Does the IL-6/KL-6 ratio distinguish different phenotypes in COVID-19 Acute Respiratory Distress Syndrome? An observational study stemmed from prospectively derived clinical, biological, and computed tomographic data

Abstract

Background: As new SARS-CoV-2 variants emerge and as treatment of COVID-19 ARDS remains exclusively supportive, there is an unmet need to better characterize its different phenotypes to tailor personalized treatments. Clinical, biological, spirometric and CT data hardly allow deciphering of Heavy (H), Intermediate (I) and Light (L) phenotypes of COVID-19 ARDS and the implementation of tailored specific strategies (prone positioning, PEEP settings, recruitment maneuvers). We hypothesized that the ratio of two pivotal COVID-19 biomarkers (interleukin 6 [IL-6] and Krebs von den Lungen 6 [KL-6], related to inflammation and pneumocyte repair, respectively) would provide a biologic insight into the disease timeline allowing 1) to differentiate H, I and L phenotypes, 2) to predict outcome and 3) to reflect some of CT findings.

Methods and findings: This was a retrospective analysis of prospectively acquired data (COVID HUS cohort). Inclusion concerned any patient with severe COVID-19 pneumonia admitted to two intensive care units between March 1st and May 1st, 2020, in a high-density cluster of the first epidemic wave (Strasbourg University Hospital, France). Demographic, clinical, biological (standard, IL-6 [new generation ELISA], KL-6 [CLEIA technique]), spirometric (driving pressure, respiratory system compliance) and CT data were collected longitudinally. CT analysis included semi-automatic and automatic lung measurements and allowed segmentation of lung volumes into 4 (poorly aerated, non-aerated, overinflated and normally aerated) and 3 (ground-glass, restricted normally aerated, and overinflated) zones, respectively. The primary outcome was to challenge the IL-6/KL-6 ratio capacity to decipher the three COVID-19 ARDS phenotypes (H, I and L) defined on clinical, spirometric and radiologic grounds. Secondary outcomes were the analysis of the prognostic value of the IL-6/KL-6 ratio and its correlates with CT-acquired data. Multivariate analysis was based on principal component analysis. One hundred and forty-eight ventilated COVID-19 ICU patients from the COVID HUS cohort were assessed for eligibility and 77 were included in the full analysis. Most were male, all were under invasive mechanical ventilation and vasopressor therapy and displayed high severity scores (SAPSII: 48 [42-56]; SOFA: 8 [7-10]). The L, I and H COVID ARDS phenotypes were identified in 11, 15 and 48 patients, respectively. In three patients, the phenotype could not be defined precisely. Thirty patients (39%) died in the ICU and the number of ventilator-free days was 2 [0-2] days. The IL-6/KL-6 ratio was not significantly different between the L, I and H phenotypes and evolved according to similar patterns over time. Surviving and deceased patients displayed an inverse kinetic of KL-6. IL-6 and the IL-6/KL-6 ratio were linearly associated with ground-glass volume on semi-automatic and automatic CT lung measurements.

Conclusions: In our population of severe ventilated COVID ARDS patients, the IL-6/KL-6 ratio was not clue to differentiate the H, I and L phenotypes and tailor a personalized ventilatory approach. There was an interesting correlation between IL-6/KL-6 ratio and ground-glass volume as determined by automated lung CT analysis. Such correlation deserves more in-depth pathophysiological study, at best gathered from a prospective cohort with a larger sample size and histological analysis.

Trial registration: COVID HUS Trial registration number: NCT04405726.

Fig 1. a Lung variables and corresponding volumes.

Summary of all pulmonary variables collected and its corresponding volumes (mL), depending on the type of method (either semi-automatic or automatic) used. b The different lung volumes.

Fig 2. Study Flowchart.

The baseline characteristics of the study cohort patients are presented in Tables 1–3.

Fig 3. Time course of log IL-6/KL-6 among the L, I and H phenotypes.

Values are mean plus/minus standard deviation. Negative values are possible because they are predicted values. For each phenotype, 5 time points were considered (D1, D7, D14, D21, D28). Linear mixed model; p=0.411.

Fig 4. Time course of log IL-6/KL-6 and risk of death in patients with COVID-19 ARDS. Values are means plus/minus standard deviations. Negative values are possible because they are predicted values. Five time points were considered (D1, D7, D14, D21, D28). Linear mixed model, p=0.838.

Fig 5. Time course of log IL-6 over time among the L, I and H phenotypes. Values are means plus/minus standard deviations. Negative values are possible because they are predicted values. For each phenotype, 5 time points were considered (D1, D7, D14, D21, D28). Linear mixed model, p=0.175.

Fig 6. Time course of Log IL-6 and risk of death in patients with COVID-19 ARDS.

Values are means plus/minus standard deviations. Five time points were considered (D1, D7, D14, D21, D28). Linear mixed model, p=0.736.

Fig 7. Time course of log KL-6 among the L, I and H phenotypes.

Values are means plus/minus standard deviation. Five time points were considered (D1, D7, D14, D21, D28). Linear mixed model, p=0.487.

Fig 8. Time course of log KL-6 and risk of death in patients with COVID-19 ARDS.

Values are means plus/minus standard deviation. Five time points were considered (D1, D7, D14, D21, D28). Linear mixed model, p=0.016.

Fig 9. Exploratory PCA on Winsorized data.