Disparities in outcomes between Black and White patients in North America with thoracic malignancies and COVID-19 infection (TERAVOLT).

BACKGROUND: Patients with thoracic malignancies who develop COVID-19 infection have a higher hospitalization rate compared to the general population and to those with other cancer types, but how this outcome differs by race and ethnicity is relatively understudied. METHODS: The TERAVOLT database is an international, multi-center repository of cross-sectional and longitudinal data studying the impact of COVID-19 on individuals with thoracic malignancies. Patients from North America with thoracic malignancies and confirmed COVID-19 infection were included for this analysis of racial and ethnic disparities. Patients with missing race data or races and ethnicities with fewer than 50 patients were excluded from analysis. Multivariable analyses for endpoints of hospitalization and death were performed on these 471 patients. RESULTS: Of the 471 patients, 73% were White and 27% were Black. The majority (90%) were non-Hispanic ethnicity, 5% were Hispanic, and 4% were missing ethnicity data. Black patients were more likely to have an Eastern Cooperative Oncology Group (ECOG) Performance Status ≥ 2 (p-value = 0.04). On multivariable analysis, Black patients were more likely than White patients to require hospitalization (Odds Ratio (OR): 1.69, 95% CI: 1.01-2.83, p-value = 0.044). These differences remained across different waves of the pandemic. However, no statistically significant difference in mortality was found between Black and White patients (OR 1.29, 95% CI: 0.69-2.40, p-value = 0.408). CONCLUSIONS: Black patients with thoracic malignancies who acquire COVID-19 infection are at a significantly higher risk of hospitalization compared to White patients, but there is no significant difference in mortality. The underlying drivers of racial disparity among patients with thoracic malignancies and COVID-19 infection require ongoing investigation.

Understanding Mi'kmaq Women's Experiences Accessing Prenatal Care in Rural Nova Scotia.

Indigenous women experience a higher incidence of maternal complications compared with non-Indigenous women. Despite this, little is known about access to prenatal care for Mi'kmaq women in Nova Scotia. The intent of this study was to gain a more comprehensive understanding of Mi'kmaq women's experiences accessing prenatal care. The findings from this study highlight key implications for nursing practice such as promoting the nurse's role in supporting and advocating for Mi'kmaq women's health and for providing culturally safe care. This research will highlight that access to prenatal care is a complex issue for some women.

Optimal screening and donor management in a public stool bank.

BACKGROUND: Fecal microbiota transplantation is an effective treatment for recurrent Clostridium difficile infection and is being investigated as a treatment for other microbiota-associated diseases. To facilitate these activities, an international public stool bank has been created, which screens donors and processes stools in a standardized manner. The goal of this research is to use mathematical modeling and analysis to optimize screening and donor management at the stool bank. RESULTS: Compared to the current policy of screening active donors every 60 days before releasing their quarantined stools for sale, costs can be reduced by 10.3 % by increasing the screening frequency to every 36 days. In addition, the stool production rate varies widely across donors, and using donor-specific screening, where higher producers are screened more frequently, also reduces costs, as does introducing an interim (i.e., between consecutive regular tests) stool test for just rotavirus and C. difficile. We also derive a donor release (i.e., into the system) policy that allows the supply to approximately match an exponentially increasing deterministic demand. CONCLUSIONS: More frequent screening, interim screening for rotavirus and C. difficile, and donor-specific screening, where higher stool producers are screened more frequently, are all cost-reducing measures. If screening costs decrease in the future (e.g., as a result of bringing screening in house), a bottleneck for implementing some of these recommendations may be the reluctance of donors to undergo serum screening more frequently than monthly.

An in vitro model for the assessment of stem cell fate following implantation within the infarct microenvironment identifies ISL-1 expression as the strongest predictor of c-Kit(+) cardiac progenitor cells' therapeutic potential.

Cell therapy has the potential to drastically improve clinical outcomes for the 1.45 million patients suffering from a myocardial infarction (MI) each year in the U.S. However, the limitations associated with this treatment - including poor engraftment, significant cell death and poor differentiation potential - have prevented its widespread application clinically. To optimize functional improvements provided by transplanted cells, there is a need to develop methods that increase cellular retention and viability, while supporting differentiation and promoting paracrine signaling. Current in vivo models are expensive, difficult to access and manipulate and are time consuming. We have developed an in vitro model of MI which allows for a straightforward, consistent and relatively accurate prediction of cell fate following injection in vivo. The model demonstrated how the infarct environment impairs cellular engraftment and differentiation, but identified an implantation strategy which enhanced cell fate in vitro. Multivariate linear regression identified variables within the model that regulated vascular differentiation potential including oxygen tension, stiffness and cytokine presence, while cardiac differentiation was more accurately predicted by Isl-1 expression in the original cell isolate than any other variable present within the model system. The model highlighted how the cells' sensitivity to the infarct variables varied from line to line, which emphasizes the importance of the model system for the prediction of cell fate on a patient specific basis. Further development of this model system could help predict the clinical efficacy of cardiac progenitor cell therapy at the patient level as well as identify the optimal strategy for cell delivery.