Dynamics of disease characteristics and clinical management of critically ill COVID-19 patients over the time course of the pandemic: an analysis of the prospective, international, multicentre RISC-19-ICU registry

Abstract

Background: It remains elusive how the characteristics, the course of disease, the clinical management and the outcomes of critically ill COVID-19 patients admitted to intensive care units (ICU) worldwide have changed over the course of the pandemic.

Methods: Prospective, observational registry constituted by 90 ICUs across 22 countries worldwide including patients with a laboratory-confirmed, critical presentation of COVID-19 requiring advanced organ support. Hierarchical, generalized linear mixed-effect models accounting for hospital and country variability were employed to analyse the continuous evolution of the studied variables over the pandemic.

Results: Four thousand forty-one patients were included from March 2020 to September 2021. Over this period, the age of the admitted patients (62 [95% CI 60-63] years vs 64 [62-66] years, p < 0.001) and the severity of organ dysfunction at ICU admission decreased (Sequential Organ Failure Assessment 8.2 [7.6-9.0] vs 5.8 [5.3-6.4], p < 0.001) and increased, while more female patients (26 [23-29]% vs 41 [35-48]%, p < 0.001) were admitted. The time span between symptom onset and hospitalization as well as ICU admission became longer later in the pandemic (6.7 [6.2-7.2| days vs 9.7 [8.9-10.5] days, p < 0.001). The PaO₂/FiO₂ at admission was lower (132 [123-141] mmHg vs 101 [91-113] mmHg, p < 0.001) but showed faster improvements over the initial 5 days of ICU stay in late 2021 compared to early 2020 (34 [20-48] mmHg vs 70 [41-100] mmHg, p = 0.05). The number of patients treated with steroids and tocilizumab increased, while the use of therapeutic anticoagulation presented an inverse U-shaped behaviour over the course of the pandemic. The proportion of patients treated with high-flow oxygen (5 [4-7]% vs 20 [14-29], p < 0.001) and non-invasive mechanical ventilation (14 [11-18]% vs 24 [17-33]%, p < 0.001) throughout the pandemic increased concomitant to a decrease in invasive mechanical ventilation (82 [76-86]% vs 74 [64-82]%, p < 0.001). The ICU mortality (23 [19-26]% vs 17 [12-25]%, p < 0.001) and length of stay (14 [13-16] days vs 11 [10-13] days, p < 0.001) decreased over 19 months of the pandemic.

Conclusion: Characteristics and disease course of critically ill COVID-19 patients have continuously evolved, concomitant to the clinical management, throughout the pandemic leading to a younger, less severely ill ICU population with distinctly different clinical, pulmonary and inflammatory presentations than at the onset of the pandemic.

Trial registration: ClinicalTrials.gov NCT04357275.

Keywords: ARDS; COVID-19; Disease dynamics; Intensive care unit; Pandemic.

Fig. 1

Dynamics of baseline characteristics over the pandemic. Mean effects over the time course of the pandemic, calculated by means of generalized mixed-effect models, are depicted by a red continuous line. 95% confidence intervals of the effect are depicted as shaded red area. The given p values originate from an analysis of deviance. Continuous variables are represented by topographic density plots, in which the intensity of the grayscale colouring indicates the highest concentration of values. Categorical variables are represented by violin plots, in which the segmental width of the plot correlates with the concentration of values

Fig. 2

Dynamics of vitals and laboratory parameters at intensive care unit admission. Mean effects over the time course of the pandemic, calculated by means of generalized mixed-effect models, are depicted by a red continuous line. 95% confidence intervals of the effect are depicted as shaded red area. The given p values originate from an analysis of deviance. Variables are represented by topographic density plots, in which the intensity of the grayscale colouring indicates the highest concentration of values

Fig. 3

Dynamics of the evolution of vital and laboratory parameters during the first 5 days of intensive care unit stay. To capture the changes in the dynamics of disease over the first days of intensive care unit stay, the difference of a variable between day 5 and day 1 is summarized as parameter (Delta) over time. Mean effects over the time course of the pandemic, calculated by means of generalized mixed-effect models, are depicted by a red continuous line. 95% confidence intervals of the effect are depicted as shaded red area. The given p values originate from an analysis of deviance. Variables are represented by topographic density plots, in which the intensity of the grayscale colouring indicates the highest concentration of values

Fig. 4

Dynamics of medication management. Mean effects over the time course of the pandemic, calculated by means of generalized mixed-effect models, are depicted by a red continuous line. 95% confidence intervals of the effect are depicted as shaded red area. The given p values originate from an analysis of deviance

Fig. 5

Dynamics of organ support management and outcomes. Mean effects over the time course of the pandemic, calculated by means of generalized mixed-effect models, are depicted by a red continuous line. 95% confidence intervals of the effect are depicted as shaded red area. The given p values originate from an analysis of deviance. Continuous variables are represented by topographic density plots, in which the intensity of the grayscale colouring indicates the highest concentration of values. Categorical variables are represented by violin plots, in which the segmental width of the plot correlates with the concentration of values. IMV invasive mechanical ventilation