Mortality in a swiftly repurposed hospital in northeast Brazil during the first and second COVID-19 waves: A retrospective cohort study.

Background: The first months of the coronavirus disease 2019 (COVID-19) pandemic demanded rapid re-organization of available local resources. This study evaluated the performance of a private hospital in the Brazilian state of Ceará that was swiftly repurposed into a public tertiary COVID-19 centre during the first wave of the COVID-19 pandemic, and how it improved in the second wave. Methods: This retrospective cohort study included 2492 patients with COVID-19 at Hospital Estadual Leonardo da Vinci (HELV) during the first and second waves. Demographic, clinical and laboratory data were collected using a dedicated web platform (ResCOVID). A Poisson regression model was used to estimate factors associated with in-hospital mortality. Results: Differences in demographics and clinical features were found between the two waves. There was reduced in-hospital mortality during the second wave (36.2%) in comparison with the first wave (48.8%). Invasive mechanical ventilation showed the strongest association with increased risk of death in both waves {first wave: relative risk (RR) 4.28 [95% confidence interval (CI) 2.86-6.41], P<0.001; second wave: RR 12.94 (95% CI 3.4-49.12), P<0.001}. Conclusions: HELV was a pillar in the strategic public health plan to respond to COVID-19 in Ceará, helping to assist a group of moderate-to-severe cases and reduce the pressure on emergency and primary care facilities. Although mortality in intubated individuals remained high, there was an overall decrease in the in-hospital mortality rate in the second wave.

Effect of an automatic triggering and cycling system on comfort and patient-ventilator synchrony during pressure support ventilation.

BACKGROUND: The digital Auto-Trak™ system is a technology capable of automatically adjusting the triggering and cycling mechanisms during pressure support ventilation (PSV). OBJECTIVE: To compare Auto-Trak with conventional settings in terms of patient-ventilator synchrony and discomfort. METHODS: Twelve healthy volunteers underwent PSV via the mouth by breathing through an endotracheal tube. In the conventional setting, a pressure support of 8 cm H2O with flow cycling (25% peak inspiratory flow) and a sensitivity of 1 cm H2O was adjusted. In Auto-Trak the triggering and cycling were automatically set. Discomfort, effort of breathing, and the asynchrony index (AI) were assessed. In a complementary bench study, the inspiratory and expiratory time delays were quantified for both settings in three mechanical models: 'normal', obstructive (COPD), and restrictive (ARDS), using the ASL 5000 simulator. RESULTS: In the volunteer study the AI and the discomfort scores did not differ statistically between the two settings. In the bench investigation the use of Auto-Trak was associated with a greater triggering delay in the COPD model and earlier expiratory cycling in the ARDS model but with no asynchronic events. CONCLUSIONS: Use of the Auto-Trak system during PSV showed similar results in comparison to the conventional adjustments with respect to patient-ventilator synchrony and discomfort in simulated conditions of invasive mechanical ventilation.