Evolving changes in mortality of 13,301 critically ill adult patients with COVID-19 over 8 months

Abstract

Purpose: Clinical characteristics and management of COVID-19 patients have evolved during the pandemic, potentially changing their outcomes. We analyzed the associations of changes in mortality rates with clinical profiles and respiratory support strategies in COVID-19 critically ill patients.

Methods: A multicenter cohort of RT-PCR-confirmed COVID-19 patients admitted at 126 Brazilian intensive care units between February 27^th and October 28^th, 2020. Assessing temporal changes in deaths, we identified distinct time periods. We evaluated the association of characteristics and respiratory support strategies with 60-day in-hospital mortality using random-effects multivariable Cox regression with inverse probability weighting.

Results: Among the 13,301 confirmed-COVID-19 patients, 60-day in-hospital mortality was 13%. Across four time periods identified, younger patients were progressively more common, non-invasive respiratory support was increasingly used, and the 60-day in-hospital mortality decreased in the last two periods. 4188 patients received advanced respiratory support (non-invasive or invasive), from which 42% underwent only invasive mechanical ventilation, 37% only non-invasive respiratory support and 21% failed non-invasive support and were intubated. After adjusting for organ dysfunction scores and premorbid conditions, we found that younger age, absence of frailty and the use of non-invasive respiratory support (NIRS) as first support strategy were independently associated with improved survival (hazard ratio for NIRS first [95% confidence interval], 0.59 [0.54-0.65], p < 0.001).

Conclusion: Age and mortality rates have declined over the first 8 months of the pandemic. The use of NIRS as the first respiratory support measure was associated with survival, but causal inference is limited by the observational nature of our data.

Keywords: Coronavirus; In-hospital mortality; Non-invasive ventilation; Respiratory support.

Fig. 1

Progression of adult ICU admissions with COVID-19 from February 27^th, 2020 to October 28^th, 2020. a Total patients in the ICU per day; b the number of new ICU admissions per day; c the number of deaths in the ICU per day; and d the daily mortality rate in the ICU (using the admission date as the reference). The black line represents daily absolute numbers, and the blue line is the smoothed curve. The three dashed lines correspond to the estimated breakpoints of structure change in the time series of ICU deaths rate panel (c): April 25^th, June 06^th, and August 10^th, respectively.

Fig. 2

Univariable survival curves (Kaplan–Meier) of factors related to the 60-day outcome in critically ill patients who underwent advanced respiratory support. a Time periods estimated with the breakpoints of structure change (Period 1: February 27^th to April 25^th; Period 2: April 26^th to June 6^th; Period 3: June 7^th to August 10^th; Period 4: August 11^th to October 28^th); b age (< 40, 40–49, 50–59, 60–69, 70–79, and ≥ 80; c Modified Frailty Index (MFI) at the admission, with groups non-frail (MFI = 0), pre-frail (MFI = 1–2) and frail (MFI ≥ 3); and d initial respiratory support considering non-invasive (NIRS first) invasive (IMV first). Differences among curves were assessed using the log-rank test with a confidence level of 0.05.

Fig. 3

Random-effects multivariable cox proportional hazards model to assess the association of clinical characteristics and initial respiratory support with 60-day mortality in patients who underwent advanced ventilatory support (NIRS and/or IMV), adjusted by the time-period of admission. The hospital was considered as the random intercept (standard deviation = 0.50). To account for the non randomization, we used inverse-probability treatment weighting (IPTW) of propensity scores regarding the initial use of NIRS. We provide the hazard ratio (HR) for 60-day in-hospital mortality and its respective 95% confidence intervals for each variable