Background: International Classification of Diseases, Tenth Edition (ICD-10) data help track outpatient antibiotic prescribing but lack validation in immunocompromised populations or subspecialty clinics for this purpose. Asymptomatic bacteriuria (ASB) and urinary tract infection (UTI) are important stewardship targets in renal transplant (RT) patients, but they may require alternative metrics to best monitor prescribing patterns. We describe ICD-10 utilization for RT clinic encounters in which antibiotics were prescribed. We developed a metric classifying “acute urinary antibiotics” (AUA) to track antibiotic use for ASB and UTI, and we validated systematic identification of AUA to enable practical implementation. Methods: We examined RT clinic visit and telemedicine encounters from 2018 to 2021 conducted 1 month after transplant. This project was deemed non–human-subjects research by the Stanford Panel on Human Subjects in Medical Research. Results: The analytic cohort included 420 antibacterial prescriptions from 408 encounters (Fig. 1). Of 238 patients, 136 (57%) were male and 112 (47%) were Hispanic or Latino. The most common primary ICD-10 code was Z94.0 (kidney transplant status) (N = 302 of 408 encounters, 75%); 26 encounters (6%) were coded for UTI (eg, N39.0, urinary tract infection, site not specified); and 214 encounters (53%) had multiple ICD-10 codes. The R82.71 code (bacteriuria) was never used. However, 215 prescriptions (51%) were classified as AUA (Fig. 2). The validation cohort included 130 prescriptions; 59 (45%) were classified as AUA and 51 (39%) had documented intent to treat ASB or UTI (positive percent agreement, 83%; negative percent agreement, 97%) (Table 1). For patients >1 month after transplant, the positive percent agreement was 95% and the negative percent agreement was 98%. Of 51 patients receiving AUA, 32 (63%) were asymptomatic despite frequently having a code for UTI (Fig. 3). Conclusions: ICD-10 coding may not be helpful in monitoring antibiotic prescribing in RT patients. The AUA metric offers a practical alternative to track antibiotic prescribing for urinary syndromes and reliably correlates with physician intent. Monitoring AUA prescribing rates could help identify opportunities to optimize antibiotic use in this complex outpatient setting.

Disclosures: None

The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery (WCPCCS) will be held in Washington DC, USA, from Saturday, 26 August, 2023 to Friday, 1 September, 2023, inclusive. The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery will be the largest and most comprehensive scientific meeting dedicated to paediatric and congenital cardiac care ever held. At the time of the writing of this manuscript, The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery has 5,037 registered attendees (and rising) from 117 countries, a truly diverse and international faculty of over 925 individuals from 89 countries, over 2,000 individual abstracts and poster presenters from 101 countries, and a Best Abstract Competition featuring 153 oral abstracts from 34 countries. For information about the Eighth World Congress of Pediatric Cardiology and Cardiac Surgery, please visit the following website: [www.WCPCCS2023.org]. The purpose of this manuscript is to review the activities related to global health and advocacy that will occur at the Eighth World Congress of Pediatric Cardiology and Cardiac Surgery.

Acknowledging the need for urgent change, we wanted to take the opportunity to bring a common voice to the global community and issue the Washington DC WCPCCS Call to Action on Addressing the Global Burden of Pediatric and Congenital Heart Diseases. A copy of this Washington DC WCPCCS Call to Action is provided in the Appendix of this manuscript. This Washington DC WCPCCS Call to Action is an initiative aimed at increasing awareness of the global burden, promoting the development of sustainable care systems, and improving access to high quality and equitable healthcare for children with heart disease as well as adults with congenital heart disease worldwide.

The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

This article explores how complaint investigations undertaken by health ombudsman contribute to the improvement of the healthcare system. Using a qualitative case-study approach, semi-structured interviews were conducted with participants form the Scottish Public Services Ombudsman (SPSO) and three health boards within its jurisdiction. Health board participants were frustrated by complaints process used by the SPSO, in particular the lack of communication during an SPSO investigation especially when there were differences in clinical judgment. Using Braithwaite’s typologies of motivational postures and Hertogh’s models of administrative control it was found that a sense of capitulation was the primary determinant in ensuring health board compliance with SPSO recommendations and that the relationship between SPSO and health boards was predominantly coercive in nature. For the SPSO to be more effective in contributing to system improvement requires it to review its role and means of conducting complaint investigations.

Three North Carolina Medicaid surveys conducted from 2000 to 2012 reported increasing numbers of Hispanic children enrolled in Medicaid and much lower trust in providers expressed by their adult caregiver respondents compared with responses for non-Hispanic Black and White children. To verify and explain this apparent trust chasm, we used bivariate and regression analyses. The variables employed included trust (dependent variable); child’s race/ethnicity, age, and sex; satisfaction and health status scales; two utilization measures; respondent’s age, sex, and education; geographical region; and population density of county of residence. Race/ethnicity was strongly associated with trust (p < .001), controlling for other independent variables. Access, satisfaction, and respondent’s age and education were also significant. Our results fit the Behavioral Model for Vulnerable Populations, which maps the role of significant variables in health-seeking behavior. After analyzing the concept of trust, we argue that lower acculturation explains lower Hispanic trust compared with non-Hispanic Blacks. We suggest policies to improve acculturation.

In Paper I, we presented an overview of the Southern-sky MWA Rapid Two-metre (SMART) survey, including the survey design and search pipeline. While the combination of MWA’s large field-of-view and the voltage capture system brings a survey speed of ${\sim} 450\, {\textrm{deg}}^{2}\,\textrm{h}^{-1}$, the progression of the survey relies on the availability of compact configuration of the Phase II array. Over the past few years, by taking advantage of multiple windows of opportunity when the compact configuration was available, we have advanced the survey to 75% of the planned sky coverage. To date, about 10% of the data collected thus far have been processed for a first-pass search, where 10 min of observation is processed for dispersion measures out to 250 ${\textrm{pc cm}}^{-3}$, to realise a shallow survey that is largely sensitive to long-period pulsars. The ongoing analysis has led to two new pulsar discoveries, as well as an independent discovery and a rediscovery of a previously incorrectly characterised pulsar, all from ${\sim} 3\% $ of the data for which candidate scrutiny is completed. In this sequel to Paper I, we describe the strategies for further detailed follow-up including improved sky localisation and convergence to timing solution, and illustrate them using example pulsar discoveries. The processing has also led to re-detection of 120 pulsars in the SMART observing band, bringing the total number of pulsars detected to date with the MWA to 180, and these are used to assess the search sensitivity of current processing pipelines. The planned second-pass (deep survey) processing is expected to yield a three-fold increase in sensitivity for long-period pulsars, and a substantial improvement to millisecond pulsars by adopting optimal de-dispersion plans. The SMART survey will complement the highly successful Parkes High Time Resolution Universe survey at 1.2–1.5 GHz, and inform future large survey efforts such as those planned with the low-frequency Square Kilometre Array (SKA-Low).

We present an overview of the Southern-sky MWA Rapid Two-metre (SMART) pulsar survey that exploits the Murchison Widefield Array’s large field of view and voltage-capture system to survey the sky south of 30$^{\circ}$ in declination for pulsars and fast transients in the 140–170 MHz band. The survey is enabled by the advent of the Phase II MWA’s compact configuration, which offers an enormous efficiency in beam-forming and processing costs, thereby making an all-sky survey of this magnitude tractable with the MWA. Even with the long dwell times employed for the survey (4800 s), data collection can be completed in $<$100 h of telescope time, while still retaining the ability to reach a limiting sensitivity of $\sim$2–3 mJy (at 150 MHz, near zenith), which is effectively 3–5 times deeper than the previous-generation low-frequency southern-sky pulsar survey, completed in the 1990s. Each observation is processed to generate $\sim$5000–8000 tied-array beams that tessellate the full $\sim 610\, {\textrm{deg}^{2}}$ field of view (at 155 MHz), which are then processed to search for pulsars. The voltage-capture recording of the survey also allows a multitude of post hoc processing options including the reprocessing of data for higher time resolution and even exploring image-based techniques for pulsar candidate identification. Due to the substantial computational cost in pulsar searches at low frequencies, the survey data processing is undertaken in multiple passes: in the first pass, a shallow survey is performed, where 10 min of each observation is processed, reaching about one-third of the full-search sensitivity. Here we present the system overview including details of ongoing processing and initial results. Further details including first pulsar discoveries and a census of low-frequency detections are presented in a companion paper. Future plans include deeper searches to reach the full sensitivity and acceleration searches to target binary and millisecond pulsars. Our simulation analysis forecasts $\sim$300 new pulsars upon the completion of full processing. The SMART survey will also generate a complete digital record of the low-frequency sky, which will serve as a valuable reference for future pulsar searches planned with the low-frequency Square Kilometre Array.

Despite promising steps towards the elimination of hepatitis C virus (HCV) in the UK, several indicators provide a cause for concern for future disease burden. We aimed to improve understanding of geographical variation in HCV-related severe liver disease and historic risk factor prevalence among clinic attendees in England and Scotland. We used metadata from 3829 HCV-positive patients consecutively enrolled into HCV Research UK from 48 hospital centres in England and Scotland during 2012–2014. Employing mixed-effects statistical modelling, several independent risk factors were identified: age 46–59 y (ORadj 3.06) and ≥60 y (ORadj 5.64) relative to <46 y, male relative to female sex (ORadj 1.58), high BMI (ORadj 1.73) and obesity (ORadj 2.81) relative to normal BMI, diabetes relative to no diabetes (ORadj 2.75), infection with HCV genotype (GT)-3 relative to GT-1 (ORadj 1.75), route of infection through blood products relative to injecting drug use (ORadj 1.40), and lower odds were associated with black ethnicity (ORadj 0.31) relative to white ethnicity. A small proportion of unexplained variation was attributed to differences between hospital centres and local health authorities. Our study provides a baseline measure of historic risk factor prevalence and potential geographical variation in healthcare provision, to support ongoing monitoring of HCV-related disease burden and the design of risk prevention measures.

Recent research has highlighted a tendency for more rational and deliberative decision-making in individuals with autism. We tested this hypothesis by using eye-tracking to investigate the information processing strategies that underpin multi-attribute choice in a sample of adults diagnosed with autism spectrum condition. We found that, as the number of attributes defining each option increased, autistic decision-makers were speedier, examined less of the available information, and spent a greater proportion of their time examining the option they eventually chose. Rather than indicating a more deliberative style, our results are consistent with a tendency for individuals with autism to narrow down the decision-space more quickly than does the neurotypical population.

This article revisits debates concerning poverty, inequality, and development in Latin America and explores a possible “high road” to globalization capable of achieving both more rapid economic growth and significant and lasting reductions in poverty and inequality. In reconnoitering the contours of this path, the authors probe a partial convergence in theory, concepts, and policies that may offer new opportunities for bridging the yawning chasms that heretofore have divided multilateral financial organizations, local governing elites, and academics as well as Center-Left political parties, organized labor, social movements, and NGOs. The article concludes with an assessment of the capacity of this emerging political agenda and attendant “polycentric development coalitions” to deepen and extend democracy effectively beyond the electoral arena to include basic issues of justice and equity.

This paper presents a deep-learning-based workflow to detect synapses and predict their neurotransmitter type in the primitive chordate Ciona intestinalis (Ciona) electron microscopic (EM) images. Identifying synapses from EM images to build a full map of connections between neurons is a labor-intensive process and requires significant domain expertise. Automation of synapse classification would hasten the generation and analysis of connectomes. Furthermore, inferences concerning neuron type and function from synapse features are in many cases difficult to make. Finding the connection between synapse structure and function is an important step in fully understanding a connectome. Class Activation Maps derived from the convolutional neural network provide insights on important features of synapses based on cell type and function. The main contribution of this work is in the differentiation of synapses by neurotransmitter type through the structural information in their EM images. This enables the prediction of neurotransmitter types for neurons in Ciona, which were previously unknown. The prediction model with code is available on GitHub.