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BackgroundAlthough social factors influence uptake of preventive services, the association between social needs and influenza vaccination has not been comprehensively evaluated for adults seeking primary care in the USA.ObjectiveTo determine the association between unmet social needs and influenza vaccination.DesignRetrospective, cross-sectional, multivariable logistic regression.ParticipantsPersons completing ambulatory visits in a primary care department at a midwestern, urban, multispecialty, academic medical center between July 2017 and July 2019 (N = 7955 individuals included).Main MeasuresCompletion of influenza vaccination in the 2018–2019 influenza season (primary outcome) or any year (secondary outcome) against 11 essential social needs (childcare, companionship, food security, health literacy, home safety, neighborhood safety, housing, health care provider costs, prescription costs, transportation, and utilities). Demographics, diabetic status, COPD, smoking status, office visit frequency, and hierarchical condition category risk scores were included as covariates.Key ResultsIndividuals with transportation vulnerability were less likely to be vaccinated against influenza (current-year aOR 0.65, 95% CI: 0.53–0.78, p < 0.001; any-year aOR 0.58, 95% CI: 0.47–0.71, p < 0.001). Poor health literacy promoted any-year, but not current-year, influenza vaccination (any-year aOR 1.30, 95% CI: 1.01–1.69, p = 0.043). Older age, female sex, diabetes, more comorbidities, and more frequent primary care visits were associated with greater influenza vaccination. Persons with Black or other/multiple race and current smokers were less frequently vaccinated.ConclusionsTransportation vulnerability, health literacy, smoking, age, sex, race, comorbidity, and office visit frequency are associated with influenza vaccination. Primary care–led interventions should consider these factors when designing outreach interventions.Trial RegistrationNot applicable

Background Opportunities to practice procedural skills in the clinical learning environment are decreasing, and faculty time to coach skills is limited, even in simulation-based training. Self-directed learning with hands-on practice early in a procedural skill course might help maximize the benefit of later faculty coaching and clinical experience. However, it may also lead to well-learned errors if learners lack critical guidance. The present study sought to investigate the effects of a hands-on, self-directed “study hall” for central line insertion among first-year residents. Methods Learner cohorts before vs. after introduction of the study hall ( n  = 49) were compared on their pre- and post-test performance of key procedural behaviors that were comparable across cohorts, with all learners receiving traditional instructor-led training between tests. Results Study hall participants spent a median of 116 min in hands-on practice (range 57–175). They scored higher at pre-test (44% vs. 27%, p  = .00; Cohen’s d  = 0.95) and at post-test (80% vs. 72%, p  = .02; Cohen’s d  = 0.69). A dose–response relationship was found, such that 2 h of study hall were roughly equivalent to the performance improvement seen with four clinical observations or supervised insertions of central lines. Conclusions Self-directed, hands-on “study hall” supported improved procedural skill learning in the context of limited faculty availability. Potential additional benefits make the approach worth further experimentation and evaluation.

Professional athletes undergo annual pre-season laboratory screening, although clinical evidence supporting the practice is limited and no uniform set of guidelines on pre-season laboratory screening exists. The aim of this study was to assess the clinical value of annual pre-season laboratory screening tests for a major professional sports team over multiple years. Retrospective chart review. A retrospective analysis was performed of all laboratory results as well as screening ECGs for a single major professional sports team over a 9-year timeframe (2009–2017). The data show that 10.01% of initial screening test results were abnormal and 40.32% of abnormal tests resulted in additional testing. Overall, only 0.35% of initial tests resulted in a clinically significant outcome. Non-US born players showed a significantly higher average rate of abnormal tests/year compared to US-born players (p-value 0.006), but there was no difference in clinically significant outcomes. There was no relationship between athlete age and laboratory screening outcomes. In our study population, yearly pre-season laboratory screening of professional athletes did not yield substantial clinically significant outcomes and would not be warranted under normal clinical standards. Future best practice guidelines should combine research concerning effects of family medical history, race, gender, country of origin, and type of sport on athlete health when creating recommendations for which pre-season laboratory screenings may be pertinent even with evidence of little utility.

Previous assessments have highlighted that less than a quarter of countries are on track to achieve Millennium Development Goal 4 (MDG 4), which calls for a two-thirds reduction in mortality in children younger than 5 years between 1990 and 2015. In view of policy initiatives and investments made since 2000, it is important to see if there is acceleration towards the MDG 4 target. We assessed levels and trends in child mortality for 187 countries from 1970 to 2010. We compiled a database of 16 174 measurements of mortality in children younger than 5 years for 187 countries from 1970 to 2009, by use of data from all available sources, including vital registration systems, summary birth histories in censuses and surveys, and complete birth histories. We used Gaussian process regression to generate estimates of the probability of death between birth and age 5 years. This is the first study that uses Gaussian process regression to estimate child mortality, and this technique has better out-of-sample predictive validity than do previous methods and captures uncertainty caused by sampling and non-sampling error across data types. Neonatal, postneonatal, and childhood mortality was estimated from mortality in children younger than 5 years by use of the 1760 measurements from vital registration systems and complete birth histories that contained specific information about neonatal and postneonatal mortality. Worldwide mortality in children younger than 5 years has dropped from 11·9 million deaths in 1990 to 7·7 million deaths in 2010, consisting of 3·1 million neonatal deaths, 2·3 million postneonatal deaths, and 2·3 million childhood deaths (deaths in children aged 1–4 years). 33·0% of deaths in children younger than 5 years occur in south Asia and 49·6% occur in sub-Saharan Africa, with less than 1% of deaths occurring in high-income countries. Across 21 regions of the world, rates of neonatal, postneonatal, and childhood mortality are declining. The global decline from 1990 to 2010 is 2·1% per year for neonatal mortality, 2·3% for postneonatal mortality, and 2·2% for childhood mortality. In 13 regions of the world, including all regions in sub-Saharan Africa, there is evidence of accelerating declines from 2000 to 2010 compared with 1990 to 2000. Within sub-Saharan Africa, rates of decline have increased by more than 1% in Angola, Botswana, Cameroon, Congo, Democratic Republic of the Congo, Kenya, Lesotho, Liberia, Rwanda, Senegal, Sierra Leone, Swaziland, and The Gambia. Robust measurement of mortality in children younger than 5 years shows that accelerating declines are occurring in several low-income countries. These positive developments deserve attention and might need enhanced policy attention and resources. Bill & Melinda Gates Foundation.

Spatial representations of threatening processes - \"threat maps\" - can identify where biodiversity is at risk, and are often used to identify priority locations for conservation. In doing so, decision makers are prone to making errors, either by assuming that the level of threat dictates spatial priorities for action or by relying primarily on the location of mapped threats to choose possible actions. We show that threat mapping can be a useful tool when incorporated within a transparent and repeatable structured decision-making (SDM) process. SDM ensures transparent and defendable conservation decisions by linking objectives to biodiversity outcomes, and by considering constraints, consequences of actions, and uncertainty. If used to make conservation decisions, threat maps are best developed with an understanding of how species respond to actions that mitigate threats. This approach will ensure that conservation actions are prioritized where they are most cost-effective or have the greatest impact, rather than where threat levels are highest.

The analysis of apex predator diet has the ability to deliver valuable insights into ecosystem health, and the potential impacts a predator might have on commercially relevant species. The Australian sea lion (Neophoca cinerea) is an endemic apex predator and one of the world's most endangered pinnipeds. Given that prey availability is vital to the survival of top predators, this study set out to understand what dietary information DNA metabarcoding could yield from 36 sea lion scats collected across 1,500 km of its distribution in southwest Western Australia. A combination of PCR assays were designed to target a variety of potential sea lion prey, including mammals, fish, crustaceans, cephalopods, and birds. Over 1.2 million metabarcodes identified six classes from three phyla, together representing over 80 taxa. The results confirm that the Australian sea lion is a wide‐ranging opportunistic predator that consumes an array of mainly demersal fauna. Further, the important commercial species Sepioteuthis australis (southern calamari squid) and Panulirus cygnus (western rock lobster) were detected, but were present in <25% of samples. Some of the taxa identified, such as fish, sharks and rays, clarify previous knowledge of sea lion prey, and some, such as eel taxa and two gastropod species, represent new dietary insights. Even with modest sample sizes, a spatial analysis of taxa and operational taxonomic units found within the scat shows significant differences in diet between many of the sample locations and identifies the primary taxa that are driving this variance. This study provides new insights into the diet of this endangered predator and confirms the efficacy of DNA metabarcoding of scat as a noninvasive tool to more broadly define regional biodiversity. The Australian sea lion is an endangered apex predator which is endemic to Western Australia. We collected and extracted the DNA from 36 scats taken from five known sea lion haul out locations around the southeast coast of Western Australia. Several assays were used to target barcode sequences to both identify the diet of the sea lions and gain insight into the biodiversity of their habitats.

Before 2020, mental disorders were leading causes of the global health-related burden, with depressive and anxiety disorders being leading contributors to this burden. The emergence of the COVID-19 pandemic has created an environment where many determinants of poor mental health are exacerbated. The need for up-to-date information on the mental health impacts of COVID-19 in a way that informs health system responses is imperative. In this study, we aimed to quantify the impact of the COVID-19 pandemic on the prevalence and burden of major depressive disorder and anxiety disorders globally in 2020. We conducted a systematic review of data reporting the prevalence of major depressive disorder and anxiety disorders during the COVID-19 pandemic and published between Jan 1, 2020, and Jan 29, 2021. We searched PubMed, Google Scholar, preprint servers, grey literature sources, and consulted experts. Eligible studies reported prevalence of depressive or anxiety disorders that were representative of the general population during the COVID-19 pandemic and had a pre-pandemic baseline. We used the assembled data in a meta-regression to estimate change in the prevalence of major depressive disorder and anxiety disorders between pre-pandemic and mid-pandemic (using periods as defined by each study) via COVID-19 impact indicators (human mobility, daily SARS-CoV-2 infection rate, and daily excess mortality rate). We then used this model to estimate the change from pre-pandemic prevalence (estimated using Disease Modelling Meta-Regression version 2.1 [known as DisMod-MR 2.1]) by age, sex, and location. We used final prevalence estimates and disability weights to estimate years lived with disability and disability-adjusted life-years (DALYs) for major depressive disorder and anxiety disorders. We identified 5683 unique data sources, of which 48 met inclusion criteria (46 studies met criteria for major depressive disorder and 27 for anxiety disorders). Two COVID-19 impact indicators, specifically daily SARS-CoV-2 infection rates and reductions in human mobility, were associated with increased prevalence of major depressive disorder (regression coefficient [B] 0·9 [95% uncertainty interval 0·1 to 1·8; p=0·029] for human mobility, 18·1 [7·9 to 28·3; p=0·0005] for daily SARS-CoV-2 infection) and anxiety disorders (0·9 [0·1 to 1·7; p=0·022] and 13·8 [10·7 to 17·0; p<0·0001]. Females were affected more by the pandemic than males (B 0·1 [0·1 to 0·2; p=0·0001] for major depressive disorder, 0·1 [0·1 to 0·2; p=0·0001] for anxiety disorders) and younger age groups were more affected than older age groups (−0·007 [–0·009 to −0·006; p=0·0001] for major depressive disorder, −0·003 [–0·005 to −0·002; p=0·0001] for anxiety disorders). We estimated that the locations hit hardest by the pandemic in 2020, as measured with decreased human mobility and daily SARS-CoV-2 infection rate, had the greatest increases in prevalence of major depressive disorder and anxiety disorders. We estimated an additional 53·2 million (44·8 to 62·9) cases of major depressive disorder globally (an increase of 27·6% [25·1 to 30·3]) due to the COVID-19 pandemic, such that the total prevalence was 3152·9 cases (2722·5 to 3654·5) per 100 000 population. We also estimated an additional 76·2 million (64·3 to 90·6) cases of anxiety disorders globally (an increase of 25·6% [23·2 to 28·0]), such that the total prevalence was 4802·4 cases (4108·2 to 5588·6) per 100 000 population. Altogether, major depressive disorder caused 49·4 million (33·6 to 68·7) DALYs and anxiety disorders caused 44·5 million (30·2 to 62·5) DALYs globally in 2020. This pandemic has created an increased urgency to strengthen mental health systems in most countries. Mitigation strategies could incorporate ways to promote mental wellbeing and target determinants of poor mental health and interventions to treat those with a mental disorder. Taking no action to address the burden of major depressive disorder and anxiety disorders should not be an option. Queensland Health, National Health and Medical Research Council, and the Bill and Melinda Gates Foundation.

Tumor-specific CD8+ T cells (TST) in patients with cancer are dysfunctional and unable to halt cancer progression. TST dysfunction, also known as exhaustion, is thought to be driven by chronic T cell antigen receptor (TCR) stimulation over days to weeks. However, we know little about the interplay between CD8 + T cell function, cell division and epigenetic remodeling within hours of activation. Here, we assessed early CD8 + T cell differentiation, cell division, chromatin accessibility and transcription in tumor-bearing mice and acutely infected mice. Surprisingly, despite robust activation and proliferation, TST had near complete effector function impairment even before undergoing cell division and had acquired hallmark chromatin accessibility features previously associated with later dysfunction/exhaustion. Moreover, continued tumor/antigen exposure drove progressive epigenetic remodeling, ‘imprinting’ the dysfunctional state. Our study reveals the rapid divergence of T cell fate choice before cell division in the context of tumors versus infection. Rudloff et al. examine the kinetics of CD8 + T cell dysfunction/exhaustion. Tumor-specific CD8 + T cells in the tumor environment exhibit epigenetic modifications within hours, before cell division. The findings suggest a temporal relationship between tumor antigen exposure, chromatin remodeling and dysfunction ‘imprinting’.

Immune checkpoint inhibitor-mediated colitis (IMC) is a common adverse event of treatment with immune checkpoint inhibitors (ICI). We hypothesize that genetic susceptibility to Crohn’s disease (CD) and ulcerative colitis (UC) predisposes to IMC. In this study, we first develop a polygenic risk scores for CD (PRS CD ) and UC (PRS UC ) in cancer-free individuals and then test these PRSs on IMC in a cohort of 1316 patients with ICI-treated non-small cell lung cancer and perform a replication in 873 ICI-treated pan-cancer patients. In a meta-analysis, the PRS UC predicts all-grade IMC (OR meta =1.35 per standard deviation [SD], 95% CI = 1.12–1.64, P  = 2×10 −03 ) and severe IMC (OR meta =1.49 per SD, 95% CI = 1.18–1.88, P  = 9×10 −04 ). PRS CD is not associated with IMC. Furthermore, PRS UC predicts severe IMC among patients treated with combination ICIs (OR meta =2.20 per SD, 95% CI = 1.07–4.53, P  = 0.03). Overall, PRS UC can identify patients receiving ICI at risk of developing IMC and may be useful to monitor patients and improve patient outcomes. Colitis is one of the most common immune-related adverse events in patients with cancer treated with immune checkpoint inhibitors. Here the authors show that a polygenic risk score for ulcerative colitis can predict immune checkpoint inhibitor-mediated colitis in patients with cancer.

Researchers are increasingly using insights derived from large-scale, electronic healthcare data to inform drug development and provide human validation of novel treatment pathways and aid in drug repurposing/repositioning. The objective of this study was to determine whether treatment of patients with multiple sclerosis with dimethyl fumarate, an activator of the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway, results in a change in incidence of type 2 diabetes and its complications. This retrospective cohort study used administrative claims data to derive four cohorts of adults with multiple sclerosis initiating dimethyl fumarate, teriflunomide, glatiramer acetate or fingolimod between January 2013 and December 2018. A causal inference frequentist model averaging framework based on machine learning was used to compare the time to first occurrence of a composite endpoint of type 2 diabetes, cardiovascular disease or chronic kidney disease, as well as each individual outcome, across the four treatment cohorts. There was a statistically significantly lower risk of incidence for dimethyl fumarate versus teriflunomide for the composite endpoint (restricted hazard ratio [95% confidence interval] 0.70 [0.55, 0.90]) and type 2 diabetes (0.65 [0.49, 0.98]), myocardial infarction (0.59 [0.35, 0.97]) and chronic kidney disease (0.52 [0.28, 0.86]). No differences for other individual outcomes or for dimethyl fumarate versus the other two cohorts were observed. This study effectively demonstrated the use of an innovative statistical methodology to test a clinical hypothesis using real-world data to perform early target validation for drug discovery. Although there was a trend among patients treated with dimethyl fumarate towards a decreased incidence of type 2 diabetes, cardiovascular disease and chronic kidney disease relative to other disease-modifying therapies–which was statistically significant for the comparison with teriflunomide–this study did not definitively support the hypothesis that Nrf2 activation provided additional metabolic disease benefit in patients with multiple sclerosis.