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Soluble ST2 as a Useful Biomarker for Predicting Clinical Outcomes in Hospitalized COVID-19 Patients
- Source :
- Diagnostics, Vol 13, Iss 2, p 259 (2023)
- Publication Year :
- 2023
- Publisher :
- MDPI AG, 2023.
-
Abstract
- Soluble suppression of tumorigenesis-2 (sST2) is an emerging biomarker for sepsis as well as for heart failure. We investigated the prognostic utility of sST2 for predicting clinical outcomes in hospitalized coronavirus disease 2019 (COVID-19) patients. In a total of 52 hospitalized COVID-19 patients, sST2 levels were measured using the ichroma ST2 assay (Boditech Med Inc., Chuncheon-si, Gang-won-do, Republic of Korea). Clinical outcomes included intensive care unit (ICU) admission, ventilator use, extracorporeal membrane oxygenation (ECMO) use, and 30-day mortality. sST2 was analyzed according to clinical outcomes. sST2, sequential organ failure assessment (SOFA) score, critical disease, and 4C mortality score were compared using the receiver operating characteristic (ROC) curve and Kaplan–Meier methods for clinical outcomes. The sST2 level differed significantly according to ICU admission, ventilator use, ECMO use, and 30-day mortality (all p < 0.05). On ROC curve analysis, sST2 predicted ICU admission, ventilator use, ECMO use, and 30-day mortality comparable to SOFA score but significantly better than critical disease. sST2 predicted ICU admission, ventilator use, and ECMO use significantly better than the 4C mortality score. On Kaplan–Meier survival analysis, hazard ratios (95% confidence interval) were 8.4 (2.7–26.8) for sST2, 14.8 (3.0–71.7) for SOFA score, 1.8 (0.5–6.5) for critical disease, and 11.7 (3.4–40.1) for 4C mortality score. This study demonstrated that sST2 could be a useful biomarker to predict ICU admission, ventilator use, ECMO use, and 30-day mortality in hospitalized COVID-19 patients. sST2 may be implemented as a prognostic COVID-19 biomarker in clinical practice.
- Subjects :
- soluble ST2
biomarker
prediction
clinical outcome
COVID-19
Medicine (General)
R5-920
Subjects
Details
- Language :
- English
- ISSN :
- 20754418
- Volume :
- 13
- Issue :
- 2
- Database :
- Directory of Open Access Journals
- Journal :
- Diagnostics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9d0c337f27d54b5ea6357e4531b87e89
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/diagnostics13020259