Racial differences in length of stay and readmission for asthma in the all of us research program.

BACKGROUND: This study addresses the limited research on racial disparities in asthma hospitalization outcomes, specifically length of stay (LOS) and readmission, across the U.S. METHODS: We analyzed in-patient and emergency department visits from the All of Us Research Program, identifying various risk factors (demographic, comorbid, temporal, and place-based) associated with asthma LOS and 30-day readmission using Bayesian mixed-effects models. RESULTS: Of 17,233 patients (48.0% White, 30.7% Black, 19.7% Hispanic/Latino, 1.3% Asian, and 0.3% Middle Eastern and North African) with 82,188 asthma visits, Black participants had 20% shorter LOS and 12% higher odds of readmission, compared to White participants in multivariate analyses. Public-insured patients had 14% longer LOS and 39% higher readmission odds than commercially insured patients. Weekend admissions resulted in a 12% shorter LOS but 10% higher readmission odds. Asthmatics with chronic diseases had a longer LOS (range: 6-39%) and higher readmission odds (range: 9-32%) except for those with allergic rhinitis, who had a 23% shorter LOS. CONCLUSIONS: A comprehensive understanding of the factors influencing asthma hospitalization, in conjunction with diverse datasets and clinical-community partnerships, can help physicians and policymakers to systematically address racial disparities, healthcare utilization and equitable outcomes in asthma care.

Multilevel Analysis of Racial and Ethnic Disparities in COVID-19 Hospitalization among Children with Allergies.

Rationale: Previous studies have identified risk factors for coronavirus disease (COVID-19) hospitalization in children. However, these studies have been limited in their ability to disentangle the contribution of racial disparities, allergic comorbidities, and environmental exposures to the development of severe COVID-19 in at-risk children with allergies. Objectives: To examine racial and ethnic disparities in COVID-19 hospitalization and their links to potentially underlying allergic comorbidities and individual and place-based factors in children with allergies. Methods: This is an electronic health record-based retrospective study of children in 2020. The outcome was COVID-19 hospitalization categorized as no hospital care for patients with asymptomatic/mild illness, short stay for patients admitted and discharged within 24 hours, and prolonged stay for patients requiring additional time to discharge (more than 24 h). Mixed-effects and mediation models were used to determine relationships among independent variables, mediators, and COVID-19 hospitalization. Results: Among the 5,258 children with COVID-19 positive test or diagnosis, 10% required a short stay, and 3.7% required a prolonged stay. Black and Hispanic children had higher odds of longer stays than non-Hispanic White children (both P < 0.001). Children with obesity and eosinophilic esophagitis diagnoses had higher odds of short and prolonged stay (all P < 0.05). Area-level deprivation was associated with short stay (adjusted odds ratio [AOR], 15.49; 95% confidence interval [CI], 5.16-45.47 for every 0.1-unit increase) and prolonged stay (AOR, 11.82; 95% CI, 2.25-62.01 for every 0.1-unit increase). Associations between race/ethnicity and COVID-19 hospitalization were primarily mediated by insurance and area-level deprivation, altogether accounting for 99% of the variation in COVID-19 hospitalization. Conclusions: There were racial and ethnic differences in children with allergies and individual and place-based factors related to COVID-19 hospitalization. Differences were primarily mediated by insurance and area-level deprivation, altogether accounting for 99% of the variation in COVID-19 hospitalization. A better understanding of COVID-related morbidity in children and the link to place-based factors is key to developing prevention strategies capable of equitably improving outcomes.

Understanding racial disparities in childhood asthma using individual- and neighborhood-level risk factors.

BACKGROUND: Racial disparities in childhood asthma outcomes result from a complex interplay of individual- and neighborhood-level factors. OBJECTIVES: We sought to examine racial disparities in asthma-related emergency department (ED) visits between African American (AA) and European American (EA) children. METHODS: This is a retrospective study of patients younger than 18 years who visited the ED at Cincinnati Children's for asthma from 2009 to 2018. The outcome was number of ED visits during a year. We assessed 11 social, economic, and environmental variables. Mediation and mixed-effects analyses were used to assess relationships between race, mediators, and number of ED visits. RESULTS: A total of 31,114 children (46.1% AA, 53.9% EA) had 186,779 asthma-related ED visits. AA children had more visits per year than EA children (2.23 vs 2.15; P < .001). Medicaid insurance was associated with a 7% increase in rate of ED visits compared with commercial insurance (1.07; 95% CI, 1.03-1.1). Neighborhood socioeconomic deprivation was associated with an increased rate of ED visits in AA but not in EA children. Area-level particulate matter with diameter less than 2.5 µm, pollen, and outdoor mold were associated with an increased rate of ED visits for both AA and EA children (all P < .001). Associations between race and number of ED visits were mediated by insurance, area-level deprivation, particulate matter with diameter less than 2.5 µm, and outdoor mold (all P < .001), altogether accounting for 55% of the effect of race on ED visits. Race was not associated with number of ED visits (P = .796) after accounting for mediators. CONCLUSIONS: Racial disparities in asthma-related ED visits are mediated by social, economic, and environmental factors, which may be amenable to interventions aimed at improving outcomes and eliminating inequities.

Associated health and social determinants of mobile populations across HIV epidemic gradients in Southern Africa.

BACKGROUND: Growing travel connectivity and economic development have dramatically increased the magnitude of human mobility in Africa. In public health, vulnerable population groups such as mobile individuals are at an elevated risk of sexually transmitted diseases, including HIV. METHODS: The population-based Demographic Health Survey data of five Southern African countries with different HIV epidemic intensities (Angola, Malawi, South Africa, Zambia, and Zimbabwe) were used to investigate the association between HIV serostatus and population mobility adjusting for socio-demographic, sexual behavior and spatial covariates. RESULTS: Mobility was associated with HIV seropositive status only in Zimbabwe (adjusted odds ratio [AOR] = 1.37 [95% confidence interval [CI]: 1.01-1.67]). These associations were not significant in Angola, Malawi, South Africa, and Zambia. Females had higher odds of mobility than males in Zimbabwe (AOR = 1.37, CI: 1.10-1.69). The odds of mobility decreased with age in all five countries. CONCLUSIONS: Our findings highlight the heterogeneity of the social and health determinants of mobile populations in several countries with different HIV epidemic intensities. Effective interventions using precise geographic focus combined with detailed attribute characterization of mobile populations can enhance their impact especially in areas with high density of mobile individuals and high HIV prevalence.

The epidemiological landscape of anemia in women of reproductive age in sub-Saharan Africa.

The role of geographical disparities of health-related risk factors with anemia are poorly documented for women of reproductive age in sub-Saharan Africa (SSA). We aimed to determine the contribution of potential factors and to identify areas at higher risk of anemia for women in reproductive age in SSA. Our study population comprised 27 nationally representative samples of women of reproductive age (15-49) who were enrolled in the Demographic and Health Surveys and conducted between 2010 and 2019 in SSA. Overall, we found a positive association between being anemic and the ecological exposure to malaria incidence [adjusted odds ratio (AOR) = 1.02, 95% confidence interval (CI) 1.02-1.02], and HIV prevalence (AOR = 1.01, CI 1.01-1.02). Women currently pregnant or under deworming medication for the last birth had 31% (AOR = 1.31, CI 1.24-1.39) and 5% (AOR = 1.05, CI 1.01-1.10) higher odds of having anemia, respectively. Similarly, women age 25-34 years old with low education, low income and living in urban settings had higher odds of having anemia. In addition, underweight women had 23% higher odds of suffering anemia (AOR = 1.23, CI 1.15-1.31). Females with low levels of education and wealth index were consistently associated with anemia across SSA. Spatial distribution shows increased risk of anemia in Central and Western Africa. Knowledge about the contribution of known major drivers and the spatial distribution of anemia risk can mitigate operational constraints and help to design geographically targeted intervention programs in SSA.

Identification of Vulnerable Populations and Areas at Higher Risk of COVID-19-Related Mortality during the Early Stage of the Epidemic in the United States.

We characterized vulnerable populations located in areas at higher risk of COVID-19-related mortality and low critical healthcare capacity during the early stage of the epidemic in the United States. We analyze data obtained from a Johns Hopkins University COVID-19 database to assess the county-level spatial variation of COVID-19-related mortality risk during the early stage of the epidemic in relation to health determinants and health infrastructure. Overall, we identified highly populated and polluted areas, regional air hub areas, race minorities (non-white population), and Hispanic or Latino population with an increased risk of COVID-19-related death during the first phase of the epidemic. The 10 highest COVID-19 mortality risk areas in highly populated counties had on average a lower proportion of white population (48.0%) and higher proportions of black population (18.7%) and other races (33.3%) compared to the national averages of 83.0%, 9.1%, and 7.9%, respectively. The Hispanic and Latino population proportion was higher in these 10 counties (29.3%, compared to the national average of 9.3%). Counties with major air hubs had a 31% increase in mortality risk compared to counties with no airport connectivity. Sixty-eight percent of the counties with high COVID-19-related mortality risk also had lower critical care capacity than the national average. The disparity in health and environmental risk factors might have exacerbated the COVID-19-related mortality risk in vulnerable groups during the early stage of the epidemic.

Spatiotemporal transmission dynamics of the COVID-19 pandemic and its impact on critical healthcare capacity.

The role of geospatial disparities in the dynamics of the COVID-19 pandemic is poorly understood. We developed a spatially-explicit mathematical model to simulate transmission dynamics of COVID-19 disease infection in relation with the uneven distribution of the healthcare capacity in Ohio, U.S. The results showed substantial spatial variation in the spread of the disease, with localized areas showing marked differences in disease attack rates. Higher COVID-19 attack rates experienced in some highly connected and urbanized areas (274 cases per 100,000 people) could substantially impact the critical health care response of these areas regardless of their potentially high healthcare capacity compared to more rural and less connected counterparts (85 cases per 100,000). Accounting for the spatially uneven disease diffusion linked to the geographical distribution of the critical care resources is essential in designing effective prevention and control programmes aimed at reducing the impact of COVID-19 pandemic.

Identification of Vulnerable Populations and Areas at Higher Risk of COVID-19 Related Mortality in the U.S.

Background: The role of health-related disparities including sociodemographic, environmental, and critical care capacity in the COVID-19 pandemic are poorly understood. In the present study, we characterized vulnerable populations located in areas at higher risk of COVID-19 related mortality and low critical healthcare capacity in the U.S. Methods: Using Bayesian multilevel analysis and small area disease risk mapping, we assessed the spatial variation of COVID-19 related mortality risk for the U.S. in relation with healthcare disparities including race, ethnicity, poverty, air quality, and critical healthcare capacity. Results: Overall, highly populated, regional air hub areas, and minorities had an increased risk of COVID-19 related mortality. We found that with an increase of only 1 ug/m3 in long term PM2.5 exposure, the COVID-19 mortality rate increased by 13%. Counties with major air hubs had 18% increase in COVID-19 related death compared to counties with no airport connectivity. Sixty-eight percent of the counties with high COVID-19 related mortality risk were also counties with lower critical care capacity than national average. These counties were primary located at the North- and South-Eastern regions of the country. Conclusion: The existing disparity in health and environmental risk factors that exacerbate the COVID-19 related mortality, along with the regional healthcare capacity, determine the vulnerability of populations to COVID-19 related mortality. The results from this study can be used to guide the development of strategies for the identification and targeting preventive strategies in vulnerable populations with a higher proportion of minority groups living in areas with poor air quality and low healthcare capacity.

Computer Imagery and Neurological Rehabilitation: On the Use of Augmented Reality in Sensorimotor Training to Step Up Naturally Occurring Cortical Reorganization in Patients Following Stroke.

This work promotes the use of computer-generated imagery -as visual illusions- to speed up motor learning in rehabilitation. In support of this, we adhere the principles of experience-dependent neuroplasticity and the positive impact of virtual reality (VR) thereof. Specifically, post-stroke patients will undergo motor therapy with a surrogate virtual limb that fakes the paralyzed limb. Along these lines, their motor intentions will match the visual evidence, which fosters physiological, functional and structural changes over time, for recovery of lost function in an injured brain. How we make up such an illusion using computer graphics, is central to this paper.

Creatools: una plataforma para el desarrollo de software de procesamiento de imágenes médicas. Aplicación a la segmentación de arterias coronarias y a la detección automática de lesiones en imágenes de angiotac / Creatools: a framework for the development of medical image processing software. Application for the segmentation of coronary arteries and for the automatic detection of lesions in CT images

En este artículo se presenta un software de código abierto, llamado CreaTools, cuyo principal objetivo es el procesar y facilitar la visualización de imágenes médicas. Este software flexible funciona en diferentes sistemas operativos (Linux, Mac OS X, Windows), se desarrolla en el lenguaje de programación C++ para asegurar una fácil integración de módulos C++ y proporciona a los usuarios herramientas computacionales para construir interfaces gráficas de usuario (GUI), incluidos los datos de entrada/salida (manejo de archivos), la visualización, la interacción y el procesamiento de datos. Este artículo muestra también la utilidad de CreaTools mediante un proyecto de investigación que consiste en la detección automática de lesiones arteriales. Los algoritmos desarrollados han sido implementados en una interfaz gráfica amigable con visualización 3D e interacción. Ejemplos de tales algoritmos incluyen la extracción de ejes de arterias y la generación de modelos descriptivos de arterias con lesiones y sin lesiones.