Soluble IL-2R Levels at Baseline Predict the Development of Severe Respiratory Failure and Mortality in COVID-19 Patients.
Viruses
; 14(4)2022 04 10.
Article
in English
| MEDLINE | ID: covidwho-1786081
ABSTRACT
Risk stratification of coronavirus disease-19 (COVID-19) patients by simple markers is critical to guide treatment. We studied the predictive value of soluble interleukin-2 receptor (sIL-2R) for the early identification of patients at risk of developing severe clinical outcomes. sIL-2R levels were measured in 197 patients (60.9% males; median age 61 years; moderate disease, n = 65; severe, n = 132, intubated and/or died, n = 42). All patients received combined immunotherapies (anakinra ± corticosteroids ± intravenous immunoglobulin ± tocilizumab) according to our local treatment algorithm. The endpoint was the composite event of intubation due to severe respiratory failure (SRF) or mortality. Median (interquartile range) sIL-2R levels were significantly higher in patients with severe disease, compared with those with moderate disease (6 (6.2) vs. 5.2 (3.4) ng/mL, p = 0.017). sIL-2R was the strongest laboratory predictive factor for intubation/death (hazard ratio 1.749, 95%CI 1.041-2.939, p = 0.035) after adjustment for other known risk factors. Youden's index revealed optimal sIL-2R cut-off for predicting intubation/death at 9 ng/mL (sensitivity 67%; specificity 86%; positive and negative predictive value 57% and 91%, respectively). Delta sIL-2R between the day of event or discharge minus admission date was higher in patients that intubated/died than in those who did not experience an event (2.91 (10.42) vs. 0.44 (2.88) ng/mL; p = 0.08)). sIL-2R on admission and its dynamic changes during follow-up may reflect disease severity and predict the development of SRF and mortality.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Respiratory Insufficiency
/
Receptors, Interleukin-2
/
COVID-19
Type of study:
Cohort study
/
Diagnostic study
/
Prognostic study
Limits:
Female
/
Humans
/
Male
/
Middle aged
Language:
English
Year:
2022
Document Type:
Article
Affiliation country:
V14040787
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