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02.11.2018 | Original Scientific Report (including Papers Presented at Surgical Conferences) Open Access

Soluble Urokinase Plasminogen Activator Receptor (suPAR) as an Added Predictor to Existing Preoperative Risk Assessments

World Journal of Surgery
Morten Alstrup, Jeppe Meyer, Martin Schultz, Line Jee Hartmann Rasmussen, Lars Simon Rasmussen, Lars Køber, Jakob Lundager Forberg, Jesper Eugen-Olsen, Kasper Iversen
Wichtige Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1007/​s00268-018-4841-1) contains supplementary material, which is available to authorized users.



Risk assessment strategies, such as using the American Society of Anesthesiologists (ASA) physical status classification, attempt to identify surgical high-risk patients. Soluble urokinase plasminogen activator receptor (suPAR) is a biomarker reflecting overall systemic inflammation and immune activation, and it could potentially improve the identification of high-risk surgical patients.


We included patients acutely admitted to the emergency department who subsequently underwent surgery within 90 days of admission. Patients were stratified into low-risk or high-risk groups, according to ASA classification (ASAlow: ASA I–II; ASAhigh: ASA III–VI) and suPAR level, measured at admission (suPARhigh above and suPARlow below 5.5 ng/ml), respectively. Pre-specified complications were identified in national registries and electronic medical records. The association between ASA classification, suPAR level, CRP and the rate of postoperative complications was analyzed with logistic regression and Cox regression analyses, estimating odds ratios and hazard ratios (HRs).


During 90-day follow-up from surgery, 31 (7.0%) patients died and 158 (35.6%) patients had postoperative complications. After adjusting for age, sex, and ASA classification, the HR for 90-day postoperative mortality was 2.5 (95% CI 1.6–4.0) for every doubling of suPAR level. suPAR was significantly better than CRP at predicting mortality and all complications (P = 0.0036 and P = 0.0041, respectively). Combining ASA classification and suPAR level significantly improved prediction of mortality and the occurrence of a postoperative complication within 90 days after surgery (P < 0.0001).


Measuring suPAR levels in acutely admitted patients may aid in identifying high-risk patients and improve prediction of postoperative complications.

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