sTREM-1 as a Predictive Biomarker for Disease Severity and Prognosis in COVID-19 Patients

Nan Geng; Zhipeng Wu; Zhao Liu; Wen Pan; Yueke Zhu; Hongbo Shi; Ying Han; Yingmin Ma; Bo Liu

doi:10.2147/JIR.S464789

sTREM-1 as a Predictive Biomarker for Disease Severity and Prognosis in COVID-19 Patients

J Inflamm Res. 2024 Jun 17:17:3879-3891. doi: 10.2147/JIR.S464789. eCollection 2024.

Authors

Nan Geng^#¹, Zhipeng Wu^#^{2

3

4}, Zhao Liu¹, Wen Pan¹, Yueke Zhu¹, Hongbo Shi³, Ying Han⁵, Yingmin Ma^{2

3

4}, Bo Liu¹

Affiliations

¹ Department of Emergency Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, 100069, People's Republic of China.
² Department of Respiratory and Critical Care Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, 100069, People's Republic of China.
³ Beijing Institute of Hepatology, Beijing Youan Hospital, Capital Medical University, Beijing, 100069, People's Republic of China.
⁴ Beijing Research Center for Respiratory Infectious Diseases, Beijing, 100013, People's Republic of China.
⁵ Department of Gastroenterology and Hepatology, Beijing Youan Hospital, Capital Medical University, Beijing, 100069, People's Republic of China.

^# Contributed equally.

Abstract

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.

Keywords: 28-day mortality; COVID-19; disease severity; inflammation-related markers; sTREM-1.

Grants and funding

This work was supported by National Key Research and Development Program of China [Grant No. 2022YFC2305002], Beijing municipal medical research institute public welfare development and reform pilot project [Grant No. jingyiyan2021-10], COVID-19 Special Project of Beijing You’an Hospital [Grant No. 2023-6], Middle-aged and Young Talent Incubation Programs (Clinical Research) of Beijing You’an Hospital [Grant No. BJYAYY-YN2022-12, BJYAYY-YN2022-13], Beijing research center for respiratory infectious diseases project [Grant No. BJRID2024-001], Beijing Natural Science Foundation [Grant No. M22030] and Beijing Natural Science Foundation [Grant No. 7232079].