Disparities in outcomes of COVID-19 hospitalizations in native American individuals.

Objectives: This study aimed to investigate COVID-19-related disparities in clinical presentation and patient outcomes in hospitalized Native American individuals. Methods: The study was performed within 30 hospitals of the Banner Health system in the Southwest United States and included 8,083 adult patients who tested positive for SARS-CoV-2 infection and were hospitalized between 1 March 2020 and 4 September 2020. Bivariate and multivariate analyses were used to assess racial and ethnic differences in clinical presentation and patient outcomes. Results: COVID-19-related hospitalizations in Native American individuals were over-represented compared with non-Hispanic white individuals. Native American individuals had fewer symptoms at admission; greater prevalence of chronic lung disease in the older adult; two times greater risk for ICU admission despite being younger; and 20 times more rapid clinical deterioration warranting ICU admission. Compared with non-Hispanic white individuals, Native American individuals had a greater prevalence of sepsis, were more likely to require invasive mechanical ventilation, had a longer length of stay, and had higher in-hospital mortality. Conclusion: Native American individuals manifested greater case-fatality rates following hospitalization than other races/ethnicities. Atypical symptom presentation of COVID-19 included a greater prevalence of chronic lung disease and a more rapid clinical deterioration, which may be responsible for the observed higher hospital mortality, thereby underscoring the role of pulmonologists in addressing such disparities.

Delayed intubation associated with in-hospital mortality in patients with COVID-19 respiratory failure who fail heated and humified high flow nasal canula.

BACKGROUND: Advanced respiratory support modalities such as non-invasive positive pressure ventilation (NiPPV) and heated and humidified high flow nasal canula (HFNC) served as useful alternatives to invasive mechanical ventilatory support for acute respiratory failure (ARF) during the peak of the SARS-CoV-2/COVID-19 pandemic. Unlike NiPPV, HFNC is a newer modality and its role in the treatment of patients with severe ARF is not yet clearly defined. Furthermore, the characteristics of responders versus non-responders to HFNC have not been determined. Although recent evidence indicates that many patients with ARF treated with HFNC survive without needing intubation, those who fail and are subsequently intubated have worse outcomes. Given that prolonged use of HFNC in patients with ARF might exacerbate patient self-inflicted lung injury, we hypothesized that among those patients with ARF due to COVID-19 pneumonia, prolonged HFNC beyond 24 h before intubation would be associated with increased in-hospital mortality. METHODS: This was a retrospective, multicenter, observational cohort study of 2720 patients treated for ARF secondary to SARS-CoV-2/COVID-19 pneumonia and initially managed with HFNC within the Banner Health system during the period from March 1st, 2020, to July 31st, 2021. In the subgroup of patients for went from HFNC to IMV, we assessed the effect of the duration of HFNC prior to intubation on mortality. RESULTS: 1392 (51%) were successfully treated with HFNC alone and 1328 (49%) failed HFNC and were intubated (HFNC to IMV). When adjusted for the covariates, HFNC duration less than 24 h prior to intubation was significantly associated with reduced mortality. CONCLUSIONS: Among patients with ARF due to COVID-19 pneumonia who fail HFNC, delay of intubation beyond 24 h is associated with increased mortality.

Real-Time Automated Sampling of Electronic Medical Records Predicts Hospital Mortality.

BACKGROUND: Real-time automated continuous sampling of electronic medical record data may expeditiously identify patients at risk for death and enable prompt life-saving interventions. We hypothesized that a real-time electronic medical record-based alert could identify hospitalized patients at risk for mortality. METHODS: An automated alert was developed and implemented to continuously sample electronic medical record data and trigger when at least 2 of 4 systemic inflammatory response syndrome criteria plus at least one of 14 acute organ dysfunction parameters was detected. The systemic inflammatory response syndrome and organ dysfunction alert was applied in real time to 312,214 patients in 24 hospitals and analyzed in 2 phases: training and validation datasets. RESULTS: In the training phase, 29,317 (18.8%) triggered the alert and 5.2% of such patients died, whereas only 0.2% without the alert died (unadjusted odds ratio 30.1; 95% confidence interval, 26.1-34.5; P < .0001). In the validation phase, the sensitivity, specificity, area under the curve, and positive and negative likelihood ratios for predicting mortality were 0.86, 0.82, 0.84, 4.9, and 0.16, respectively. Multivariate Cox-proportional hazard regression model revealed greater hospital mortality when the alert was triggered (adjusted hazards ratio 4.0; 95% confidence interval, 3.3-4.9; P < .0001). Triggering the alert was associated with additional hospitalization days (+3.0 days) and ventilator days (+1.6 days; P < .0001). CONCLUSION: An automated alert system that continuously samples electronic medical record data can be implemented, has excellent test characteristics, and can assist in the real-time identification of hospitalized patients at risk for death.