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BackgroundRacial disparities in trauma care have been reported for a range of outcomes, but the extent to which these remain after accounting for socioeconomic and environmental factors remains unclear. The objective of this study was to evaluate the unique contributions of race, health insurance, community distress, and rurality/urbanicity on trauma outcomes after carefully controlling for specific injury-related risk factors.MethodsAll adult (age, ≥18 years) trauma patients admitted to a single Level I trauma center with a statewide, largely rural, catchment area from January 2010 to December 2020 were retrospectively reviewed. Primary outcomes were mortality, rehabilitation referral, and receipt of opioids in the emergency department. Demographic, socioeconomic, and injury characteristics as well as indicators of community distress and rurality based on home address were abstracted from a trauma registry database.ResultsAnalyses revealed that Black patients (n = 13,073) were younger, more likely to be male, more likely to suffer penetrating injuries, and more likely to suffer assault-based injuries compared with White patients (n = 10,946; all p < 0.001). In adjusted analysis, insured patients had a 28% lower risk of mortality (odds ratio, 0.72; p = 0.005) and were 92% more likely to be referred for postdischarge rehabilitation than uninsured patients (odds ratio, 1.92; p = 0.005). Neither race- nor place-based factors were associated with mortality. However, post hoc analyses revealed a significant race by age interaction, with Black patients exhibiting more pronounced increases in mortality risk with increasing age.ConclusionThe present findings help disentangle the social determinants of trauma disparities by adjusting for place and person characteristics. Uninsured patients were more likely to die and those who survived were less likely to receive referrals for rehabilitation services. The expected racial disparity in mortality risk favoring White patients emerged in middle age and was more pronounced for older patients.Level of evidencePrognostic and epidemiological, Level III.

Objective The aim of the study is to determine clinical correlates of moderate to severe bronchopulmonary dysplasia (BPD) in preterm infants following surgical necrotizing enterocolitis (NEC). Study Design This is a retrospective, single-center cohort study comparing patients with moderate to severe BPD to patients with non/mild BPD among surgical NEC infants. BPD was defined by NIH 2001 consensus definition. Results Of 92 consecutive neonates with surgical NEC, 77% (71/92) had moderate/severe BPD and 22% (21/92) had non/mild BPD. The patent ductus arteriosus (PDA) was significantly higher in those developing moderate/severe BPD (67.6% [48/71]) than non/mild BPD (28.6% [6/21]; p = 0.001). Postoperatively, infants with moderate/severe BPD had more severe acute kidney injury (AKI; 67.6 [48/71] vs. 28.6% [6/21]; p = 0.001), were intubated longer (40.5 [interquartile (IQR): 12, 59] vs. 6 days [IQR: 2, 13]; p <0.001), received more parenteral nutrition (109 [IQR: 77, 147] vs. 55 days [IQR: 19, 70]; p <0.001), developed higher surgical morbidity (46.5 [33/71] vs. 14.3% [3/21]; p = 0.008), had more intestinal failure (62.5 vs. 13.3%; p <0.001), required a longer hospital stay (161 [IQR: 112, 186] vs. 64 days [IQR: 20, 91]; p <0.001), and were more likely to need home oxygen. In a multivariable analysis, lower birth weight (OR = 0.3, [95% confidence interval (CI): 0.1–0.5]; p = 0.001), PDA (OR = 10.3, [95% CI: 1.6–65.4]; p = 0.014), and longer parenteral nutritional days (OR = 8.8; [95% CI: 2.0–43.0]; p = 0.005) were significantly and independently associated with higher odds of moderate/severe versus non-/mild BPD. Conclusion Development of moderate/severe BPD occurred in the majority of preterm infants with surgical NEC in this consecutive series. Preterm infants with moderate/severe BPD were more likely to have a PDA before NEC. Development of moderate/severe BPD was associated with significantly greater burden and duration of postoperative morbidity following surgical NEC. Identifying surgical NEC infants at increased risk of moderate/severe BPD and developing lung protection strategies may improve surgical NEC outcomes. Key Points Three-fourths of preterm infants experienced severe lung injury following surgical NEC. The infants with severe moderate/severe BPD were most likely associated with greater duration of postoperative morbidity. There is need to understand and develop lung protective strategies in infants with surgical NEC. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has demonstrated the need for efficient and comprehensive, simultaneous assessment of multiple combined novel therapies for viral infection across the range of illness severity. Randomized Controlled Trials (RCT) are the gold standard by which efficacy of therapeutic agents is demonstrated. However, they rarely are designed to assess treatment combinations across all relevant subgroups. A big data approach to analyzing real-world impacts of therapies may confirm or supplement RCT evidence to further assess effectiveness of therapeutic options for rapidly evolving diseases such as COVID-19. Methods: Gradient Boosted Decision Tree, Deep and Convolutional Neural Network classifiers were implemented and trained on the National COVID Cohort Collaborative (N3C) data repository to predict the patients' outcome of death or discharge. Models leveraged the patients' characteristics, the severity of COVID-19 at diagnosis, and the calculated proportion of days on different treatment combinations after diagnosis as features to predict the outcome. Then, the most accurate model is utilized by eXplainable Artificial Intelligence (XAI) algorithms to provide insights about the learned treatment combination impacts on the model's final outcome prediction. Results: Gradient Boosted Decision Tree classifiers present the highest prediction accuracy in identifying patient outcomes with area under the receiver operator characteristic curve of 0.90 and accuracy of 0.81 for the outcomes of death or sufficient improvement to be discharged. The resulting model predicts the treatment combinations of anticoagulants and steroids are associated with the highest probability of improvement, followed by combined anticoagulants and targeted antivirals. In contrast, monotherapies of single drugs, including use of anticoagulants without steroid or antivirals are associated with poorer outcomes. Conclusions: This machine learning model by accurately predicting the mortality provides insights about the treatment combinations associated with clinical improvement in COVID-19 patients. Analysis of the model's components suggests benefit to treatment with combination of steroids, antivirals, and anticoagulant medication. The approach also provides a framework for simultaneously evaluating multiple real-world therapeutic combinations in future research studies. [ABSTRACT FROM AUTHOR]

Background: While COVID-19 vaccines reduce adverse outcomes, post-vaccination SARS-CoV-2 infection remains problematic. We sought to identify community factors impacting risk for breakthrough infections (BTI) among fully vaccinated persons by rurality. Methods: We conducted a retrospective cohort study of US adults sampled between January 1 and December 20, 2021, from the National COVID Cohort Collaborative (N3C). Using Kaplan-Meier and Cox-Proportional Hazards models adjusted for demographic differences and comorbid conditions, we assessed impact of rurality, county vaccine hesitancy, and county vaccination rates on risk of BTI over 180 days following two mRNA COVID-19 vaccinations between January 1 and September 21, 2021. Additionally, Cox Proportional Hazards models assessed the risk of infection among adults without documented vaccinations. We secondarily assessed the odds of hospitalization and adverse COVID-19 events based on vaccination status using multivariable logistic regression during the study period. Results: Our study population included 566,128 vaccinated and 1,724,546 adults without documented vaccination. Among vaccinated persons, rurality was associated with an increased risk of BTI (adjusted hazard ratio [aHR] 1.53, 95% confidence interval [CI] 1.42–1.64, for urban-adjacent rural and 1.65, 1.42–1.91, for nonurban-adjacent rural) compared to urban dwellers. Compared to low vaccine-hesitant counties, higher risks of BTI were associated with medium (1.07, 1.02–1.12) and high (1.33, 1.23–1.43) vaccine-hesitant counties. Compared to counties with high vaccination rates, a higher risk of BTI was associated with dwelling in counties with low vaccination rates (1.34, 1.27–1.43) but not medium vaccination rates (1.00, 0.95–1.07). Community factors were also associated with higher odds of SARS-CoV-2 infection among persons without a documented vaccination. Vaccinated persons with SARS-CoV-2 infection during the study period had significantly lower odds of hospitalization and adverse events across all geographic areas and community exposures. Conclusions: Our findings suggest that community factors are associated with an increased risk of BTI, particularly in rural areas and counties with high vaccine hesitancy. Communities, such as those in rural and disproportionately vaccine hesitant areas, and certain groups at high risk for adverse breakthrough events, including immunosuppressed/compromised persons, should continue to receive public health focus, targeted interventions, and consistent guidance to help manage community spread as vaccination protection wanes. [ABSTRACT FROM AUTHOR]

Purpose: Rural communities are among the most underserved and resource‐scarce populations in the United States. However, there are limited data on COVID‐19 outcomes in rural America. This study aims to compare hospitalization rates and inpatient mortality among SARS‐CoV‐2‐infected persons stratified by residential rurality. Methods: This retrospective cohort study from the National COVID Cohort Collaborative (N3C) assesses 1,033,229 patients from 44 US hospital systems diagnosed with SARS‐CoV‐2 infection between January 2020 and June 2021. Primary outcomes were hospitalization and all‐cause inpatient mortality. Secondary outcomes were utilization of supplemental oxygen, invasive mechanical ventilation, vasopressor support, extracorporeal membrane oxygenation, and incidence of major adverse cardiovascular events or hospital readmission. The analytic approach estimates 90‐day survival in hospitalized patients and associations between rurality, hospitalization, and inpatient adverse events while controlling for major risk factors using Kaplan‐Meier survival estimates and mixed‐effects logistic regression. Findings: Of 1,033,229 diagnosed COVID‐19 patients included, 186,882 required hospitalization. After adjusting for demographic differences and comorbidities, urban‐adjacent and nonurban‐adjacent rural dwellers with COVID‐19 were more likely to be hospitalized (adjusted odds ratio [aOR] 1.18, 95% confidence interval [CI], 1.16‐1.21 and aOR 1.29, CI 1.24‐1.1.34) and to die or be transferred to hospice (aOR 1.36, CI 1.29‐1.43 and 1.37, CI 1.26‐1.50), respectively. All secondary outcomes were more likely among rural patients. Conclusions: Hospitalization, inpatient mortality, and other adverse outcomes are higher among rural persons with COVID‐19, even after adjusting for demographic differences and comorbidities. Further research is needed to understand the factors that drive health disparities in rural populations. [ABSTRACT FROM AUTHOR]