Literature Collection
11K+
References
9K+
Articles
1500+
Grey Literature
4600+
Opioids & SU
The Literature Collection contains over 11,000 references for published and grey literature on the integration of behavioral health and primary care. Learn More
Use the Search feature below to find references for your terms across the entire Literature Collection, or limit your searches by Authors, Keywords, or Titles and by Year, Type, or Topic. View your search results as displayed, or use the options to: Show more references per page; Sort references by Title or Date; and Refine your search criteria. Expand an individual reference to View Details. Full-text access to the literature may be available through a link to PubMed, a DOI, or a URL. References may also be exported for use in bibliographic software (e.g., EndNote, RefWorks, Zotero).
This grey literature reference is included in the Academy's Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.
This grey literature reference is included in the Academy's Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.
INTRODUCTION: The spread of the SARS-CoV-2 virus, which caused Coronavirus Disease 2019 (COVID-19), led to a global pandemic and public health crisis, which affected the physical health and mental well-being of Americans in every part of the country. Although the effect of the pandemic was ubiquitous, it has been more extensively studied in urban areas, which leads to an underscoring of the burden of COVID-19 in rural US. Health disparities adversely affect children in rural communities, each of which is unique and requires interventions based on regional needs. Characterization of COVID-19 disease in the pediatric population in rural areas is important for the development of protocols to address future surges of COVID-19 cases by the local health systems. METHODS: This study is a retrospective, cross-sectional chart review of 86 children hospitalized with the diagnosis of COVID-19 at three different hospitals that are part of an integrated rural health system in North and South Dakota. The population demographics of the surveyed states included Caucasian (84.2% SD; 86.6% ND), Native American (8.6% SD; 4.9% ND), Black (2.6% SD; 3.6% ND), and Asian (1.8% SD; 1.7% ND). All the charts identified from the EMR by filtering for patients hospitalized between October 2020 and May 2021, with an age less than 18 years, and with the ICD-10 code for COVID-19 infection were reviewed. Patients with Multi-system Inflammatory Syndrome in Children were excluded. RESULTS: More than half of the patients identified as Caucasian (58%), (24%) as Native American, (12%) as Black/ African American, (5%) as Asian, and (1%) were unidentified. The median age was 12 years. Almost half of the patients, 42%, had a significant past medical history, defined as having one or more of the following diagnoses: asthma, diabetes mellitus, or immunodeficiency. The most common comorbidity was an elevated BMI>25 noted in 31 patients of which 11 (13%) were overweight and 20 (23%) were obese. 18 patients (22%) were admitted to the ICU with a median length of ICU-stay of 3.5 days. 34 patients (40%) required oxygen supplementation with a median length duration of 3-days. 8 patients (9%) required intubation. The median length of mechanical ventilation support was 3-days. There were no deaths. CONCLUSIONS: It was interesting to note that in this study, pediatric patients with SARS-CoV-2 infection requiring hospitalization were disproportionately represented by minority groups (Native Americans, Blacks, and Asians) when compared to the proportion in the population. The predominance of Caucasian patients however was reflective of the general population of the surveyed states. Almost half the patients had one or more of the following diagnoses: asthma, diabetes mellitus, or immunodeficiency, risk factors previously identified for COVID-19. A common comorbidity among the patients studied was increased BMI, which has been noted as a risk factor for SARS-CoV-2 infection in the literature. This demonstrates that there are multiple common risk factors in rural and urban populations despite environmental differences.
This grey literature reference is included in the Academy's Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.
This grey literature reference is included in the Academy's Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.
This grey literature reference is included in the Academy's Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.
This grey literature reference is included in the Academy's Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.