Related Experiment Video
Updated: Jun 27, 2026
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
sTREM-1 as a Predictive Biomarker for Disease Severity and Prognosis in COVID-19 Patients
Nan Geng1, Zhipeng Wu2,3,4, Zhao Liu1
1Department of Emergency Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, 100069, People's Republic of China.
Insights
Soluble TREM-1 (sTREM-1) levels correlate with COVID-19 severity and mortality. Elevated sTREM-1 is an independent predictor of adverse outcomes, improving prognostic accuracy when combined with other biomarkers.
Area of Science:
- Immunology
- Infectious Diseases
- Biomarker Discovery
Background:
- COVID-19 severity and prognosis research is crucial for patient outcomes.
- Limited data exists on soluble TREM-1 (sTREM-1) as a prognostic marker in COVID-19.
Purpose of the Study:
- To investigate the role of sTREM-1 in predicting COVID-19 severity and prognosis.
- To evaluate sTREM-1 as a potential biomarker for adverse outcomes in COVID-19 patients.
Main Methods:
- 115 COVID-19 patients were analyzed for demographic data, lab measurements, and plasma sTREM-1 levels.
- Statistical analyses, including ROC curves and multivariate logistic regression, were employed.
Main Results:
- sTREM-1 levels increased with COVID-19 disease severity.
- sTREM-1 showed good predictive value for severity (AUC=0.762) and 28-day mortality (AUC=0.805).
- sTREM-1, HGB, D-dimer, and CAR were independent predictors of 28-day mortality (combined AUC=0.919).
Conclusions:
- sTREM-1 is a valuable predictor of COVID-19 severity and mortality.
- sTREM-1 serves as an independent prognostic factor for adverse patient outcomes.
- Further large-scale multicenter studies are warranted to validate these findings.
Background:
Research on biomarkers associated with the severity and adverse prognosis of COVID-19 can be beneficial for improving patient outcomes. However, there is limited research on the role of soluble TREM-1 (sTREM-1) in predicting the severity and prognosis of COVID-19 patients.
Methods:
A total of 115 COVID-19 patients admitted to the emergency department of Beijing Youan Hospital from February to May 2023 were included in the study. Demographic information, laboratory measurements, and blood samples for sTREM-1 levels were collected upon admission.
Results:
Our study found that sTREM-1 levels in the plasma of COVID-19 patients increased with the severity of the disease (moderate vs mild, p=0.0013; severe vs moderate, p=0.0195). sTREM-1 had good predictive value for disease severity and 28-day mortality (area under the ROC curve was 0.762 and 0.805, respectively). sTREM-1 also exhibited significant correlations with age, body temperature, respiratory rate, PaO2/FiO2, PCT, CRP, and CAR. Ultimately, through multivariate logistic regression analysis, we determined that sTREM-1 (OR 1.008, 95% CI: 1.002-1.013, p=0.005), HGB (OR 0.966, 95% CI: 0.935-0.998, p=0.036), D-dimer (OR 1.001, 95% CI: 1.000-1.001, p=0.009), and CAR (OR 1.761, 95% CI: 1.154-2.688, p=0.009) were independent predictors of 28-day mortality in COVID-19 patients. The combination of these four markers yielded a strong predictive value for 28-day mortality in COVID-19 cases with an AUC of 0.919 (95% CI: 0.857 -0.981).
Conclusion:
sTREM-1 demonstrated good predictive value for disease severity and 28-day mortality, serving as an independent prognostic factor for adverse patient outcomes. In the future, we anticipate conducting large-scale multicenter studies to validate our research findings.
