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Early warning of bloodstream infection in elderly patients with circulating microparticles

Abstract

Background

The difficulty of early diagnosis of bloodstream infection in the elderly patients leads to high mortality. Therefore, it is essential to determine some new methods of early warning of bloodstream infection in the elderly patients for timely adjustment of treatment and improvement of prognosis.

Methods

Patients aged over 65 years with suspected bloodstream infections were included and divided into bloodstream infection (BSI) and non-bloodstream infection (non-BSI) groups based on blood culture results. The morphology of microparticles (MPs) was observed by using transmission electron microscopy, and the number of MPs was dynamically monitored by flow cytometry.

Results

A total of 140 patients were included in the study: 54 in the BSI group and 86 in the non-BSI group. Total MPs (T-MPs) ≥ 6000 events/µL (OR, 7.693; 95% CI 2.944–20.103, P < 0.0001), neutrophil-derived MPs (NMPs) ≥ 500 events/µL (OR, 12.049; 95% CI 3.574–40.623, P < 0.0001), and monocyte counts ≤ 0.4 × 109/L (OR, 3.637; 95% CI 1.415–9.348, P = 0.007) within 6 h of fever were independently associated with bloodstream infection in the elderly patients. We also developed an early warning model for bloodstream infection in the elderly patients with an area under the curve of 0.884 (95% CI 0.826–0.942, P < 0.0001), sensitivity of 86.8%, specificity of 76.5%, positive predictive value of 70.8%, and negative predictive value of 89.8%.

Conclusion

The early warning model of bloodstream infection based on circulating T-MPs, NMPs, and monocyte counts within 6 h of fever in the elderly patients was helpful in early detection of bloodstream infection and therefore promptly adjustment of treatment plan.

Introduction

As a critical illness, the morbidity and mortality of bloodstream infection increase with age. Studies have reported a mortality rate of 16%–49% for bloodstream infections in individuals aged 65–75 years and 21%–56% for those aged ≥ 75 years [1,2,3].The diagnosis of bloodstream infections relies on blood cultures, however, the long waiting time for blood cultures may delay the diagnosis. Non-culture-based diagnostic techniques, such as high-throughput sequencing, mass spectrometry, and real-time polymerase chain reaction techniques, are cumbersome, time-consuming, expensive, and difficult to promote [4,5,6]. C-reactive protein (CRP) and procalcitonin (PCT) are the most commonly used infection-related indicators in clinical practice, however too many influencing factors and poor sensitivity in the elderly population, limit their early diagnostic value [7, 8]. Thus, looking for certain suitable biomarkers for early warning of bloodstream infections in the elderly patients may reduce the mortality and morbidity of this critical condition.

Micropaticles (MPs) are submicron vesicles between 0.1 and 1 µm in diameter formed by cell membrane outgrowth and shedding upon activation or apoptosis, expressing parent cell-derived antigens [9]. MPs have a high expression of phosphatidylserine (PS) on their surface and carry proteins, lipids and nucleic acids [DNA, messenger RNA (mRNA), microRNA (miRNA)] from the mother cells [9]. MPs are derived from various types of circulating cells and involved in promoting coagulation, cell adhesion, chemotaxis, and release of various inflammatory factors and have been reported to contribute to the early diagnosis of sepsis-induced disseminated intravascular coagulation [10, 11]. However, to our knowledge, there are insufficient studies related to MPs and bloodstream infections in the elderly population, so this study was designed to explore the early warning role of circulating MPs on bloodstream infections in the elderly population.

Materials and methods

Patients

Patients aged over 65 years with suspected bloodstream infections from October 2018 to October 2020 at the Second Medical Center, Chinese PLA General Hospital, were included as the study group. The control group included elderly patients admitted for routine physical examinations during the same period. They presented with chronic diseases but were free of infectious disease. The inclusion criteria were: body temperature ≥ 38 °C with or without chills and (i) shock or decreased blood pressure (systolic blood pressure decreased by 40 mmHg or more than usual) or (ii) presence of central venous catheter or (iii) elevated infection index (leukocyte counts ≥ 15,000/µL or ≤ 4000/µL). The exclusion criteria were: end-stage disease with expected survival < 7 days; rheumatic autoimmune disease; malignancy (including hematologic tumors); abnormal liver function (Child–Pugh grade ≥ C); renal dysfunction (chronic kidney disease ≥ stage 3b); cardiac insufficiency (New York Heart Association ≥ grade 3); use of glucocorticoids or blood transfusion therapy 3 days before enrollment or during treatment; and failure to complete blood collection within 6 h and on the 2nd day of fever. According to the blood culture results, the patients were divided into non-bloodstream infection (non-BSI) group and bloodstream infection (BSI) group.

Data collection

The basic information of the study subjects was collected, including sex, age, underlying disease (coronary heart disease, hypertension, diabetes, chronic obstructive pulmonary disease, hyperlipidemia, atrial fibrillation, chronic renal insufficiency), presence of indwelling lines (deep vein, urinary catheter, gastric tube), use of antibiotics within 30 days, infection status (site of infection, causative organism), and prognosis.

Blood sampling

In the study group, leukocyte counts, neutrophil percentage, monocyte counts, CRP, and PCT levels were measured within 6 h, on days 2 and 14 of fever (except in patients who died), and 3 mL of venous blood was collected from the elbow of subjects in the study and control groups (on the day of enrollment) using a sodium citrate anticoagulation tube (3.2%, 0.109 M). To avoid the effect of punctured vessels on the MPs, blood samples for testing MPs were obtained at last.

MP isolation by differential centrifugation was performed: 3 mL of whole blood was centrifuged (4 °C, 2000g) for 10 min, and 1000 µL of supernatant was obtained to collect platelet-poor plasma (PPP); then, PPP was ultracentrifuged (4 °C, 13,000g) for 3 min, and 400 µL of supernatant was obtained to collect platelet-free plasma (PFP), which was stored in the refrigerator at − 80 °C.

Microparticle analysis

Observation of MPs morphology by transmission electron microscopy

MPs (20 µl) from patients were placed on copper mesh and incubated for 5 min. We removed the remaining liquid with filter paper, and added 20 µl phosphotungstic acid. After standing for 10 min, any remaining liquid was removed with filter paper, and the sample was observed by transmission electron microscopy.

Detection of MPs number by flow cytometry

PFP was dissolved at room temperature and then ultracentrifuged (4 °C, 21,000g) for 60 min, and 100 µL of the bottom fraction was obtained as MPs. The number of MPs was detected by FACSCanto™ II flow cytometer (BD Bioscience, San Jose, CA, USA). Annexin V was used to identify the PS expressed on the surface of the MPs. Annexin V + MPs is the total number of MPs, CD11b + /Annexin V + represents leukocyte-derived MPs (LMPs), CD66b + /Annexin V + represents neutrophil-derived MPs (NMPs), CD14 + /Annexin V + represents monocyte-derived MPs (MMPs), and CD105 + /Annexin V + represents endotheliocyte-derived MPs (EMPs). The immunofluorescent monoclonal antibodies used were as follows (BioLegend, San Diego, CA, USA): Annexin V labeled by PE, CD11b labeled by APC-Cy7, CD66b labeled by FITC, CD14 labeled by APC-Cy7, and CD105 labeled by Percp-cy5.5. Moreover, 25 µL of MPs,1 µL Annexin V and 100 µL Annexin V binding buffer were added into two Eppendorf tubes A and B, and incubated for 20 min at room temperature, avoiding light. Then, 1 µL CD11b-APC-Cy7 and 1 µL CD66b-FITC were added into tube A, and 1 µL CD14-APC-Cy7 and 1 µL CD105-Percp-cy5.5 were added into tube B and incubated for 20 min at room temperature, avoiding light. Then, both tubes A and B were washed with phosphate-buffered saline (PBS), transferred to BD absolute counting tubes (BD Bioscience, San Jose, CA, USA), and tested on the machine. Furthermore, 0.2 µm, 0.5 µm, 1 µm, and 2 µm standard microspheres (Invitrogen, Carlsbad, CA, USA) were used to set the gate and determine the location of 0.1–1.0 µm MPs (Additional file 1: Fig. S1). To avoid the noise caused by dust and crystallization, the buffer and PBS were filtered through a 0.22-µm filter. MPs were counted in events/µL.

Statistical analysis

IBM SPSS Statistics 23.0 (SPSS, Chicago, IL, USA) was used for statistical analyses. A Kolmogorov–Smirnov test was used to test the normality of the continuous variables. Quantitative data with normal distributions were expressed as the means and standard deviations and were analyzed by t-tests. Quantitative data with non-normal distributions were presented as the medians and interquartile ranges (IQRs) and were assessed with the Mann–Whitney U test. The Chi-square test or Fisher’s exact probability test was used to compare count data. Univariate analysis and multivariate logistic regression analysis (Forward: LR) were used to determine the independent influencing factors and an early warning model of bloodstream infection in elderly patients was established. The sensitivity and specificity of the early warning model were tested by receiver operating characteristic (ROC) curve. A P value less than 0.05 was considered statistically significant.

Result

MPs morphology

MPs had spherical structures with diameters ranging from 100 to 1000 nm, heterogeneity in size, and typical lipid bilayer structure (Additional file 1: Fig. S2).

Basic clinical characteristics of the included patients

A total of 140 patients were included in this study: 86 patients in the non-BSI group and 54 patients in the BSI group (Additional file 1: Fig. S3). The rates of deep venous placement, urinary catheter retention, and antibiotic use within 30 days were significantly higher in the BSI group than those in the non-BSI group (92.6% vs 77.9%, P = 0.022; 48.1% vs 30.2%, P = 0.037; 79.6% vs 64%, P = 0.049, Additional file 2: Table S1).

In the BSI group, the infecting pathogens were mainly Escherichia coli in 17 (31.5%) cases, Klebsiella pneumoniae in 14 (25.9%) cases, Pseudomonas aeruginosa in 8 (14.8%) cases, and Streptococcus haemolyticus in 6 (11.1%) cases. In the non-BSI group, 60 (69.8%) cases were pulmonary infections, 15 (17.4%) cases were urinary tract infections, and five (5.8%) cases were biliary tract infections (Additional file 2: Table S1). The infecting pathogens were mainly Klebsiella pneumoniae in 21 (24.4%) cases, Pseudomonas aeruginosa in 20 (23.3%) cases, and Escherichia coli in 12 (14.0%) cases (Additional file 2: Table S2).

Comparison and trends of inflammatory indexes in the two groups

The monocyte counts and percentage within 6 h of fever in the BSI group were significantly lower than those in the non-BSI group, and the PCT levels within 6 h and at the second day of fever in the BSI group were significantly higher than those in the non-BSI group (P < 0.05, Table 1).

Table 1 Inflammatory markers in non-BSI group and BSI group

Neutrophil percentage peaked within 6 h of fever in both groups and was significantly higher in the BSI group within 6 h of fever than that on the next day (P = 0.049). In the BSI group, monocyte counts peaked on day 2 and were significantly lower within 6 h of fever than those on day 2 (P = 0.029) and showed no difference between day 2 and 14 (P = 0.471). In the non-BSI group, the monocyte counts showed no difference within 6 h of fever and on day 2 (P = 0.188) and were significantly higher on day 2 than those on day 14 (P = 0.010). CRP and PCT levels peaked on day 2 of fever in both groups and were significantly higher than those within 6 h of fever (P < 0.05). All inflammatory indexes (except monocyte counts in BSI group) significantly decreased on day 14.

Comparison and trends of MPs in the two groups

Within 6 h of fever and on day 2, total MP (T-MP), LMP, and NMP levels were significantly higher in the BSI group than those in the non-BSI group, and there was no difference in MMP and EMP levels between the two groups (Table 2). On day 14, NMP levels were significantly higher in the BSI group than those in the non-BSI group (P = 0.016, Table 2, Fig. 1, Additional file 1: Fig. S4).

Table 2 Microparticles in non-BSI group and BSI group
Fig. 1
figure 1

Dynamic monitoring of MPs. T-MPs, LMPs, NMPs, MMPs, and EMPs peaked within 6 h of fever in both groups and were significantly higher than those on day 2. All types of MPs decreased gradually with time. A Total MPs, B leukocyte-derived MPs, C neutrophil-derived MPs, D monocyte-derived MPs, and E endotheliocyte-derived MPs. BSI: bloodstream infection; non-BSI: non-bloodstream infection; MPs: microparticles; T-MPs: total microparticles; LMPs: leukocyte-derived microparticles; NMPs: neutrophil-derived microparticles; MMPs: monocyte-derived microparticles; EMPs: endotheliocyte-derived microparticles

T-MP, LMP, NMP, MMP, and EMP levels peaked within 6 h of fever in both groups and gradually decreased with time (Table 2, Fig. 1).

Comparison of MPs in the study group on day 14 with the control group

After excluding patients who died within 14 days (n = 8), T-MPs were significantly higher in the study group on day 14 than those in the control group, and LMPs and NMPs were significantly higher in the BSI group than those in the control group, while there was no significant difference in all types of MPs between the non-BSI group and control group (Additional file 2: Table S3). There was no significant difference in clinical characteristics between study group and control group (Additional file 2: Table S3).

Establishment of bloodstream infection early warning model in the elderly population

Factors that differed within 6 h of fever (P < 0.1) in the univariate analysis were included in the multivariate logistic regression analysis (forward: LR), and T-MPs ≥ 6000 events/µL (OR, 7.693; 95% CI 2.944–20.103, P < 0.0001), NMPs ≥ 500 events/µL (OR, 12.049; 95% CI 3.574–40.623, P < 0.0001), and monocyte counts ≤ 0.4 × 109/L (OR, 3.637; 95% CI 1.415–9.348, P = 0.007) were independently associated with bloodstream infection in the elderly population (Table 3).

Table 3 Multivariate logistic regression analysis for early warning of bloodstream infection in the elderly

Based on the results of multivariate regression analysis, an early warning model of bloodstream infection in the elderly population was established: Logit(P) = − 3.977 + 2.040 × T-MPs1(≥ 6000 events/µL = 1, < 6000 events/µL = 0) + 2.489 × NMPs1(≥ 500 events/µL = 1, < 500 events/µL = 0) + 1.291 × monocyte counts1 (≤ 0.4 × 109/L = 1, > 0.4 × 109/L = 0).

It was further transformed to obtain: Y = 1.580 × T-MPs1(≥ 6000 events/µL = 1, < 6000 events/µL = 0) + 1.928 × NMPs1(≥ 500 events/µL = 1, < 500 events/µL = 0) + monocyte counts1(≤ 0.4 × 109/L = 1, > 0.4 × 109/L = 0).

Receiver operating characteristic (ROC) curve to evaluate the predictive value of early warning model for predicting bloodstream infection in the elderly population

The ROC curve showed that the area under the curve (AUC) of the early warning model for predicting bloodstream infection in the elderly population was 0.884 (95% CI 0.826–0.942, P < 0.0001), the optimal cutoff value of Y was 3.5, the sensitivity was 86.8%, the specificity was 76.5%, the positive predictive value was 70.8%, and the negative predictive value was 89.8% (Table 4, Fig. 2).

Table 4 Predictive performance of early warning model and other factors for predicting bloodstream infection in the elderly population
Fig. 2
figure 2

Receiver operating characteristic (ROC) curve to evaluate the predictive value of early warning model and other factors for predicting bloodstream infection in the elderly population. Area under the curve of warning model was 0.884 (95%CI 0.826–0.942, P < 0.0001). PCT: procalcitonin; T-MPs: total microparticles; LMPs: leukocyte-derived microparticles; NMPs: neutrophil-derived microparticles; 1: within 6 h; 2: day 2

Discussion

MPs exert pro-inflammatory, procoagulant, and thrombogenic effects by stimulating receptors on the surface of target cells or transferring substances, such as proteins, lipids, mRNAs, or microRNAs, that they carry to target cells [12]. MPs have been shown to be associated with infection [11, 13, 14], and we also found that MPs of all cellular origins were significantly increased within 6 h of infection in elderly patients and gradually decreased with treatment and improvement of infection, suggesting that MPs are associated with the occurrence and prognosis of infection. More importantly, we found that T-MPs and NMPs combined with monocyte counts within 6 h of fever in elderly patients could provide early warning of bloodstream infection, which could help adjust treatment early and reduce mortality.

We included elderly patients who presented with high fever with or without chills during hospitalization, all of whom were suspected to have bloodstream infection from the clinical presentation, and 38.6% (54/140) of the patients were finally diagnosed in the subsequent observation. Although the disease severity at enrollment was similar to that of patients with non-bloodstream infections, approximately one-third of these patients died within 30 days of infection. A series of studies have indicated that bloodstream infections can cause septic shock, leading to multiorgan dysfunction and significantly higher mortality [15, 16], as does delayed antibiotic administration [17]. Therefore, early diagnosis and treatment are key to improvement of prognosis of bloodstream infections [18, 19]. It has been reported that PCT level rapidly increases in the early stages of infection (within 6 h) and can indicate bloodstream infection [20]. However, in the elderly population, we found that PCT can indicate bloodstream infection on day 2 of fever (Table 4), when the optimal time for treatment of bloodstream infection has been missed. A series of studies also suggest that PCT has extremely limited value in early warning of bloodstream infection in elderly patients [7, 8]. Therefore, rapid and effective diagnostic markers are still lacking.

In the present study, circulating T-MPs, and NMPs within 6 h of fever provided early warning of bloodstream infection, which was able to identify bloodstream infection significantly earlier than PCT [20], although there was no significant difference in circulating leukocyte and neutrophil counts between the two groups at this time. Nieuwland et al. [21] have also found that early circulating platelet-derived MP (PMP) and NMP levels in patients with septicemia caused by Streptococcus meningitidis were significantly increased compared with health donors. Timar et al. [13] found that, in patients with Staphylococcus aureus bacteremia, circulating NMP levels were significantly increased at 24 h of fever compared with health volunteers. However, these above-mentioned studies did not compare the early warning effect of MPs and other inflammatory markers and did not dynamically monitor the changes in MPs. When we dynamically monitored circulating MPs, we found that T-MP, LMP, and NMP levels were still higher in the BSI group than those in the non-BSI group on day 2 of fever, and levels of all types of MPs decreased significantly on day 14 of fever, but NMP levels were still significantly higher in the BSI group than those in the non-BSI group. This suggests that, during bloodstream infection, pathogenic microorganisms may rapidly induce the release of MPs from circulating cells through direct stimulation or their by-products, and this effect may persist until the late stages of infection. In fact, we compared the MPs in patients who were survived and died within 30 days. We found that the level of various MPs within 6 h of fever in the death group was significantly higher than those in the non-death group. However on day 2, the level of MPs in both groups decreased significantly, and there was no difference between the two groups. On day 14, the level of MPs in the death group was significantly higher than that in the non-death group again, suggesting that the level of MPs might predict the prognosis. In a study by Delabranche et al. [11], LMP levels were significantly elevated on the day of admission in patients with septic shock and significantly decreased as their condition improved. O'Dea et al. [14] found that, in patients with massive burns with infection, LMP and NMP levels were significantly elevated during the phase of systemic inflammatory syndrome and significantly decreased after administration of anti-infection and other treatments. These studies suggest that MPs are associated with the occurrence and regression of infection.

Moreover, we found that circulating monocyte counts and monocyte percentage within 6 h of fever in the BSI group were significantly lower than those in the non-BSI group, which is an interesting phenomenon. As precursor cells of macrophages, monocytes are capable of cytokine production, pathogen clearance, and antigen presentation [22, 23] and may be rapidly activated to eliminate pathogenic bacteria in primary bloodstream infections, but the bloodstream infections in this study were mostly secondary, and monocytes may have been recruited at the foci of primary infection, and neutrophil levels were more rapidly elevated in bloodstream infections, so the number of monocytes was relatively low. Actually after adjusting the number of MPs to their respective parent cells, We found MMPs/Monocyte were significantly higher in the BSI group than those in the non-BSI group within 6 h of fever, although Monocyte counts were lower in the BSI group at this time. This suggests that monocytes are activated to produce more MMPs within 6 h of fever during bloodstream infection.

By establishing an early warning model for bloodstream infections in the elderly population based on the results of multivariate analysis, we can diagnose 86.8% of bloodstream infections quickly and accurately, so as to guide clinicians to effectively fight infection and improve patient prognosis. In addition, based on this model, when a subject is tested negative, the correct rate of excluding bloodstream infection is 89.8%, which can avoid abuse of broad-spectrum antibiotics that induce bacterial resistance and promote the rational use of antibiotics.

There are some drawbacks in this study. First, the number of cases of Gram-positive bacterial and fungal bloodstream infections was small, therefore, no correlation could be drawn between etiology and MP production. Second, this is a single-center study with a small sample size. Third, platelet-derived MPs (PMPs) represent the majority of circulating total MPs, however, in the pre-experiment, we found that PMPs (represented by CD41 + /Annexin V +) were not closely related to infection, on the other hand some studies showed that PMPs were more closely related to thrombosis [24], angiogenesis [25], and tumor progression [26, 27], therefore, we did not monitor PMPs.

Conclusion

Early diagnosis and treatment of bloodstream infections can improve patient prognosis and reduce the financial burden on patients and hospitals. We found for the first time that circulating T-MPs and NMPs within 6 h of fever can independently provide early warning of bloodstream infection in the elderly population, and combined with monocyte counts within 6 h of fever, an early warning model of bloodstream infection was established. Moreover, dynamic monitoring of circulating MPs can help determine the severity of infection and prognosis. This provides a new method for early identification of bloodstream infections and dynamic monitoring of infection regression. Whether MPs have the same predictive value for bloodstream infections in young adults deserves further exploration.

Availability of data and materials

The data used and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Mehl A, Åsvold BO, Lydersen S, et al. Burden of bloodstream infection in an area of Mid-Norway 2002–2013: a prospective population-based observational study. BMC Infect Dis. 2017;17(1):205.

    Article  Google Scholar 

  2. 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):501–9.

    Article  CAS  Google Scholar 

  3. Muñoz-Gamito G, Calbo-Sebastián E, Riera-García M, et al. Bloodstream infection in the up to 80 year-old-patients. Rev Clin Esp. 2012;212(6):273–80.

    Article  Google Scholar 

  4. Zhang L, Rickard CM. Non-culture based diagnostics for intravascular catheter related bloodstream infections. Expert Rev Mol Diagn. 2017;17(2):181–8.

    Article  CAS  Google Scholar 

  5. Kuusela P, Saraswat M, Joenväärä S, et al. Changes in plasma protein levels as an early indication of a bloodstream infection. PLoS ONE. 2017;12(2):e0172987.

    Article  Google Scholar 

  6. Grumaz S, Stevens P, Grumaz C, et al. Next-generation sequencing diagnostics of bacteremia in septic patients. Genome Med. 2016;8(1):73.

    Article  Google Scholar 

  7. Nouvenne A, Ticinesi A, Folesani G, et al. The association of serum procalcitonin and high-sensitivity C-reactive protein with pneumonia in elderly multimorbid patients with respiratory symptoms: retrospective cohort study. BMC Geriatr. 2016;16:16.

    Article  Google Scholar 

  8. Chenevier-Gobeaux C, Trabattoni E, Elfassy Y, et al. Decisional procalcitonin thresholds are not adapted to elderly patients admitted to the emergency room. Biomarkers. 2012;17(5):477–81.

    Article  CAS  Google Scholar 

  9. Todorova D, Simoncini S, Lacroix R, et al. Extracellular vesicles in angiogenesis. Circ Res. 2017;120(10):1658–73.

    Article  CAS  Google Scholar 

  10. Delabranche X, Boisramé-Helms J, Asfar P, et al. Microparticles are new biomarkers of septic shock-induced disseminated intravascular coagulopathy. Intensive Care Med. 2013;39(10):1695–703.

    Article  CAS  Google Scholar 

  11. Delabranche X, Quenot JP, Lavigne T, et al. On behalf to the Clinical Research in Intensive Care and Sepsis Network. Early detection of disseminated intravascular coagulation during septic shock: a multicenter prospective study. Crit Care Med. 2016;44(10):e930–9.

    Article  CAS  Google Scholar 

  12. Hargett LA, Bauer NN. On the origin of microparticles: From “platelet dust” to mediators of intercellular communication. Pulm Circ. 2013;3(2):329–40.

    Article  Google Scholar 

  13. Timár CI, Lorincz AM, Csépányi-Kömi R, et al. Antibacterial effect of microvesicles released from human neutrophilic granulocytes. Blood. 2013;121(3):510–8.

    Article  Google Scholar 

  14. O’Dea KP, Porter JR, Tirlapur N, et al. Circulating microvesicles are elevated acutely following major burns injury and associated with clinical severity. PLoS ONE. 2016;11(12):e0167801.

    Article  Google Scholar 

  15. Shao SL, Cong HY, Wang MY, et al. The diagnostic roles of neutrophil in bloodstream infections. Immunobiology. 2020;225(1):151858.

    Article  CAS  Google Scholar 

  16. Adrie C, Garrouste-Orgeas M, Ibn Essaied W, et al. Attributable mortality of ICU-acquired bloodstream infections: Impact of the source, causative micro-organism, resistance profile and antimicrobial therapy. J Infect. 2017;74(2):131–41.

    Article  Google Scholar 

  17. Rhodes A, Evans LE, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock: 2016. Intensive Care Med. 2017;43(3):304–77.

    Article  Google Scholar 

  18. Sharma S, Kumar A. Antimicrobial management of sepsis and septic shock. Clin Chest Med. 2008;29(4):677–87.

    Article  Google Scholar 

  19. Kumar A, Roberts D, Wood KE, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med. 2006;34(6):1589–96.

    Article  Google Scholar 

  20. Hamade B, Huang DT. Procalcitonin: where are we now? Crit Care Clin. 2020;36(1):23–40.

    Article  Google Scholar 

  21. Nieuwland R, Berckmans RJ, McGregor S, et al. Cellular origin and procoagulant properties of microparticles in meningococcal sepsis. Blood. 2000;95(3):930–5.

    Article  CAS  Google Scholar 

  22. Canè S, Ugel S, Trovato R, et al. The endless saga of monocyte diversity. Front Immunol. 2019;10:1786.

    Article  Google Scholar 

  23. Gordon S, Taylor PR. Monocyte and macrophage heterogeneity. Nat Rev Immunol. 2005;5(12):953–64.

    Article  CAS  Google Scholar 

  24. Sinauridze EI, Kireev DA, Popenko NY, et al. Platelet microparticle membranes have 50- to 100-fold higher specific procoagulant activity than activated platelets. Thromb Haemost. 2007;97:425–34.

    Article  CAS  Google Scholar 

  25. Anene C, Graham AM, Boyne J, et al. Platelet microparticle delivered microRNA-Let-7a promotes the angiogenic switch. Biochim Biophys Acta Mol Basis Dis. 2018;1864(8):2633–43.

    Article  CAS  Google Scholar 

  26. Liang H, Yan X, Pan Y, et al. MicroRNA-223 delivered by platelet-derived microvesicles promotes lung cancer cell invasion via targeting tumor suppressor EPB41L3. Mol Cancer. 2015;14:58.

    Article  Google Scholar 

  27. Dinkla S, van Cranenbroek B, van der Heijden WA, et al. Platelet microparticles inhibit IL-17 production by regulatory T cells through P-selectin. Blood. 2016;27:1976–86.

    Article  Google Scholar 

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Acknowledgements

We thank Liwen Bianji, Edanz Editing China, for editing the English text of a draft of this manuscript.

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Authors

Contributions

LH contributed to the study design. LT, WJ (Jiang Wang), WJ (Jionghe Wu) and YY completed the isolation and detection of MPs. WJ (Jionghe Wu), WC and GY contributed to the collection of clinical data. LT and LH contributed to the data analysis. LT, WJ (Jiang Wang) and YY drafted the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Hongxia Li.

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The study protocol was approved by the Ethics Committee of Chinese People's Liberation Army (PLA) General Hospital (Ethical approval number: S2018-162–01), and written informed consent was obtained from all the participants or legal agents.

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Liu, T., Wang, J., Yuan, Y. et al. Early warning of bloodstream infection in elderly patients with circulating microparticles. Ann. Intensive Care 11, 110 (2021). https://doi.org/10.1186/s13613-021-00901-w

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