Application of novel markers in assessing the severity and prognosis of patients with acute bloodstream infection_West China Medical Journal

Authors：

GUO Mingxia ^1,2 , YANG Meng ^1,2 ,  ZHANG Shu ¹

1. Department of Emergency Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
2. West China School of Medicine, Sichuan University, Chengdu, Sichuan 610041, P. R. China;

Corresponding?author：

ZHANG Shu, Email: zhangs@wchscu.cn

Keywords：

Bloodstream infection; novel biomarker; soluble triggering receptor expressed on myeloid cell-1; soluble form of the urokinase plasminogen activator receptor; presepsin; heparin-binding protein; microRNA; prognosis

DOI：

10.7507/1002-0179.202503028

Video：

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Bloodstream infections are featured by acute onset, rapid progression and high mortality. Early identification and accurate prognostic assessment are crucial for improving patient outcomes. This article reviews five novel biomarkers in assessing the severity and prognosis of patients with acute bloodstream infection, namely soluble triggering receptor expressed on myeloid cell-1, soluble form of the urokinase plasminogen activator receptor, presepsin, heparin-binding protein and microRNAs, all of which are positively correlated with the severity of patients’ condition, and some perform better than traditional biomarkers. However, they still have limitations such as inadequate specificity or sensitivity and lack of large-scale verification. In the future, it is necessary to integrate molecular detection and artificial intelligence to optimize application strategies and provide personalized diagnosis and treatment.

Citation： GUO Mingxia, YANG Meng, ZHANG Shu. Application of novel markers in assessing the severity and prognosis of patients with acute bloodstream infection. West China Medical Journal, 2025, 40(11): 1865-1868. doi: 10.7507/1002-0179.202503028 Copy

1.	劉隆蘋, 謝超, 吳軍民, 等. IL-6、PCT、CRP、BNP 水平評估重癥感染患者血流感染的價值. 中國醫學創新, 2025, 22(6): 140-144.
2.	劉偉, 曹獻芹, 宋媛媛, 等. 血清 PCT、CRP 水平及 WBC 檢測對急診血流感染的鑒別診斷價值. 臨床醫學研究與實踐, 2021, 6(12): 121-123.
3.	劉妍, 于小洪, 馬麗平, 等. 老年患者社區獲得性血流感染的急診預測指標. 北京醫學, 2019, 41(12): 1075-1078.
4.	Müller B, Schuetz P, Trampuz A. Circulating biomarkers as surrogates for bloodstream infections. Int J Antimicrob Agents, 2007, 30(Suppl 1): S16-S23.
5.	Choi MH, Kim D, Kim J, et al. Shift in risk factors for mortality by period of the bloodstream infection timeline. J Microbiol Immunol Infect, 2024, 57(1): 97-106.
6.	Zhang S, Zhang X, Yu W, et al. Infection biomarkers in assisting the judgement of blood stream infection and patient prognosis: a retrospective study incorporating principal components analysis. Ann Transl Med, 2020, 8(23): 1581.
7.	Henriquez-Camacho C, Losa J. Biomarkers for sepsis. Biomed Res Int, 2014, 2014: 547818.
8.	Goto M, Al-Hasan MN. Overall burden of bloodstream infection and nosocomial bloodstream infection in North America and Europe. Clin Microbiol Infect, 2013, 19(6): 501-509.
9.	Jiang J, Liu R, Yu X, et al. The neutrophil-lymphocyte count ratio as a diagnostic marker for bacteraemia: a systematic review and meta-analysis. Am J Emerg Med, 2019, 37(8): 1482-1489.
10.	Póvoa P, Coelho L, Dal-Pizzol F, et al. How to use biomarkers of infection or sepsis at the bedside: guide to clinicians. Intensive Care Med, 2023, 49(2): 142-153.
11.	Pierrakos C, Velissaris D, Bisdorff M, et al. Biomarkers of sepsis: time for a reappraisal. Crit Care, 2020, 24(1): 287.
12.	Sikora JP, Karawani J, Sobczak J. Neutrophils and the systemic inflammatory response syndrome (SIRS). Int J Mol Sci, 2023, 24(17): 13469.
13.	Behrens LM, van Egmond M, van den Berg TK. Neutrophils as immune effector cells in antibody therapy in cancer. Immunol Rev, 2023, 314(1): 280-301.
14.	Shao SL, Cong HY, Wang MY, et al. The diagnostic roles of neutrophil in bloodstream infections. Immunobiology, 2020, 225(1): 151858.
15.	Zhang H, Wang Y, Qu M, et al. Neutrophil, neutrophil extracellular traps and endothelial cell dysfunction in sepsis. Clin Transl Med, 2023, 13(1): e1170.
16.	Le Tulzo Y, Pangault C, Gacouin A, et al. Early circulating lymphocyte apoptosis in human septic shock is associated with poor outcome. Shock, 2002, 18(6): 487-494.
17.	Bellos I, Fitrou G, Daskalakis G, et al. Soluble TREM-1 as a predictive factor of neonatal sepsis: a meta-analysis. Inflamm Res, 2018, 67(7): 571-578.
18.	Park J, Yoon JH, Ki HK, et al. Performance of presepsin and procalcitonin predicting culture-proven bacterial infection and 28-day mortality: a cross sectional study. Front Med (Lausanne), 2022, 9: 954114.
19.	施佳, 林雅婷, 張瀟月, 等. 血清 sTREM-1、sTNFR-Ⅱ聯合 CF-6 對新生兒早發型敗血癥的診斷和預后評估價值研究. 現代生物醫學進展, 2024, 24(1): 54-59.
20.	Cao C, Gu J, Zhang J. Soluble triggering receptor expressed on myeloid cell-1 (sTREM-1): a potential biomarker for the diagnosis of infectious diseases. Front Med, 2017, 11(2): 169-177.
21.	Zhang L, Zhang X. Serum sTREM-1, PCT, CRP, Lac as biomarkers for death risk within 28 days in patients with severe sepsis. Open Life Sci, 2018, 13: 42-47.
22.	張麗娟, 張建平, 范宏艷, 等. 早期急診感染性休克患者血乳酸、可溶性髓系細胞觸發受體-1 變化分析. 中華醫院感染學雜志, 2022, 32(16): 2406-2410.
23.	Qin Q, Liang L, Xia Y. Diagnostic and prognostic predictive values of circulating sTREM-1 in sepsis: a meta-analysis. Infect Genet Evol, 2021, 96: 105074.
24.	Li Z, Wang H, Liu J, et al. Serum soluble triggering receptor expressed on myeloid cells-1 and procalcitonin can reflect sepsis severity and predict prognosis: a prospective cohort study. Mediators Inflamm, 2014, 2014: 641039.
25.	闞文穎. 血清 suPAR、BNP、CRP 水平檢測與 ICU 重癥血流感染患者預后相關性研究. 創傷與急危重病醫學, 2020, 8(2): 126-128.
26.	魏芳, 吳桂瓊, 孫建. ICU 血流感染患者血清 BNP、suPAR、MMP-9 水平及臨床意義. 中華醫院感染學雜志, 2021, 31(17): 2678-2682.
27.	龐秋菊, 任寶恒, 陳燦, 等. 血清降鈣素原、可溶性尿激酶型纖溶酶原激活物受體聯合病情嚴重程度評分對膿毒性休克患者預后的評估價值. 臨床內科雜志, 2024, 41(7): 469-473.
28.	Giamarellos-Bourboulis EJ, Norrby-Teglund A, Mylona V, et al. Risk assessment in sepsis: a new prognostication rule by APACHE II score and serum soluble urokinase plasminogen activator receptor. Crit Care, 2012, 16(4): R149.
29.	吳莎莎, 楊帥, 沈超, 等. 血清 suPAR、PBEF、VE-Cad 水平與膿毒癥所致 ARDS 患者病情、部分炎性反應指標及預后的關系. 國際檢驗醫學雜志, 2021, 42(10): 1189-1194.
30.	Adami ME, Kotsaki A, Antonakos N, et al. qSOFA combined with suPAR for early risk detection and guidance of antibiotic treatment in the emergency department: a randomized controlled trial. Crit Care, 2024, 28(1): 42.
31.	Ni W, Han Y, Zhao J, et al. Serum soluble urokinase-type plasminogen activator receptor as a biological marker of bacterial infection in adults: a systematic review and meta-analysis. Sci Rep, 2016, 6: 39481.
32.	郭宇, 劉穎, 梁玉龍, 等. 新型生物標志物 Presepsin 在臨床感染性疾病診療中的應用與探討. 臨床檢驗雜志, 2022, 40(2): 132-137.
33.	蘆錚, 吳金海, 賈赟, 等. 血清 HB-EGF、MR-proADM、Presepsin 水平與膿毒癥患者病情及預后相關性分析. 交通醫學, 2025, 39(3): 275-277, 281.
34.	Yu H, Qi ZJ, Hang CC, et al. Evaluating the value of dynamic procalcitonin and presepsin measurements for patients with severe sepsis. Am J Emerg Med, 2017, 35(6): 835-841.
35.	侯宇婕, 張釩, 唐振媚, 等. 2 型糖尿病合并血流感染炎性因子及 HBP 水平. 中華醫院感染學雜志, 2020, 30(22): 3414-3418.
36.	Taha AM, Najah Q, Omar MM, et al. Diagnostic and prognostic value of heparin-binding protein in sepsis: a systematic review and meta-analysis. Medicine (Baltimore), 2024, 103(25): e38525.
37.	張雷, 阮培森, 陳赫赫. 膿毒癥新型生物標志物的研究進展. 浙江臨床醫學, 2023, 25(12): 1889-1892.
38.	Tang J, Yuan H, Wu YL, et al. The predictive value of heparin-binding protein and D-dimer in patients with sepsis. Int J Gen Med, 2023, 16: 2295-2303.
39.	Benz F, Roy S, Trautwein C, et al. Circulating microRNAs as biomarkers for sepsis. Int J Mol Sci, 2016, 17(1): 78.
40.	Wang ZH, Liang YB, Tang H, et al. Dexamethasone down-regulates the expression of microRNA-155 in the livers of septic mice. PLoS One, 2013, 8(11): e80547.
41.	Yao L, Liu Z, Zhu J, et al. Clinical evaluation of circulating microRNA-25 level change in sepsis and its potential relationship with oxidative stress. Int J Clin Exp Pathol, 2015, 8(7): 7675-7684.
42.	Casagranda I, Vendramin C, Callegari T, et al. Usefulness of suPAR in the risk stratification of patients with sepsis admitted to the emergency department. Intern Emerg Med, 2015, 10(6): 725-730.
43.	Zhou T, Ren Z, Ma Y, et al. Early identification of bloodstream infection in hemodialysis patients by machine learning. Heliyon, 2023, 9(7): e18263.

1. 劉隆蘋, 謝超, 吳軍民, 等. IL-6、PCT、CRP、BNP 水平評估重癥感染患者血流感染的價值. 中國醫學創新, 2025, 22(6): 140-144.
2. 劉偉, 曹獻芹, 宋媛媛, 等. 血清 PCT、CRP 水平及 WBC 檢測對急診血流感染的鑒別診斷價值. 臨床醫學研究與實踐, 2021, 6(12): 121-123.
3. 劉妍, 于小洪, 馬麗平, 等. 老年患者社區獲得性血流感染的急診預測指標. 北京醫學, 2019, 41(12): 1075-1078.
4. Müller B, Schuetz P, Trampuz A. Circulating biomarkers as surrogates for bloodstream infections. Int J Antimicrob Agents, 2007, 30(Suppl 1): S16-S23.
5. Choi MH, Kim D, Kim J, et al. Shift in risk factors for mortality by period of the bloodstream infection timeline. J Microbiol Immunol Infect, 2024, 57(1): 97-106.
6. Zhang S, Zhang X, Yu W, et al. Infection biomarkers in assisting the judgement of blood stream infection and patient prognosis: a retrospective study incorporating principal components analysis. Ann Transl Med, 2020, 8(23): 1581.
7. Henriquez-Camacho C, Losa J. Biomarkers for sepsis. Biomed Res Int, 2014, 2014: 547818.
8. Goto M, Al-Hasan MN. Overall burden of bloodstream infection and nosocomial bloodstream infection in North America and Europe. Clin Microbiol Infect, 2013, 19(6): 501-509.
9. Jiang J, Liu R, Yu X, et al. The neutrophil-lymphocyte count ratio as a diagnostic marker for bacteraemia: a systematic review and meta-analysis. Am J Emerg Med, 2019, 37(8): 1482-1489.
10. Póvoa P, Coelho L, Dal-Pizzol F, et al. How to use biomarkers of infection or sepsis at the bedside: guide to clinicians. Intensive Care Med, 2023, 49(2): 142-153.
11. Pierrakos C, Velissaris D, Bisdorff M, et al. Biomarkers of sepsis: time for a reappraisal. Crit Care, 2020, 24(1): 287.
12. Sikora JP, Karawani J, Sobczak J. Neutrophils and the systemic inflammatory response syndrome (SIRS). Int J Mol Sci, 2023, 24(17): 13469.
13. Behrens LM, van Egmond M, van den Berg TK. Neutrophils as immune effector cells in antibody therapy in cancer. Immunol Rev, 2023, 314(1): 280-301.
14. Shao SL, Cong HY, Wang MY, et al. The diagnostic roles of neutrophil in bloodstream infections. Immunobiology, 2020, 225(1): 151858.
15. Zhang H, Wang Y, Qu M, et al. Neutrophil, neutrophil extracellular traps and endothelial cell dysfunction in sepsis. Clin Transl Med, 2023, 13(1): e1170.
16. Le Tulzo Y, Pangault C, Gacouin A, et al. Early circulating lymphocyte apoptosis in human septic shock is associated with poor outcome. Shock, 2002, 18(6): 487-494.
17. Bellos I, Fitrou G, Daskalakis G, et al. Soluble TREM-1 as a predictive factor of neonatal sepsis: a meta-analysis. Inflamm Res, 2018, 67(7): 571-578.
18. Park J, Yoon JH, Ki HK, et al. Performance of presepsin and procalcitonin predicting culture-proven bacterial infection and 28-day mortality: a cross sectional study. Front Med (Lausanne), 2022, 9: 954114.
19. 施佳, 林雅婷, 張瀟月, 等. 血清 sTREM-1、sTNFR-Ⅱ聯合 CF-6 對新生兒早發型敗血癥的診斷和預后評估價值研究. 現代生物醫學進展, 2024, 24(1): 54-59.
20. Cao C, Gu J, Zhang J. Soluble triggering receptor expressed on myeloid cell-1 (sTREM-1): a potential biomarker for the diagnosis of infectious diseases. Front Med, 2017, 11(2): 169-177.
21. Zhang L, Zhang X. Serum sTREM-1, PCT, CRP, Lac as biomarkers for death risk within 28 days in patients with severe sepsis. Open Life Sci, 2018, 13: 42-47.
22. 張麗娟, 張建平, 范宏艷, 等. 早期急診感染性休克患者血乳酸、可溶性髓系細胞觸發受體-1 變化分析. 中華醫院感染學雜志, 2022, 32(16): 2406-2410.
23. Qin Q, Liang L, Xia Y. Diagnostic and prognostic predictive values of circulating sTREM-1 in sepsis: a meta-analysis. Infect Genet Evol, 2021, 96: 105074.
24. Li Z, Wang H, Liu J, et al. Serum soluble triggering receptor expressed on myeloid cells-1 and procalcitonin can reflect sepsis severity and predict prognosis: a prospective cohort study. Mediators Inflamm, 2014, 2014: 641039.
25. 闞文穎. 血清 suPAR、BNP、CRP 水平檢測與 ICU 重癥血流感染患者預后相關性研究. 創傷與急危重病醫學, 2020, 8(2): 126-128.
26. 魏芳, 吳桂瓊, 孫建. ICU 血流感染患者血清 BNP、suPAR、MMP-9 水平及臨床意義. 中華醫院感染學雜志, 2021, 31(17): 2678-2682.
27. 龐秋菊, 任寶恒, 陳燦, 等. 血清降鈣素原、可溶性尿激酶型纖溶酶原激活物受體聯合病情嚴重程度評分對膿毒性休克患者預后的評估價值. 臨床內科雜志, 2024, 41(7): 469-473.
28. Giamarellos-Bourboulis EJ, Norrby-Teglund A, Mylona V, et al. Risk assessment in sepsis: a new prognostication rule by APACHE II score and serum soluble urokinase plasminogen activator receptor. Crit Care, 2012, 16(4): R149.
29. 吳莎莎, 楊帥, 沈超, 等. 血清 suPAR、PBEF、VE-Cad 水平與膿毒癥所致 ARDS 患者病情、部分炎性反應指標及預后的關系. 國際檢驗醫學雜志, 2021, 42(10): 1189-1194.
30. Adami ME, Kotsaki A, Antonakos N, et al. qSOFA combined with suPAR for early risk detection and guidance of antibiotic treatment in the emergency department: a randomized controlled trial. Crit Care, 2024, 28(1): 42.
31. Ni W, Han Y, Zhao J, et al. Serum soluble urokinase-type plasminogen activator receptor as a biological marker of bacterial infection in adults: a systematic review and meta-analysis. Sci Rep, 2016, 6: 39481.
32. 郭宇, 劉穎, 梁玉龍, 等. 新型生物標志物 Presepsin 在臨床感染性疾病診療中的應用與探討. 臨床檢驗雜志, 2022, 40(2): 132-137.
33. 蘆錚, 吳金海, 賈赟, 等. 血清 HB-EGF、MR-proADM、Presepsin 水平與膿毒癥患者病情及預后相關性分析. 交通醫學, 2025, 39(3): 275-277, 281.
34. Yu H, Qi ZJ, Hang CC, et al. Evaluating the value of dynamic procalcitonin and presepsin measurements for patients with severe sepsis. Am J Emerg Med, 2017, 35(6): 835-841.
35. 侯宇婕, 張釩, 唐振媚, 等. 2 型糖尿病合并血流感染炎性因子及 HBP 水平. 中華醫院感染學雜志, 2020, 30(22): 3414-3418.
36. Taha AM, Najah Q, Omar MM, et al. Diagnostic and prognostic value of heparin-binding protein in sepsis: a systematic review and meta-analysis. Medicine (Baltimore), 2024, 103(25): e38525.
37. 張雷, 阮培森, 陳赫赫. 膿毒癥新型生物標志物的研究進展. 浙江臨床醫學, 2023, 25(12): 1889-1892.
38. Tang J, Yuan H, Wu YL, et al. The predictive value of heparin-binding protein and D-dimer in patients with sepsis. Int J Gen Med, 2023, 16: 2295-2303.
39. Benz F, Roy S, Trautwein C, et al. Circulating microRNAs as biomarkers for sepsis. Int J Mol Sci, 2016, 17(1): 78.
40. Wang ZH, Liang YB, Tang H, et al. Dexamethasone down-regulates the expression of microRNA-155 in the livers of septic mice. PLoS One, 2013, 8(11): e80547.
41. Yao L, Liu Z, Zhu J, et al. Clinical evaluation of circulating microRNA-25 level change in sepsis and its potential relationship with oxidative stress. Int J Clin Exp Pathol, 2015, 8(7): 7675-7684.
42. Casagranda I, Vendramin C, Callegari T, et al. Usefulness of suPAR in the risk stratification of patients with sepsis admitted to the emergency department. Intern Emerg Med, 2015, 10(6): 725-730.
43. Zhou T, Ren Z, Ma Y, et al. Early identification of bloodstream infection in hemodialysis patients by machine learning. Heliyon, 2023, 9(7): e18263.

West China Medical Journal

Application of novel markers in assessing the severity and prognosis of patients with acute bloodstream infection

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