connectivity among hierarchically organized sensorimotor regions and its association with (trait) anxiety.MethodsWe selected 164 participants from the Human Connectome Project based on psychometric measures. We used their resting-state functional MRI data and Dynamic Causal Modeling (DCM) to assess effective connectivity within and between key regions in the exteroceptive, interoceptive, and motor hierarchy. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes we first established the architecture of effective connectivity in sensorimotor networks and investigated its association with fear somatic arousal (FSA) and fear affect (FA) scores. To probe the robustness of our results, we implemented a leave-one-out cross validation analysis.ResultsAt the group level, the top-down connections in exteroceptive cortices were inhibitory in nature whereas in interoceptive and motor cortices they were excitatory. With increasing FSA scores, the pattern of top-down effective connectivity was enhanced in all three networks: an observation that corroborates well with anxiety phenomenology. Anxiety associated changes in effective connectivity were of effect size sufficiently large to predict whether somebody has mild or severe somatic anxiety. Interestingly, the enhancement in top-down processing in sensorimotor cortices were associated with FSA but not FA scores, thus establishing the (relative) dissociation between somatic and cognitive dimensions of anxiety.ConclusionsOverall, enhanced top-down effective connectivity in sensorimotor cortices emerges as a promising and quantifiable candidate marker of trait somatic anxiety. These results pave the way for a novel approach into investigating the neural underpinnings of anxiety based on the recognition of anxiety as an embodied phenomenon and the emerging interest in top-down cortical processing.