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Author(s): Lindsay Arthur [sup.1] , Parthak Prodhan [sup.1] [sup.2] , Richard Blaszak [sup.3] , Brendan Crawford [sup.3] , Clare C. Brown [sup.4] , Jason Arthur [sup.5] [sup.6] Author Affiliations: (1) [...], Background Lung ultrasound is a well-established technique to assess extravascular lung water, a proxy for volume status, in the adult population. Despite its utility, the data are limited supporting the use of ultrasound to evaluate fluid volume status among pediatric patients. Our study uses a simplified ultrasound protocol to evaluate changes in extravascular lung water, represented by b-lines, among pediatric patients undergoing hemodialysis. Methods This prospective single-center study included children from birth to 18 years of age. The number of b-lines per ml/kg of fluid removed was compared prior to, at the midpoint, and following termination of dialysis. An 8-zone protocol was utilized, and b-lines were correlated to hemoconcentration measured by the CRIT-LINE® hematocrit. Results Six patients with a total of 26 hemodialysis sessions were included in this study. The b-line measurements post-dialysis were 2.27 (p < 0.001; 94%CI -3.31, -1.22) lower relative to pre-dialysis. The number of b-lines was reduced by 1.69 (p < 0.001; -2.58, -0.80) between pre-dialysis and at the midpoint of dialysis and by 0.58 (p = 0.001; -0.90, -0.24) between the midpoint of dialysis and post-dialysis. A 1 mL/kg fluid loss correlated to a decrease in the original b-lines by 0.079. An inverse relationship (r = -0.54; 95% CI: -0.72, -0.34; p < 0.001) was noted between the b-lines and the patients&apos; hematocrit levels. Conclusions A simplified 8-zone ultrasound protocol can assess fluid volume change in real time and correlates with hematocrit levels obtained throughout dialysis. This provides a valuable method for monitoring fluid status in volume overloaded patient populations. Graphical abstract

Background: Telehealth is a rapidly growing modality for expanding healthcare access, especially in the post-COVID-19 era. However, telehealth requires high-quality broadband, thus making broadband a social determinant of health. The objective of this study was to evaluate the association between broadband access and telehealth utilization across the United States during the COVID-19 pandemic. Methods: Using a cross-sectional, ecological study design, we merged county-level data on broadband capacity (Microsoft's Rural Broadband Initiative), telehealth utilization among Medicare Fee-for-Service beneficiaries from January through September 2020 (CareJourney), and county-level socioeconomic characteristics (Area Health Resources Files). Multivariable linear regression was used to estimate the association between broadband capacity, county-level characteristics, and telehealth utilization. Results: Among the 3107 counties, those with the greatest broadband availability (quintile 5) had 47% higher telehealth utilization compared to counties with the least broadband availability (quintile 1). In the adjusted model, a 1 standard deviation (SD) increase in broadband access was associated with a 1.54 percentage point (pp) increase in telehealth utilization (P < 0.001). Rural county designation (−1.96 pp; P < 0.001) and 1 SD increases in average Medicare beneficiary age (−1.34 pp; P = 0.001), number of nursing home beds per 1000 individuals (−0.38 pp; P = 0.002), and proportion of Native Americans/Pacific Islanders (−0.59 pp; P < 0.001) were associated with decreased telehealth utilization. Conclusion: The association between broadband access and telehealth utilization and the decreased telehealth utilization in rural areas highlight the importance of broadband access for healthcare access and the need to continue investing in broadband infrastructure to promote equitable healthcare access across populations. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the impact of the 2022 infant formula shortage on self-reported anxiety and depression. Background: The US national infant formula shortage of 2022 originated from supply chain disruptions triggered by the COVID-19 pandemic, and the shortage was further compounded by a recall of tainted formula products. Methods: We used survey-weighted data from the Household Pulse Survey (HPS) to measure self-reported anxiety and depression among individuals with formula-fed infants less than 1 year of age. We evaluated the association between 2 formula disruption variables (being impacted by the infant formula shortage or having difficulty obtaining formula in the last 7 days) with 2 mental health outcomes (anxiety and depression) using multivariable logistic regressions. Results: We found increased odds of self-reported anxiety (aOR: 3.13; P < .001) and depression (aOR: 3.05; P = .005) for respondents affected by the infant formula shortage. There were no adjusted associations between having difficulty obtaining formula in the last 7 days and anxiety and depression. Conclusions: Individuals affected by the infant formula shortage had increased odds of both anxiety and depression. Continued efforts to improve food security for low-income infants is critical for ensuring equitable nutritional and health outcomes across infant populations. Implications for practice and research: Continued efforts to reduce food insecurity for low-income infants are critically needed, as infant nutrition impacts caregiver mental health and infant health. Efforts to improve lactation support and breastfeeding initiation are needed in addition to improvements in access to formula. [ABSTRACT FROM AUTHOR]

This study examined if there was difference in cost of care after implementation of scattered bed inpatient hospice, first implemented in October 2021 in an Academic Medical Center in Arkansas. This retrospective, cross-sectional study compared the cost of care during the pre-implementation phase (n = 121, July 2020-March 2021) to patients admitted to hospice care (n = 84, October 2021-June 2022). Hospice length of stay (LOS) was 4 times longer than the LOS after a Do Not Resuscitate order (DNR) was placed for patients in the pre-implementation period. The end of life costs after the implementation of inpatient hospice was 69% less than the end of life costs in the pre-implementation period. [ABSTRACT FROM AUTHOR]

Background and Aims: Longitudinal change in income is crucial in explaining cardiovascular health inequalities. However, there is limited evidence for cardiovascular disease (CVD) risk associated with income dynamics over time among individuals with type 2 diabetes (T2D). Methods: Using a nationally representative sample from the Korean National Health Insurance Service database, 1 528 108 adults aged 30–64 with T2D and no history of CVD were included from 2009 to 2012 (mean follow-up of 7.3 years). Using monthly health insurance premium information, income levels were assessed annually for the baseline year and the four preceding years. Income variability was defined as the intraindividual standard deviation of the percent change in income over 5 years. The primary outcome was a composite event of incident fatal and nonfatal CVD (myocardial infarction, heart failure, and stroke) using insurance claims. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated after adjusting for potential confounders. Results: High-income variability was associated with increased CVD risk (HRhighest vs. lowest quartile 1.25, 95% CI 1.22–1.27; Ptrend <.001). Individuals who experienced an income decline (4 years ago vs. baseline) had increased CVD risk, which was particularly notable when the income decreased to the lowest level (i.e. Medical Aid beneficiaries), regardless of their initial income status. Sustained low income (i.e. lowest income quartile) over 5 years was associated with increased CVD risk (HRn = 5 years vs. n = 0 years 1.38, 95% CI 1.35–1.41; Ptrend <.0001), whereas sustained high income (i.e. highest income quartile) was associated with decreased CVD risk (HRn = 5 years vs. n = 0 years 0.71, 95% CI 0.70–0.72; Ptrend <.0001). Sensitivity analyses, exploring potential mediators, such as lifestyle-related factors and obesity, supported the main results. Conclusions: Higher income variability, income declines, and sustained low income were associated with increased CVD risk. Our findings highlight the need to better understand the mechanisms by which income dynamics impact CVD risk among individuals with T2D. Structured Graphical Abstract This study investigates the association between income dynamics over five years and incident composite cardiovascular outcomes in non-elderly individuals with type 2 diabetes. Our graphical abstract highlights significant associations between cardiovascular risk and income metrics, including income variability (standard deviation of percent change), changes in income status (rise and decline), and cumulative number of years in low- or high-income status. [ABSTRACT FROM AUTHOR]

Previous machine learning approaches fail to consider race and ethnicity and social determinants of health (SDOH) to predict childhood asthma exacerbations. A predictive model for asthma exacerbations in children is developed to explore the importance of race and ethnicity, rural-urban commuting area (RUCA) codes, the Child Opportunity Index (COI), and other ICD-10 SDOH in predicting asthma outcomes. Insurance and coverage claims data from the Arkansas All-Payer Claims Database were used to capture risk factors. We identified a cohort of 22,631 children with asthma aged 5–18 years with 2 years of continuous Medicaid enrollment and at least one asthma diagnosis in 2018. The goal was to predict asthma-related hospitalizations and asthma-related emergency department (ED) visits in 2019. The analytic sample was 59% age 5–11 years, 39% White, 33% Black, and 6% Hispanic. Conditional random forest models were used to train the model. The model yielded an area under the curve (AUC) of 72%, sensitivity of 55% and specificity of 78% in the OOB samples and AUC of 73%, sensitivity of 58% and specificity of 77% in the training samples. Consistent with previous literature, asthma-related hospitalization or ED visits in the previous year (2018) were the two most important variables in predicting hospital or ED use in the following year (2019), followed by the total number of reliever and controller medications. Predictive models for asthma-related exacerbation achieved moderate accuracy, but race and ethnicity, ICD-10 SDOH, RUCA codes, and COI measures were not important in improving model accuracy. [ABSTRACT FROM AUTHOR]

The article discusses a study by Margerison and colleagues which evaluated changes in five categories of pregnancy-associated death during the first two years of COVID-19 pandemic. Topics include racial/ethnic disparities in each of the incidental or accidental causes, significant increases in different types of pregnancy-associated deaths during the first two years of the pandemic, and a template of evaluations of inequities provided by the researchers outside the perinatal space.

Background: Data dashboards have become more widely used for the public communication of health-related data, including in maternal health. Objective: We aimed to evaluate the content and features of existing publicly available maternal health dashboards in the United States. Methods: Through systematic searches, we identified 80 publicly available, interactive dashboards presenting US maternal health data. We abstracted and descriptively analyzed the technical features and content of identified dashboards across four areas: (1) scope and origins, (2) technical capabilities, (3) data sources and indicators, and (4) disaggregation capabilities. Where present, we abstracted and qualitatively analyzed dashboard text describing the purpose and intended audience. Results: Most reviewed dashboards reported state-level data (58/80, 72%) and were hosted on a state health department website (48/80, 60%). Most dashboards reported data from only 1 (33/80, 41%) or 2 (23/80, 29%) data sources. Key indicators, such as the maternal mortality rate (10/80, 12%) and severe maternal morbidity rate (12/80, 15%), were absent from most dashboards. Included dashboards used a range of data visualizations, and most allowed some disaggregation by time (65/80, 81%), geography (65/80, 81%), and race or ethnicity (55/80, 69%). Among dashboards that identified their audience (30/80, 38%), legislators or policy makers and public health agencies or organizations were the most common audiences. Conclusions: While maternal health dashboards have proliferated, their designs and features are not standard. This assessment of maternal health dashboards in the United States found substantial variation among dashboards, including inconsistent data sources, health indicators, and disaggregation capabilities. Opportunities to strengthen dashboards include integrating a greater number of data sources, increasing disaggregation capabilities, and considering end-user needs in dashboard design. [ABSTRACT FROM AUTHOR]