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

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-04065-2.

Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients

Background

Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest for the development of prediction models as they excel in the analysis of complex signals in data-rich environments such as critical care.

Methods

We retrieved data on patients with COVID-19 admitted to an intensive care unit (ICU) between March and October 2020 from the RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry. We applied the Extreme Gradient Boosting (XGBoost) algorithm to the data to predict as a binary outcome the increase or decrease in patients' Sequential Organ Failure Assessment (SOFA) score on day 5 after ICU admission. The model was iteratively cross-validated in different subsets of the study cohort.

Results

The final study population consisted of 675 patients. The XGBoost model correctly predicted a decrease in SOFA score in 320/385 (83%) critically ill COVID-19 patients, and an increase in the score in 210/290 (72%) patients. The area under the mean receiver operating characteristic curve for XGBoost was significantly higher than that for the logistic regression model (0.86 vs. 0.69, P < 0.01 [paired t-test with 95% confidence interval]).

Conclusions

The XGBoost model predicted the change in SOFA score in critically ill COVID-19 patients admitted to the ICU and can guide clinical decision support systems (CDSSs) aimed at optimizing available resources.

Implications of early respiratory support strategies on disease progression in critical COVID-19: a matched subanalysis of the prospective RISC-19-ICU cohort

BACKGROUND

Uncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is widespread. While the risks and benefits of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefits of different respiratory support strategies, employed in intensive care units during the first months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates.

METHODS

Subanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclassified into standard oxygen therapy ≥10 L/min (SOT), high-flow oxygen therapy (HFNC), noninvasive positive-pressure ventilation (NIV), and early IMV, according to the respiratory support strategy employed at the day of admission to ICU. Propensity score matching was performed to ensure comparability between groups.

RESULTS

Initially, 1421 patients were assessed for possible study inclusion. Of these, 351 patients (85 SOT, 87 HFNC, 87 NIV, and 92 IMV) remained eligible for full analysis after propensity score matching. 55% of patients initially receiving noninvasive respiratory support required IMV. The intubation rate was lower in patients initially ventilated with HFNC and NIV compared to those who received SOT (SOT: 64%, HFNC: 52%, NIV: 49%, p = 0.025). Compared to the other respiratory support strategies, NIV was associated with a higher overall ICU mortality (SOT: 18%, HFNC: 20%, NIV: 37%, IMV: 25%, p = 0.016).

CONCLUSION

In this cohort of critically ill patients with COVID-19, a trial of HFNC appeared to be the most balanced initial respiratory support strategy, given the reduced intubation rate and comparable ICU mortality rate. Nonetheless, considering the uncertainty and stress associated with the COVID-19 pandemic, SOT and early IMV represented safe initial respiratory support strategies. The presented findings, in agreement with classic ARDS literature, suggest that NIV should be avoided whenever possible due to the elevated ICU mortality risk.