Introduction: With opioid-related deaths reaching epidemic levels, gaining a better understanding of access to treatment for opioid use disorder (OUD) is critical. Most studies have focused on 1 side of the equation-either provider capacity or patients' need for care, as measured by overdose deaths. This study examines the overlay between treatment program availability and opioid mortality, comparing accessibility by region. Methods: Geospatial and statistical analyses were used to model OUD treatment programs relative to population density and opioid overdose death incidence at the state and county level. We computed a ratio between program capacity and mortality called the programsper-death (PPD) ratio. Results: There were 40 274 opioid deaths in 2016 and 12 572 treatment programs across the contiguous 48 states, yielding a ratio of 1 program for every 3.2 deaths. Texas had the lowest number of treatment programs per 100 000 persons (1.4) and Maine the highest (13.2). West Virginia ranked highest in opioid deaths (39.09 per 100 000). Ohio, the District of Columbia, and West Virginia had the greatest mismatch between providers and deaths, with an average of 1 program for every 8.5 deaths. Over 32% of US counties had no treatment programs and among those with >10 deaths, nearly 2.5% had no programs. Over 19% of all counties had a ratio 1 provider facility per 10 deaths. Conclusion: Assessing the overlay between treatment capacity and need demonstrated that regional imbalances exist. These data can aid in strategic planning to correct the mismatch and potentially reduce mortality in the most challenged geographic regions.

The 2001 World Health Organization and Schofield predictive equations overestimated and underestimated, respectively, energy requirements compared with those obtained by bicarbonate dilution kinetics. Bicarbonate kinetics allows accurate determination of energy needs in critically ill children.

BACKGROUND AND OBJECTIVES Compared with population-based rates, at-risk rates (ARRs) account for underlying variations of asthma prevalence. When applied with geospatial analysis, ARRs may facilitate more accurate evaluations of the contribution of place-based social determinants of health (SDOH) to pediatric asthma morbidity. Our objectives were to calculate ARRs for pediatric asthma-related emergency department (ED) encounters and hospitalizations by census-tract in Washington, the District of Columbia (DC) and evaluate their associations with SDOH. METHODS This population-based, cross-sectional study identified children with asthma, 2 to 17 years old, living in DC, and included in the DC Pediatric Asthma Registry from January 2018 to December 2019. ED encounter and hospitalization ARRs (outcomes) were calculated for each DC census-tract. Five census-tract variables (exposures) were selected by using the Healthy People 2030 SDOH framework: educational attainment, vacant housing, violent crime, limited English proficiency, and families living in poverty. RESULTS During the study period, 4321 children had 7515 ED encounters; 1182 children had 1588 hospitalizations. ARRs varied 10-fold across census-tracts for both ED encounters (64–728 per 1000 children with asthma) and hospitalizations (20–240 per 1000 children with asthma). In adjusted analyses, decreased educational attainment was significantly associated with ARRs for ED encounters (estimate 12.1, 95% confidence interval [CI] 8.4 to 15.8, P <.001) and hospitalizations (estimate 1.2, 95% CI 0.2 to 2.2, P = .016). Violent crime was significantly associated with ARRs for ED encounters (estimate 35.3, 95% CI 10.2 to 60.4, P = .006). CONCLUSION Place-based interventions addressing SDOH may be an opportunity to reduce asthma morbidity among children with asthma.

These results confirm a decrease in cerebral blood flow during HUTT as assessed by head NIRS in patients with autonomic dysfunction. Specifically, we have profiled the cerebral blood flow contours throughout the phases of HUTT, which add insight into the clinical spectrum of the disorder and may correlate with clinical severity.