suPARnostic® by ViroGates

Patient triage

suPARcharging triage – Empowering clinical decisions

Triage in the Emergency Department

Initial triaging in the Emergency Department is one of the most critical steps in securing good patient outcomes. All around the world, clinicians have different methods to assess the risk stratification of patients in hospitals to categorise the urgency and need for care.

Triage involves a complex decision-making process carried out by specially trained nurses, technicians, and doctors based on vital signs, complaints, respiratory rate, oxygen saturation in blood, pulse, level of consciousness, blood pressure, age, and body temperature¹⁵.

Internationally, there is no consensus on the protocol used for the decision-making process. Therefore, specific regions have adopted several triage scales that guide healthcare professionals in their clinical decision-making.

Risk Scoring Systems for Triage

Quick Sequential Organ Failure Assessment (qSOFA)

The qSOFA score is a bedside assessment that can identify patients with suspected infection with a greater risk of having a poor outcome outside the intensive care unit (ICU). qSOFA uses three criteria, assigning one point for each of these criteria: low blood pressure (SBP≤100 mmHg), high respiratory rate (≥22 breaths per min), or altered mentation (Glasgow coma scale<15)⁴⁸.

Adaptive Process Triage (ADAPT)

This triage scoring system was developed in Sweden and is currently used in hospitals across Sweden and some in Denmark. The scoring system is based on a patient’s vital signs (ABCD-system) and a short questionnaire filled out for each complaint. The patients are divided into five priority groups: a) red (life-threatening), b) orange (seriously ill), c) yellow (ill), d) green (need of assessment), and e) blue (fast track)⁴⁹.

National Early Warning Score (NEWS)

This risk scoring system is based on the following parameters⁵⁰:

Respiratory rate (A)
Oxygen saturation (B)
Blood pressure (C)
Level of consciousness (D)
Temperature (E)

Simplified Acute Physiologic Score II (SAPS)

The scoring system is based on 12 physiologic variables, age, type of admission, and existing medical conditions experienced by the patient⁵¹.

Acute Physiology and Chronic Health Evaluation II (APACHE)

The scoring system is based on 12 physiologic criteria, age of the patient, and pre-existing condition of the patient⁵¹.

Systemic Inflammatory Response Syndrome (SIRS)

SIRS is defined by the following four criteria (Note: SIRS was replaced by the qSOFA in most hospitals, but still used in some countries)⁵²:

Increased heart rate (>90 beats/min)
Increased respiratory rate (>20 breaths/min)
Fever or hypothermia (>38 degrees or <36 degrees)
Increased White blood cell count >1,200/mm3

Limitations of conventional triage

Conventional triage processes carried out by visual and physical examinations have the following limitations:

A study found that the experience and training of individual nurses¹⁸ significantly influenced clinical triage efficiency. This results in high variability. Since conventional triages are not based on objective measurements, they can be influenced by personal bias and cultural differences.
Triage stratifications based on visible vital signs may ineffectively diagnose penetrating injuries and blunt trauma. More mistakes are likely to be made if the patient is unconscious and unable to communicate their symptoms.

Even widely used triage protocols like the Manchester Triage system were found to lead to several cases of sub and super-triage (under and over-classification of severity)¹⁹. Errors in categorisation were seen mostly in cases of patients presenting chest pain, resulting in long waiting times and ineffective treatment²⁰. A meta-analysis study in Great Britain found that triage decisions made in most hospitals across the country were based on insufficient evidence, resulting in repeated re-admissions and increased mortality¹⁵.

suPARcharging triage

The prognostic biomarker suPAR is a data-based scientific tool that empowers healthcare professionals to make quick and correct triage decisions across diseases. Implementing suPAR in triage, improves patient outcomes and reduces healthcare costs^44,54.

suPARnostic products are approved for all the major chemical analysers, fit existing hospital laboratory workflows and delivers results in less than 20 mins.

How to interpret suPAR results

suPAR level < 4 ng/mL

Supports patient discharge

suPAR level > 6 ng/mL

Supports patient hospitalisation

Soluble urokinase plasminogen activator (suPAR) may be of exceptionally high value in triage in the Emergency Department due to the high degree of unspecificity. A randomised controlled study showed that patients with measured suPAR levels and those with suPAR levels within the acceptable norms were more often discharged early. On average, patients evaluated with suPAR measures stayed 6,5 hours shorter in the hospital compared to the control group without suPAR measurement⁴⁴.

High plasma suPAR levels have been associated with increased severity and mortality in COVID-19^{56, 57}, HIV³⁵, sepsis²⁸, tuberculosis³⁶ , malaria³⁷, auto-immune diseases, Streptococcus pneumonia bacteremia, cancer³⁸, Alzheimer’s39, cardiovascular diseases⁴⁰, organ failure, neoplastic and pregnancy relation conditions, and type 2 diabetes mellitus⁴¹. High plasma concentrations of suPAR have also been associated with more extended hospital stays^{45, 46}.

The most commonly used inflammatory biomarker is C-reactive protein measured using high-sensitivity (hsCRP) assays. Elevated CRP levels have also been linked to cancer, CVD, and all-cause mortality⁴.

Interestingly, suPAR outperforms CRP in prognosing a range of diseases. Additionally, suPAR is linked to a biochemical pathway more closely associated with organ damage than CRP and is therefore poised to be more sensitive⁴⁰. Moreover, although troponins are the preferred biomarker in CVD prognosis, troponin levels rise only 2-6 ng/mL after a myocardial infarction (MI) event, and measurements at the 1st and 3rd hour are needed to determine MI. In contrast, a one-time test of suPAR is sufficient to rule out severe disease⁴⁴.

The Charlson Comorbidity score predicts the annual mortality of a patient with a range of co-morbid diseases such as heart disease, diabetes, HIV, cancer, etc. The inclusion of suPAR in the Charlson algorithm contributed to a better prediction of disease severity⁴².

Fever is a fairly common presenting symptom in hospitals. But, it can be easily misdiagnosed due to its highly variable etiology. In such cases, there is a need for an objective biomarker that would accurately reflect the severity and magnitude of the infection⁴³. suPAR is an ideal candidate due to its highly nonspecific nature. Low plasma levels can be used to identify patients with a good prognosis which enables early discharge. In Denmark, suPAR based stratification helped reduce ED overcrowding without any adverse effects on mortality or morbidity⁴⁴.

The use of suPAR for triage in hospitals has been researched. Some of the essential findings from clinical studies are listed below:

A study published in 2019 in the Scandinavian Journal of Trauma, Resuscitation, and Emergency Medicine studied the effectiveness of suPAR in grouping patients into high and low risk after they arrive in the Emergency Department (ED). The study’s findings revealed that measurement of suPAR in the triage process can allow more accurate identification of ED patients at risk⁵⁴.
Another study from 2019 published in the Journal of Family Medicine and Primary Care found that suPAR can be reliably used in the emergency department for triage and prognostic assessment of patients⁵⁵.

Documented by 700+ peer-reviewed publications

Here you can find a summary of the research done on suPAR within different disease areas.

suPAR publications

Disease areas

Triage FAQ

What is Triage

Triage is a process in which injured or sick individuals are grouped into various categories. The basis of the grouping relies on the patients’ need for immediate medical treatment or the degree of benefit a patient may derive from emergency medical attention⁴⁷.

Why Triage?

Patients visit the hospital for a variety of reasons ranging from minor injuries to life-threatening conditions. The American college of emergency physicians (ACEP) reports a rising trend in patients visiting the Emergency Department (ED). In 2007, the number even surpassed the size of the population of the U.S two-fold. However, hospital resources are limited. Therefore, not all patients can be treated simultaneously. Consequentially, the average waiting time before a patient receives medical care has increased by 25%¹.

Under these circumstances, it is imperative to accurately distinguish patients who need immediate attention from those who can wait. Using triage, patients are sorted based on vital signs, level of consciousness, pain, etc. The resulting scale can then be used to predict disease severity and risk of death².
There is a plethora of evidence from around the world establishing the beneficial effect of triage categorisation on clinical outcomes, safety, and waiting time^{3,4,5,6,7,8,9,10,11}. A shorter hospital stay consecutively lowers the risk of hospital-acquired infections, shortens immobilisation, and reduces cost. Triage has also helped reduce the number of patients leaving EDs without seeing a doctor¹².

The Triage Area

Triage can be carried out in pre-hospital settings, for example at the accident site, during transport, or at the emergency department. Most hospitals have a dedicated triage area where specially trained nurses, emergency responders, or doctors will follow specific protocols to categorise patients.

In most western countries, triage is carried out at two levels; Primary triage is performed based on visual symptoms at the first point of contact. Secondary triage is done by conducting a thorough examination. In some cases, a tertiary triage may also be carried out in the ICU¹³.

Triage is a complex decision-making process carried out by nurses, technicians, or doctors who have been specially trained for the purpose. In the UK and Scandinavia, nurse-led units (NLUs) are predominantly used to assess patients¹⁴. The decision can be made based on vital signs, chief complaint, respiratory rate, oxygen saturation in blood, pulse, level of consciousness, blood pressure, age, and body temperature¹⁵. However, internationally there is no consensus on the protocol used for the decision-making process. However, several triage scales have been adopted by specific regions that guide the health care technicians in their decision-making.

The Triage Code

Every triage system is unique. Some are used to decide waiting time, while others can determine the length of hospital stay, treatment strategy, or choice of investigative protocol. The most commonly used risk stratification system in EDs around the world has five urgency levels or categories.

CATEGORY	DESCRIPTION	WAITING TIME
1	Immediate	None
2	Very Urgent	2 -10 Minutes
3	Urgent	30 Minutes
4	Routine	One hour
5	Not Urgent	Two hours

Category 1: These patients are critically impaired but likely survive if given immediate, life-saving treatment. Therefore, they are given first priority towards resources.

Category 2: This category includes patients with severe life-threatening illnesses who require intervention as soon as possible. They are generally attended to within 10 minutes.

Category 3: These patients have severe illnesses and need to be treated within 30 minutes.

Category 4: This category includes patients with a potentially severe condition that must be treated within an hour.

Category 5: These patients have less urgent conditions and can wait up to 2 hours.

Hospital Triage Categories

The most commonly used triage system around the world is the START triage system. In this system, all injured individuals >8 years of age are evaluated, based on the system’s algorithm, in 60 seconds or less. The criteria used for this system is based on the following⁴⁷:

The patient’s ability to walk
Respiratory rate
Capillary filling
Radial pulse
Obeying the commands of the healthcare professional

After examining each of the above criteria, the patient is marked by one of the red, yellow, green, and black tags. The four-color tags mean the following⁴⁷:

Red: Patients who need immediate medical care are put in this category. These patients cannot follow commands, do not have a radial pulse, and their respiratory rate is >30 breaths/min.
Yellow: Urgent non-ambulatory patients who can follow commands.
Green: Non-urgent patients who can walk.
Black: Deceased patients

Biomarkers in Triage

Biomarkers refer to biochemical parameters that are upregulated or downregulated in association with a disease. When compared to vital signs, biomarkers are objective, dynamic, and easily measurable. Therefore, triaging using biomarker assays can provide rational risk stratifications more rapidly than conventional triages.

Many biomarkers have been identified for their prognostic ability and included in Emergency departments across the world. These include lactate²¹, copeptin²², pro-adrenomedullin (proADM)^23,26,27,28, albumin²⁴, procalcitonin (PCT)²³, C-reactive protein (CRP)²⁵ and soluble urokinase plasminogen activator receptor (suPAR).

Chest pain is the most common cause of ED visits worldwide. However, traditional evaluation methods such as physical examinations, X-rays, and EKG are less sensitive and time-consuming. The detection of improved cardiac biomarkers, including Ck-MB, troponin, myoglobin²⁹ , etc., has enabled enhanced risk stratifications that do not require admission to the hospital, thus vastly reducing healthcare costs³⁰.

Even in resource-poor settings in Tanzania, a combination of 11 host-response biomarkers, including STREM 1, C-reactive protein (CRP), and procalcitonin (PCT), outperformed conventional triages in accurately stratifying patients³¹.

In some diseases such as septicaemia, pneumonia, stroke, and myocardial infarction, early risk categorisation using biomarkers has helped save lives²³.  Similarly, for patients with prostate cancer, triaging using Prostate Cancer Antigen (PCA3), TMPRSS2-ERG, SelectMDx, and S3M resulted in early diagnosis and reduced mortality³².

Biomarkers have proved particularly useful in etiologically variant conditions that are hard to diagnose visually. Respiratory infections are the most common cause of ED visits in low-income countries. While triaging patients in those countries, proADM assays have helped accurately detect the severity of infection, thus reducing the length of stay and rate of readmissions³³.

Biomarkers assays are also significant in conditions that appear curable but may rarely lead to sepsis and mortality. For example, febrile urinary tract infections are usually treatable with oral anti-microbial, but in rare cases, lead to septic shock. The biomarker MR-proADM was able to accurately detect people who required subsequent hospitalisation³⁴.

What is C-reactive protein

CRP is a protein produced by liver cells. The concentration of CRP in the bloodstream increases in the presence of infection and inflammation. Thus, the level of CRP in blood samples is a sensitive indicator of inflammatory conditions, infections, etc. CRP has been found to be an effective biomarker for triage⁵³. A high CRP is indicative of bacterial infection and is often used to prescribe antibiotics.

What is suPAR

suPAR is a non-specific marker for inflammation and overall patient health status. Compared to CRP, suPAR is a stronger indicator of patient prognosis and disease severity. As suPAR has a high negative predictive value, a low suPAR level is often used for the discharge decision in combination with clinical signs⁵⁴.

References

1. Hing, E. & Bhuiya, F. Wait time for treatment in hospital emergency departments: 2009. NCHS Data Brief 1–8 (2012).

2. Christ, M., Grossmann, F., Winter, D., Bingisser, R. & Platz, E. Modern Triage in the Emergency Department. Dtsch Arztebl Int 107, 892–898 (2010).

3. Mullan, P. C., Torrey, S. B., Chandra, A., Caruso, N. & Kestler, A. Reduced overtriage and undertriage with a new triage system in an urban accident and emergency department in Botswana: a cohort study. Emerg Med J 31, 356–360 (2014).

4. Olson et al.,. Task shifting an inpatient triage, assessment and treatment programme improves the quality of care for hospitalised Malawian children. Tropical Medicine and Internation Health 18, 879–86 (2013).

5. Raper, J., Davis, B. A. & Scott, L. Patient satisfaction with emergency department triage nursing care: a multicenter study. J Nurs Care Qual 13, 11–24 (1999).

6. Subash, F., Dunn, F., McNicholl, B. & Marlow, J. Team triage improves emergency department efficiency. Emerg Med J 21, 542–544 (2004).

7. Wiler, J. L. et al. Optimizing emergency department front-end operations. Ann Emerg Med 55, 142-160.e1 (2010).

8. Keep, J. W. et al. National early warning score at Emergency Department triage may allow earlier identification of patients with severe sepsis and septic shock: a retrospective observational study. Emerg Med J 33, 37–41 (2016).

9. Lee, A. et al. How to minimize inappropriate utilization of Accident and Emergency Departments: improve the validity of classifying the general practice cases amongst the A&E attendees. Health Policy 66, 159–168 (2003).

10. Richardson, J. R., Braitberg, G. & Yeoh, M. J. Multidisciplinary assessment at triage: a new way forward. Emerg Med Australas 16, 41–46 (2004).

11. Considine, J., Kropman, M., Kelly, E. & Winter, C. Effect of emergency department fast track on emergency department length of stay: a case-control study. Emerg Med J 25, 815–819 (2008).

12. Gravel et al., J. Interrater agreement between nurses for the Pediatric Canadian Triage and Acuity Scale in a tertiary care center. Academic Emergency Medicine 15, 1262–7 (2008).

13. Elizabeth, F. Chapter 54, Ciottone’s Disaster Medicine. (2016).

14. Griffiths, P., Edwards, M., Forbes, A. & Harris, R. Post-acute intermediate care in nursing-led units: a systematic review of effectiveness. Int J Nurs Stud 42, 107–116 (2005).

15. Farrohknia, N. et al. Emergency department triage scales and their components: a systematic review of the scientific evidence. Scand J Trauma Resusc Emerg Med 19, 42 (2011).

16. Jenson, A. et al. Reliability and validity of emergency department triage tools in low- and middle-income countries: a systematic review. Eur J Emerg Med 25, 154–160 (2018).

17. Lerner, E. B. et al. Mass casualty triage: an evaluation of the data and development of a proposed national guideline. Disaster Med Public Health Prep 2 Suppl 1, S25-34 (2008).

18. Rahmati, H., Azmoon, M., Kalantari Meibodi, M. & Zare, N. Effects of Triage Education on Knowledge, Practice and Qualitative Index of Emergency Room Staff: A Quasi-Interventional Study. Bull Emerg Trauma 1, 69–75 (2013).

19. Souza, C. C. de, Toledo, A. D., Tadeu, L. F. R. & Chianca, T. C. M. Risk classification in an emergency room: agreement level between a Brazilian institutional and the Manchester Protocol. Revista Latino-Americana de Enfermagem 19, 26–33 (2011).

20. Azeredo, T. R. M., Guedes, H. M., Rebelo de Almeida, R. A., Chianca, T. C. M. & Martins, J. C. A. Efficacy of the Manchester Triage System: a systematic review. Int Emerg Nurs 23, 47–52 (2015).

21. Barfod, C. et al. Peripheral venous lactate at admission is associated with in-hospital mortality, a prospective cohort study. Acta Anaesthesiol Scand 59, 514–523 (2015).

22. Nickel, C. H., Bingisser, R. & Morgenthaler, N. G. The role of copeptin as a diagnostic and prognostic biomarker for risk stratification in the emergency department. BMC Med 10, 7 (2012).

23. Schuetz et al., P. Biomarkers from distinct biological pathways improve early risk stratification in medical emergency patients: the multinational, prospective, observational TRIAGE study. Critical Care (London, England) 19, (2015).

24. Socorro García, A., de la Fuente Hermosín, I. & Baztán, J. J. Serum albumin and total cholesterol as prognostic factors of mortality in very old patients hospitalized by acute illness. European Geriatric Medicine 6, 442–446 (2015).

25. Oh, J. et al. High-sensitivity C-reactive protein/albumin ratio as a predictor of in-hospital mortality in older adults admitted to the emergency department. Clin Exp Emerg Med 4, 19–24 (2017).

26. Liu, D., Xie, L., Zhao, H., Liu, X. & Cao, J. Prognostic value of mid-regional pro-adrenomedullin (MR-proADM) in patients with community-acquired pneumonia: a systematic review and meta-analysis. BMC Infect Dis 16, 1–11 (2016).

27. Pavo, N. et al. Cardiovascular biomarkers in patients with cancer and their association with all-cause mortality. Heart 101, 1874–1880 (2015).

28. Suberviola et al., B. Hospital mortality prognostication in sepsis using the new biomarkers suPAR and proADM in a single determination on ICU admission. Intensive Care Medicine 39, 1945–52 (2013).

29. Dhingra, R. & Vasan, R. S. Biomarkers in Cardiovascular Disease. Trends Cardiovasc Med 27, 123–133 (2017).

30. DeLaney, M. C., Neth, M. & Thomas, J. J. Chest pain triage: Current trends in the emergency departments in the United States. J Nucl Cardiol 24, 2004–2011 (2017).

31. Richard-Greenblatt, M. et al. Prognostic accuracy of sTREM-1-based algorithms in febrile adults presenting to Tanzanian outpatient clinics. Clin. Infect. Dis. (2019) doi:10.1093/cid/ciz419.

32. Osses, D. F., Roobol, M. J. & Schoots, I. G. Prediction Medicine: Biomarkers, Risk Calculators and Magnetic Resonance Imaging as Risk Stratification Tools in Prostate Cancer Diagnosis. International Journal of Molecular Sciences 20, 1637 (2019).

33. Albrich, W. C. et al. Biomarker-enhanced triage in respiratory infections: a proof-of-concept feasibility trial. Eur. Respir. J. 42, 1064–1075 (2013).

34. Stalenhoef, J. E. et al. Biomarker guided triage can reduce hospitalization rate in community acquired febrile urinary tract infection. Journal of Infection 77, 18–24 (2018).

35. Sidenius, N. et al. Serum level of soluble urokinase-type plasminogen activator receptor is a strong and independent predictor of survival in human immunodeficiency virus infection. Blood 96, 4091–4095 (2000).

36. Haupt, T. H. et al. Plasma suPAR levels are associated with mortality, admission time, and Charlson Comorbidity Index in the acutely admitted medical patient: a prospective observational study. Crit Care 16, R130 (2012).

37. Østervig, R. M. et al. SuPAR – A future prognostic biomarker in emergency medicine. Scand J Trauma Resusc Emerg Med 23, A31 (2015).

38. Min, H. Y. et al. Urokinase receptor antagonists inhibit angiogenesis and primary tumor growth in syngeneic mice. Cancer Res. 56, 2428–2433 (1996).

39. Thunø et al., M. suPAR: The Molecular Crystal Ball. Molecular Markers of Infectious Diseases Volume 27, (2009).

40. Hodges et al., G. suPAR: A New Biomarker for Cardiovascular Disease? – PubMed – NCBI. Canadian journal of cardiology 10, 1293–302. (2015).

41. Botha et al., S. Associations of suPAR with lifestyle and cardiometabolic risk factors. Eur J Clin Invest 44, 619–26 (2014).

42. Nayak, R. K., Allingstrup, M., Phanareth, K. & Kofoed-Enevoldsen, A. suPAR as a biomarker for risk of readmission and mortality in the acute medical setting. Dan Med J 62, A5146 (2015).

43. Bassat, Q. The Perks of Prognostic Biomarkers: A Paradigm Shift in the Triage of Sick Febrile Patients. Clin Infect Dis doi:10.1093/cid/ciz420.

44. Schultz, M. et al. Early Discharge from the Emergency Department Based on Soluble Urokinase Plasminogen Activator Receptor (suPAR) Levels: A TRIAGE III Substudy. Dis Markers 2019, (2019).

45. Rasmussen, L.J.H. et al. Soluble urokinase plasminogen activator receptor (suPAR) in acute care: a strong marker of disease presence and severity, readmission and mortality. A retrospective cohort study. Emergency Medicine Journal 33.11, 769-775. (2016).

46. Rasmussen, L.J.H. et al. Combining National Early Warning Score with soluble urokinase plasminogen activator receptor (suPAR) improves risk prediction in acute medical patients: a registry-based cohort study. Critical care medicine 46.12: 1961. (2018).

47. Bazyar J, Farrokhi M, Khankeh H. Triage Systems in Mass Casualty Incidents and Disasters: A Review Study with A Worldwide Approach. Open Access Maced J Med Sci. 2019;7(3):482‐494. Published 2019 Feb 12. doi:10.3889/oamjms.2019.119

48. https://qsofa.org/what.php

49. Nordberg M, Lethvall S, Castrén M. The validity of the triage system ADAPT. Scand J Trauma Resusc Emerg Med. 2010;18(Suppl 1):P36. Published 2010 Sep 17. doi:10.1186/1757-7241-18-S1-P36

50. Bilben B, Grandal L, Søvik S. National Early Warning Score (NEWS) as an emergency department predictor of disease severity and 90-day survival in the acutely dyspneic patient – a prospective observational study. Scand J Trauma Resusc Emerg Med. 2016;24:80. Published 2016 Jun 2. doi:10.1186/s13049-016-0273-9

51. Aminiahidashti H, Bozorgi F, Montazer SH, Baboli M, Firouzian A. Comparison of APACHE II and SAPS II Scoring Systems in Prediction of Critically Ill Patients’ Outcome. Emerg (Tehran). 2017;5(1):e4.

52. Marik PE, Taeb AM. SIRS, qSOFA and new sepsis definition. J Thorac Dis. 2017;9(4):943‐945. doi:10.21037/jtd.2017.03.125

53. Li Q, Ding X, Xia G, et al. Eosinopenia and elevated C-reactive protein facilitate triage of COVID-19 patients in fever clinic: a retrospective case-control study [published online ahead of print, 2020 May 3]. EClinicalMedicine. 2020;100375. doi:10.1016/j.eclinm.2020.100375

54. Schultz M, Rasmussen LJH, Kallemose T, et al. Availability of suPAR in emergency departments may improve risk stratification: a secondary analysis of the TRIAGE III trial. Scand J Trauma Resusc Emerg Med. 2019;27(1):43. Published 2019 Apr 11. doi:10.1186/s13049-019-0621-7

55. Kumar P, Kakar A, Gogia A, Waziri N. Evaluation of soluble urokinase-type plasminogen activator receptor (suPAR) quick test for triage in the emergency department. J Family Med Prim Care. 2019;8(12):3871‐3875. Published 2019 Dec 10. doi:10.4103/jfmpc.jfmpc_116_19

56. Kyriazopoulou, E., Poulakou, G., Milionis, H. et al. Early treatment of COVID-19 with anakinra guided by soluble urokinase plasminogen receptor plasma levels: a double-blind, randomized controlled phase 3 trial. Nat Med (2021). https://doi.org/10.1038/s41591-021-01499-z

57. VELISSARIS, D., LAGADINOU, M., PARASKEVAS, T., OIKONOMOU, E., KARAMOUZOS, V., KARTERI, S., BOUSIS, D., PANTZARIS, N., TSIOTSIOS, K., MARANGOS, M.. Evaluation of Plasma Soluble Urokinase Plasminogen Activator Receptor Levels in Patients With COVID-19 and Non-COVID-19 Pneumonia: An Observational Cohort Study. Journal of Clinical Medicine Research, North America, 13, oct. 2021. Available at: <https://www.jocmr.org/index.php/JOCMR/article/view/4579/25893473>