European Heart Journal: Acute Cardiovascular Care (2022) 11, 731–738 ORIGINAL SCIENTIFIC PAPER https://doi.org/10.1093/ehjacc/zuac096 Biomarkers Soluble urokinase-type plasminogen activator receptor improves early risk stratification in cardiogenic shock Mari Hongisto 1,*, Johan Lassus2, Tuukka Tarvasmäki 2, Jordi Sans-Roselló3, Heli Tolppanen2, Anu Kataja1, Toni Jäntti2, Tuija Sabell2, Marek Banaszewski4, Jose Silva-Cardoso5, John Parissis6, Raija Jurkko2, Jindrich Spinar7, Maaret Castrén 1, Alexandre Mebazaa8, Josep Masip9, and Veli-Pekka Harjola1 for the CardShock Study Investigators and the GREAT Network 1 Emergency Medicine, University of Helsinki, Department of Emergency Medicine and Services, Helsinki University Hospital, Helsinki, Finland; 2Cardiology, University of Helsinki and Heart and Lung Centre, Helsinki University Hospital, Helsinki, Finland; 3Cardiology Department, Hospital de la Santa Creu I Sant Pau, Universitat Autònoma de Barcelona, Biomedical Research Institute IIB-Sant Pau, CIBER-CV, Spain; 4National Institute of Cardiology, Warsaw, Poland; 5CINTESIS—Center for Health Technology and Services Research, Faculty of Medicine, University of Porto, São João University Medical Center, Faculty of Medicine, University of Porto, Porto, Portugal; 6ER and Heart Failure Unit, Attikon University Hospital, National and Kapodestrian University of Athens, Athens, Greece; 7St. Ann university hospital and Medical faculty Masaryk University, Brno, Czech Republic; 8Université de Paris, Inserm 942—MASCOT, Paris, France; and 9Research Direction, Consorci Sanitari Integral, University of Barcelona, Barcelona, Spain Received 19 May 2022; revised 14 July 2022; accepted 1 August 2022; online publish-ahead-of-print 11 August 2022 Aims Soluble urokinase–type plasminogen activator receptor (suPAR) is a biomarker reflecting the level of immune activation. It has been shown to have prognostic value in acute coronary syndrome and heart failure as well as in critical illness. Considering the complex pathophysiology of cardiogenic shock (CS), we hypothesized suPAR might have prognostic prop­ erties in CS as well. The aim of this study was to assess the kinetics and prognostic utility of suPAR in CS. ............................................................................................................................................................................................. Methods SuPAR levels were determined in serial plasma samples (0–96 h) from 161 CS patients in the prospective, observational, and results multicentre CardShock study. Kinetics of suPAR, its association with 90-day mortality, and additional value in risk-stratifi­ cation were investigated. The median suPAR-level at baseline was 4.4 [interquartile range (IQR) 3.2–6.6)] ng/mL. SuPAR levels above median were associated with underlying comorbidities, biomarkers reflecting renal and cardiac dysfunction, and higher 90-day mortality (49% vs. 31%; P = 0.02). Serial measurements showed that survivors had significantly lower suPAR levels at all time points compared with nonsurvivors. For risk stratification, suPAR at 12 h (suPAR12h) with a cut- off of 4.4 ng/mL was strongly associated with mortality independently of established risk factors in CS: OR 5.6 (95% CI 2.0–15.5); P = 0.001) for death by 90 days. Adding suPAR12h > 4.4 ng/mL to the CardShock risk score improved discrim­ ination identifying high-risk patients originally categorized in the intermediate-risk category. ............................................................................................................................................................................................. Conclusion SuPAR associates with mortality and improves risk stratification independently of other previously known risk factors in CS patients. * Corresponding author. Tel: +358 40 586 3263, Fax: +358 9 471 66650, Email: mari.hongisto@hus.fi © The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com 732 M. Hongisto et al. Graphical Abstract Soluble urokinase-type plasminogen activator receptor (suPAR) improves early risk stratification in cardiogenic shock spesifically in patients with intermediate risk. ............................................................................................................................................................................................. Keywords Cardiogenic shock • suPAR • Risk stratification • Biomarker multicentre study on CS conducted in nine tertiary centres in eight European Introduction countries between October 2010 and December 2012. A detailed description Cardiogenic shock (CS) is the most life-threating manifestation of acute of the study design and main results have been previously published.11 heart failure (HF) characterized by systemic hypoperfusion due to se­ vere cardiac dysfunction, often leading to multi-organ failure. In add­ Inclusion criteria and data collection ition, the activation of systemic inflammatory responses plays a Patients (n = 219) aged over 18 years were included within 6 hours from central role in the complex pathogenesis of CS.1 the detection of shock. In addition to an acute cardiac cause, the inclusion Soluble urokinase–type plasminogen activator receptor (suPAR) is criteria required a systolic blood pressure (SBP) of < 90 mmHg for 30 min the soluble form of the membrane-bound urokinase plasminogen acti­ (despite adequate fluid administration), or the need for a vasopressor to vator receptor.2,3 SuPAR is thought to reflect the level of immune ac­ maintain SBP > 90 mmHg and at least one sign of hypoperfusion (altered tivation. It has been shown to have excellent prognostic properties in mental status, cold periphery, oliguria < 0.5 mL/kg/h for the previous 6 h, several acute and chronic inflammatory states, including infectious dis­ or blood lactate > 2 mmol/L). Exclusion criteria included shock caused by ongoing haemodynamically significant arrhythmia and shock after cardiac eases, cancer, organ failures, critical illnesses, and cardiovascular dis­ or non-cardiac surgery. The aetiology of CS [acute coronary syndrome eases.4–9 High suPAR levels are known to associate with worse (ACS) or non-ACS] was defined by the local investigators, and the patients outcome in acute and chronic kidney disease, as well as in HF.7,9,10 were treated according to local clinical practice. Medical history, baseline Biomarkers have proved to be helpful in risk stratification and prog­ characteristics, clinical signs, and treatment and procedures were recorded. nostication in cardiovascular diseases. We hypothesized that suPAR The primary endpoint was 90-day all-cause mortality. Written informed could serve as a biomarker reflecting multi-organ dysfunction as well consent was obtained from each patient or next of kin if the patient was as the severity of the systemic inflammatory response involved in CS unable to give the consent on admission. The study was approved by local pathogenesis, and be valuable in risk prediction in CS. ethics committees and conducted in accordance with the Declaration of The aim of this study was to investigate the role of suPAR in CS using Helsinki. serial measurements, to assess its association with organ dysfunction, and to evaluate the prognostic ability and value of suPAR in early risk Blood sampling and laboratory analyses stratification in CS. Serial plasma samples were collected at seven pre-specified time points: at baseline (0 h), 12, 24, 36, 48, 72, and at 96 h. Plasma aliquots were imme­ Methods diately frozen and stored at –70°C until assayed. Patients with available study plasma samples at baseline were included in this substudy (n = 161); This was a biomarker substudy of the CardShock study. The CardShock study two centres did not participate in the biomarker substudy. Creatinine, (ClinicalTrials.gov identifier: NCT01374867) was a prospective, observational, C-reactive protein, alanine aminotransferase, high-sensitivity troponin T SuPAR improves risk stratification in cardiogenic shock 733 (hsTnT), and n-terminal pro–B-type natriuretic peptide (NT-proBNP) were Table 1 outlines the clinical characteristics and presentation, bio­ analysed using assays from Roche Diagnostics (Basel, Switzerland), whereas chemistry at baseline, and treatment, stratified by the baseline median suPAR was analysed using a commercially available enzyme-linked immuno­ suPAR level. The prevalence of comorbidities, particularly HF, atrial fib­ sorbent assay (ELISA) kit (suPARnostic®, ViroGates, Denmark). SuPAR rillation, and renal failure, was significantly higher among those with a was analysed by ViroGates in Denmark, whereas rest of the biomarkers baseline suPAR above median, as were the levels of creatinine, were analysed at a central accredited laboratory (ISLAB, Kuopio, Finland). Arterial blood lactate and pH were analysed locally. Estimated glomerular fil­ NT-proBNP, and CRP. ACS aetiology was more common in patients tration rate (eGFR) was calculated from creatinine values using the CKD-EPI with suPAR ≤ median. The treatment did not differ with respect to (Chronic Kidney Disease Epidemiology Collaboration) equation.12 the suPAR level (Table 1). The use of mechanical assist devices was in­ frequent in this study, only few patients were treated with temporary mechanical circulatory support, except for the use of intra-aortic bal­ Statistical analyses loon pump, which was used in 87 (46%) patients. Results are presented as numbers (n) and percentages (%) for categor­ ical variables, and as means and standard deviations (SD), or as medians Correlation of suPAR with other and interquartile ranges (IQRs) for continuous variables, as appropri­ biomarkers ate. Patients were categorized by the baseline median suPAR into SuPAR correlated moderately with markers reflecting renal function two groups: (i) above median and (ii) median or less. Between-group (creatinine ρ = 0.44, P < 0.001; and estimated GFR ρ = –0.46; P < 0.001), comparisons were performed using Chi-squared tests or Fisher’s ex­ congestion/cardiac stress (NT-proBNP ρ = 0.41, P < 0.001), and CRP act tests for categorical variables and Student’s t-tests or Mann– (ρ = 0.38; P < 0.001). Conversely, suPAR did not correlate with hs-TnT, Whitney U tests for continuous variables, as appropriate. Wilcoxon neutrophil-to-lymphocyte ratio (NLR) or with pH, and its correlation signed rank tests were used to determine differences in serial suPAR with age (ρ = 0.26; P = 0.003), lactate (ρ = 0,30; P = 0.001), and Alat measurements. Spearman tests were used to assess the correlation (ρ = 0.22; P = 0.008) was modest. of suPAR with other biomarkers. The correlation analyses were per­ formed on samples taken at 12 h. Differences in suPAR levels between survivors and non-survivors over time were analysed with linear mixed Outcome and serial sampling of suPAR modelling; due to skewed distribution, suPAR values were log- Clinical outcomes, stratified by the baseline median suPAR level, are transformed to normalize the distribution and the residuals. The pri­ presented in Table 1. Mortality at 90 days was significantly higher in mary endpoint was all-cause 90-day mortality; three patients were those having baseline suPAR above median (49% vs. 31%; P = 0.02). lost to follow-up. According to serial measurements, survivors had significantly lower Kaplan–Meier curves were used to examine the 90-day survival and suPAR levels at all time points compared with non-survivors log-rank tests were used for group comparisons. A multivariate logistic (Figure 1; P < 0.001 for between-group, and P < 0.001 for all pairwise regression model was used to evaluate the association of suPAR with comparisons). Furthermore, suPAR levels remained fairly stable during 90-day mortality. The model was adjusted with the CardShock risk the first 24 h among survivors 4.15 (IQR 2.85–5.95) ng/mL at baseline score, a nine-point risk prediction tool for in-hospital mortality consist­ vs. 3.84 (IQR 2.80–5.46) ng/mL at 24 h; P = 0.84. In contrast, in non- ing of seven clinical parameters: age, eGFR, blood lactate, confusion on survivors suPAR levels increased from 5.11 (IQR 3.36–7.13) ng/mL at admission, left ventricular ejection fraction (LVEF), previous myocardial baseline to 5.90 (IQR 4.49–9.32) ng/mL at 24 h; P < 0.001. Changes in infarction or coronary artery bypass grafting, and ACS aetiology.11 suPAR levels differed significantly between survivors and non-survivors Results from the regression analyses are presented as odds ratios during the whole study period (Pinteraction < 0.001) (Figure 1). (ORs) with 95% confidence intervals (CIs). To evaluate the prognostic value of suPAR and its capability to im­ SuPAR in risk prediction prove discrimination beyond the CardShock risk score, receiver oper­ To assess the ability of suPAR for early risk stratification in CS, we se­ ating characteristic (ROC) curves were generated and the areas under lected suPAR12h for further analysis (n = 138). When analysed as a con­ the curves (AUC) were calculated. The Youden index was used to de­ tinuous variable, SuPAR12h had an AUC of 0.72 for 90-day mortality. termine the optimal cut-off value for suPAR at 12 h (suPAR12h) from According to the Youden index, the optimal cut-off value for the ROC curve. The additional value of suPAR in the risk prediction suPAR12h to predict outcome was 4.4 ng/mL. Patients with suPAR12h model was assessed using the likelihood ratio test for nested models. > 4.4 ng/mL had a 90-day mortality of 56% compared with 19% for A two-sided P value <0.05 was regarded as statistically significant. All those with suPAR12h ≤ the cut-off (P < 0.001). After adjustment for statistical analyses were performed with SPSS 25.0 software (IBM, the CardShock risk score variables, suPAR12h remained an independent Armonk, NY). predictor for 90-day mortality, OR 5.6 (2.0–15.5); P = 0.001. We ana­ lysed the predictive role of NLR as well. Although NLR was an inde­ pendent predictor for 90-day mortality when adjusted for the Results CardShock variables (OR 0.94 [0.89–0.996]; P = 0.04), after adjusting This study included 161 patients with a mean age of 66 (12) years; 26% this model further with suPAR12h ≥ 4.4 ng/mL, NLR lost its predictive were women, and ACS was the main cause of shock (79%). All-cause role, but suPAR associated independently with the outcome. mortality at 90 days was 40%. The clinical characteristics of the study As a binary variable partitioned by the cut-off value, SuPAR12h im­ population are presented in Table 1. proved discrimination compared to CardShock risk score alone (AUC 0.87 vs. 0.84; χ2 = 14.2 for 90-day mortality prediction; P < 0.001 for comparison of nested models) (Figure 2) as well as when SuPAR levels in CS added on top of the CardShock risk score and NLR (AUC 0.81 vs. Baseline suPAR level measurements were available from 161 patients, 0.86; P = 0.004) (see Supplementary material online, Figure S1). with a median of 4.4 (IQR 3.2–6.6) ng/mL. In serial sampling, the me­ Kaplan-Meier analysis showed that, by dividing each CardShock dian level of the biomarker remained relatively stable during the risk category by the suPAR12h cut-off into two subgroups (low/inter­ first 12 h [4.4 (IQR 3.3–7.5) ng/mL at 12 h] but tended to increase mediate/high risk category + suPAR12h above or below cut-off), risk from then on, reaching a maximum at 96 h with a median of 5.6 stratification improved, especially in the intermediate risk group (IQR 4.1–9.4) ng/mL. (Figure 3). 734 M. Hongisto et al. Table 1 Clinical characteristics and presentation, biochemistry, treatment of the shock, and outcome All n = 161 suPAR ≤ median n = 81 suPAR > median n = 80 P-value ...................................................................................................................................................................................... Age, years (SD) 66 (12) 66 (11) 66 (12) 1.0 Female, n (%) 41 (26) 21 (26) 20 (25) 0.9 BMI, kg/m2 (SD) 27 (4) 27 (4) 27 (4) 0.8 Aetiology of shock, n (%) ACS 127 (79) 71 (88) 56 (70) 0.006 STEMI 106 (66) 65 (80) 41 (53) <0.001 Medical history, n (%) Hypertension 100 (62) 47 (58) 53 (66) 0.3 Diabetes 48 (30) 21 (26) 27 (34) 0.3 Coronary artery disease 53 (33) 21 (26) 32 (40) 0.06 Heart failure 27 (17) 7 (9) 20 (25) 0.005 Atrial fibrillation 25 (16) 6 (7) 19 (24) 0.004 Renal insufficiency 19 (12) 1 (1) 18 (23) <0.001 Clinical presentation (at baseline) Systolic BP; mmHg 77 (14) 75 (12) 80 (15) 0.05 HR, beats/min 88 (28) 86 (26) 90 (29) 0.4 LVEF; % 32 (14) 35 (14) 29 (13) 0.006 CardShock risk score 4.3 (1.9) 3.9 (1.9) 4.7 (1.9) 0.008 Biochemistry (at baseline) Hemoglobin; g/L 129 (24) 132 (20) 125 (26) 0.05 CRP; mg/L 16 (2–75) 6 (2–25) 41 (9–89) <0.001 Creatinine; µmol/L 101 (77–139) 88 (69–114) 127 (91–168) <0.001 eGFR; mL/min/1.73 m2 62 (41-–87) 71 (55–96) 48 (30–70) <0.001 ALT; U/L 46 (21–96) 44 (23–79) 50 (20–141) 0.2 pH 7.32 (7.20–7.40) 7.34 (7.21–7.43) 7.30 (7.19–7.38) 0.3 Lactate; mmol/L 2.7 (1.6–5.9) 2.6 (1.5–4.9) 3.0 (1.7–6.8) 0.1 Peak lactate; mmol/L 3.0 (2.0–6.6) 2.7 (1.7–5.5) 3.2 (2.3–8.2) 0.6 NT-proBNP; ng/L 2450 (565–9172) 1077 (253–3589) 6726 (2088–16786) <0.001 hs-TnT; ng/L 1857 (365–5279) 1885 (446–5365) 1733 (208–5110) 0.6 NLR (n = 122) 6.5 (3.7–10.7) 7.0 (3.9–11.7) 5.9 (3.1–10.2) 0.6 Treatment, n (%) Coronary angiogram 132 (82) 75 (93) 57 (71) <0.001 PCIa 109 (83) 66 (88) 43 (75) 0.1 a CABG 6 (5) 2 (3) 4 (7) 0.4 Use of norepinephrine 127 (79) 64 (79) 63 (79) 0.90 Use of dobutamine 92 (57) 45 (56) 47 (59) 0.80 Invasive mechanical ventilation 105 (65) 52 (64) 53 (66) 0.60 Renal replacement therapy 18 (11) 7 (9) 11 (14) 0.30 In-hospital mortality, n (%) 59 (37) 23 (28) 36 (45) 0.03 90-day mortality, n (%) 64 (40) 25 (31) 39 (49) 0.02 Data are presented as numbers and percentages (%), means (with SD), or medians (with interquartile range), as appropriate. ACS, acute coronary syndrome; ALT, alanine aminotransferase; BMI, body mass index; BP, blood pressure; CABG, coronary artery bypass surgery ;CRP, C-reactive protein; eGFR, estimated glomerular filtration rate; HR, heart rate; LVEF, left ventricular ejection fraction; NLR, neutrophil-to-lymphocyte ratio; PCI, percutaneous coronary intervention; SD, standard deviation; STEMI, ST-elevation myocardial infarction. a Proportion of those who underwent angiogram. SuPAR improves risk stratification in cardiogenic shock 735 Figure 1 Soluble urokinase–type plasminogen activator receptor 0–96 h levels in survivors vs. non-survivors. Soluble urokinase–type plasminogen activator receptor levels during 0–96 h in survivors and non-survivors. Soluble urokinase–type plasminogen activator receptor median levels at each time point are presented below the figure. Figure 2 Receiver operating characteristic curves for predicting 90-day mortality. Receiver operating characteristic curves for 90-day mortality pre­ diction for (i) soluble urokinase–type plasminogen activator receptor at 12 h, (ii) CardShock risk score, and (iii) CardShock risk score + soluble uro­ kinase–type plasminogen activator receptor12h > 4.4 ng/mL. 736 M. Hongisto et al. Figure 3 Kaplan–Meier survival curves for 90-day mortality stratified by the CardShock risk score categories and soluble urokinase–type plasmino­ gen activator receptor above or below the cut-off-value 4.4 ng/mL at 12 h. Panel (A) comparison of survival curves according to the CardShock risk score categories (low/intermediate/high risk), (B) comparison of survival curves according to the CardShock risk score categories (low/intermedi­ ate/high risk) divided by the soluble urokinase–type plasminogen activator receptor cut-off 4.4 ng/mL at 12 h into two subgroups. Discussion concentrations between CS and sepsis or pancreatitis may be due to a higher degree of inflammation and a greater amount of inflamma­ This is the first study to assess suPAR in the context of CS and its as­ tory cells observed in the latter critical illnesses. This can be related to sociation with outcome. We report three main findings. First, suPAR two findings. First, shedding of urokinase-type plasminogen activation levels in CS are elevated and associate with comorbidities and acute or­ receptor (uPAR) from activated neutrophils has been shown to re­ gan dysfunctions. Secondly, higher suPAR levels are associated with present a main source of suPAR in serum and plasma in systemic in­ worse outcomes, and suPAR is a strong and independent predictor flammation and in patients with sepsis16 Secondly, although of mortality in CS. Finally, measuring suPAR12h from baseline with a cut- inflammation has a remarkable role in the complex pathophysiology off of 4.4 ng/mL improves early risk stratification. in CS, the degree of inflammation has shown to be much lower in The suPAR levels in our study were markedly lower than suPAR le­ CS than in septic shock.17 However, systemic inflammatory response vels reported in other critically ill patients. In sepsis, suPAR has been syndrome (SIRS) complicates approximately 20% of CS cases and is reported to be as high as 9–11 ng/mL, and, in acute severe pancrea­ associated with increased mortality.1 Biomarkers could help to iden­ titis, the biomarker has been shown even to reach 17 ng/mL.5,13,14 tify different phenotypes of CS, such as those with SIRS, and help with In contrast, the suPAR levels in this study more closely resemble the risk assessment. those reported in populations with ST-elevation myocardial infarc­ SuPAR was associated with a previous history of renal insufficiency tion and chronic HF (3.5–4 ng/mL).9,15 The differences in suPAR and HF, and it correlated positively with markers reflecting these SuPAR improves risk stratification in cardiogenic shock 737 derangements. This is not surprising, considering that suPAR is known presented with ACS-CS. In more recent studies non-ACS aetiology to be related to the pathogenesis and development of chronic kidney has been more common and in contrast to our study, the prognosis disease, and it was recently shown to be associated with a risk of acute has been better in patients with ACS-CS.19 kidney injury as well.7,10 In addition, suPAR has been shown to predict mortality in chronic HF.9 It remains unclear whether suPAR is a spe­ cific, prognostic biomarker for CS or merely reflects the severity of Conclusions underlying chronic as well as acute renal dysfunction and HF, both re­ lated to worse prognosis in CS. However, SuPAR was shown to be a Circulating suPAR levels are elevated in CS and associate with mul­ strong and independent predictor of mortality in CS. The underlying tiple acute and chronic organ impairments. Higher suPAR levels are pathophysiological mechanisms behind the incremental prognostic independently associated with mortality in CS patients. Finally, ability of suPAR are not fully understood. The causes may be multifac­ suPAR improves early risk stratification, especially in patients initial­ torial and relate to the close correlation of suPAR with existing co­ ly categorized into intermediate risk class by the CardShock risk morbidities and incident acute organ failures as well as with the score. complex pathophysiology of CS itself. NLR, another biomarker of inflammation, did not correlate with suPAR in our study. SuPAR outperformed NLR in prognostication Supplementary material and discrimination. Interestingly, higher NLR levels associated with a Supplementary material is available at European Heart Journal: Acute better outcome. Our results are somewhat contradictory compared Cardiovascular Care online. with a study by Jentzer et al.,18 who found high NLR levels to associate with a worse outcome. However, the association was seen in milder shock states but not in more severe cases reflecting probably dimin­ Acknowledgements ished role of inflammation and NLR or exhaustion of the immune sys­ The authors thankfully acknowledge the contribution of the CardShock tem in severe shock. The patient population in the study by Jentzer study investigators in all participating hospitals and the GREAT net­ et al.18 is quite different from our study—only 6% had CS as an admis­ work. Laboratory kits for suPAR analyses were kindly provided by sion diagnosis and in-hospital mortality in this study was low (8%). The Virogates (Birkerød, Denmark), and kits for NT-proBNP and hsTnT patients in our study suffered from more severe CS which probably ex­ were provided by Roche Diagnostics (Basel, Switzerland). plains the controversial observations. We found that an optimal cut-off of 4.4 ng/mL for suPAR12h Funding strongly predicted mortality and improved early risk stratification This work was supported by Aarne Koskelo Foundation, the Finnish when added to the CardShock risk score, especially in the patients Foundation for Cardiovascular Research, and Finnish state funding for with intermediate risk. This is an important finding, considering the university-level health research. M.H. received a personal scholarship acute setting of CS and the importance of identifying high-risk patients from the Department of Emergency Medicine and Services of Helsinki who would benefit most from further intensive and costly treatment University Hospital and a personal grant from Aarne Koskelo options, such as mechanical circulatory support. Evaluation of the pa­ Foundation. The funders had no role in study design, data collection and tients with intermediate risk with traditional clinical tools may remain analysis, decision to publish, or preparation of the manuscript. imprecise and potentially delay implication of further life-saving inter­ ventions. Using suPAR as a ‘warning bell’, in combination with mainly Conflict of interest: J.P. received honoraria for lectures from Orion clinical variables in the CardShock risk score, could identify patients at Pharma, Roche Diagnostics, Novartis, Astra and Servier. A.M. reports high risk more accurately, and thus guide the treatment intensity after personal fees from Orion, Servier, Otsuka, Philips, Sanofi, the initial phase of CS. Adrenomed, Epygon and Fire 1 and grants and personal fees from When a novel biomarker is considered to be applied in clinical use, 4TEEN4, Abbott, Roche and Sphyngotec. All other authors have no the costs and usefulness are carefully assessed. Considering suPAR, conflicts to declare. there is a commercially available kit with a rapid turnaround time. SuPAR can be analysed on automated analyser platforms routinely used in laboratories with short (1–2 h) turn-over times so the test re­ Data availability sults will be available in a time frame comparable to that of other rou­ The data underlying this article will be shared on reasonable request to tinely used biomarkers. Furthermore, there is a point-of-care -test the corresponding author. The data that support the findings of this available for suPAR increasing its attractiveness and applicability from study are available from the corresponding author (M.H.) upon reason­ a clinical point of view. The costs of suPAR testing are comparable to able request. other commonly used biomarkers. References 1. Kohsaka S, Menon V, Lowe AM, Lange M, Dzavik V, Sleeper LA, Hochman JS, SHOCK Limitations Investigators. 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