Respiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study

Abstract

Background: Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs).

Methods: This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support.

Results: A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR [95%CI]; 5.86 [4.83-7.10]), treatment in an LMIC (OR [95%CI]; 2.04 [1.97-2.11]), and tachypnoea at hospital admission (OR [95%CI]; 1.16 [1.14-1.18]). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR [95%CI]; 1.27 [1.25-1.30]).

Conclusions: In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable.

Keywords: COVID-19; Critical care; High flow nasal cannula; Invasive mechanical ventilation.

Fig. 1

Flow chart. This figure shows patients included in the analysis and cohort selection process

Fig. 2

Probability density of patients' basic demographics (age and sex), according to the first ventilation treatment received. A Complete cohort. B Patients from high-income countries. C Patients from low middle-income countries

Fig. 3

Cumulative frequency (net number of patients) of ventilation treatment given to patients. A Complete cohort. B Patients from high-income countries. C Patients from low middle-income countries

Fig. 4

Chord graphic with demographics and comorbidities of patients according to the type of first ventilation treatment received. A Complete cohort. B Patients from high-income countries. C Patients from low middle-income countries

Fig. 5

Alluvia diagram of the patients’ transitions between ventilation treatments and clinical outcomes. The width of the links is proportional to the number of patients. A Complete cohort. B Patients from high-income countries. C Patients from low middle-income countries

Fig. 6

An automatised model to determine risk factors associated with non-invasive ventilation failure. A variables more strongly related to non-invasive ventilation failure according to the Gini importance. B the contribution of the variables to the output; the red values indicate a high-value contribution of the variable, and the blue values a low-value contribution. The positive values in the plot indicate a high probability of 28-day fatality, and negative values indicate a low likelihood of 28-day fatality. Panel C presents a logistic regression model, showing variables more strongly associated with the 28-day fatality ratio. The most significant variables were leucocyte count, low-/middle-income country attention, higher respiratory rate, and higher systolic blood pressure

Fig. 7

An automatised model to determine risk factors associated with the 28-day fatality ratio. A The contribution of the variables to the output; the red values indicate a high-value contribution of the variable, and the blue values a low-value contribution. The positive values in the plot indicate a high probability of 28 fatalities, and negative values indicate a low likelihood of 28-day fatality. B A logistic regression model, showing variables more strongly associated with the 28-day fatality ratio. C Each cross-validation trial's receiver operative curve (ROC) for the subset of the selected variables. The blue curve represents the average of the ROC curves of each test, and the average area under the ROC is also presented. The most significant variables associated with the 28-day fatality ratio were age, cardiac arrest, low-/middle-income country attention, and leucocyte count. Also, patients that fail the non-invasive or high-flow nasal cannula are independently associated with a higher 28-day fatality ratio