Abstract
Introduction: Soluble urokinase plasminogen activator receptor (suPAR) is an emerging biomarker of the level of chronic systemic inflammation and the general condition of the patient. We aimed to investigate the impact of general anesthesia and major surgery on perioperative suPAR and C-reactive protein (CRP) levels. Methods: This study included patients undergoing elective major noncardiac surgery with an expected duration of ≥2 h under general anesthesia. Inclusion criteria were age ≥18 years and American Society of Anesthesiologists’ physical status I–IV. Blood was drawn 30 min prior to induction of anesthesia (preoperatively), as well as 30 min after emergence from anesthesia (postoperatively). Plasma suPAR levels were determined using the suPARnostic® Quick Triage lateral flow assay. CRP measurements were performed by particle-enhanced immunoturbidimetric assay. Results: The difference in preoperative and postoperative suPAR levels was not statistically significant (7.7 [5.28–10.4] ng/mL vs. 7.15 [5.68–9.8] ng/mL, p = 0.462). CRP levels increased significantly during surgery (0.81 [0.24–2.1] mg/dL vs. 5.76 [2.2–8.75] mg/dL, p < 0.001). No correlation was observed between CRP and suPAR levels, both preoperatively (rho = 0.127; p = 0.208) and postoperatively (rho = 0.017; p = 0.87). A statistically significant increase was also observed in postoperative white blood cell count (7.576 vs. 10.711, p < 0.001). Conclusion: General anesthesia and operative trauma did not affect perioperative suPAR levels despite the activation of systemic inflammatory response.
Introduction
In modern perioperative medicine, the evaluation of patient’s basal inflammatory status is important for maintaining homeostasis and improving outcomes after surgery [1]. Preoperative inflammation is usually assessed with biomarkers of acute inflammation, but these are rapidly up- and down-regulated, and thus, their quantification may be time-sensitive and unreliable [2]. On the other hand, there are currently no standard biomarkers for indicating the presence of organ-damaging chronic inflammation in surgical patients [3].
The biomarker soluble urokinase plasminogen activator receptor (suPAR) is a robust measure of chronic systemic inflammation [4]. suPAR is the soluble form of the cell membrane-bound protein urokinase plasminogen activator receptor (uPAR), which is expressed mainly on immune cells, endothelial cells, and smooth muscle cells. suPAR is cleaved from the surface of immunologically activated cells and can be detected in peripheral circulation. Its specific physiologic role is unclear, but its levels in circulation reflect the aggregate activity of the uPAR system with respect to innate immune activity, proteolysis, and extracellular matrix remodeling [5].
suPAR is a very stable molecule with minimal circadian changes, while its levels are under limited genetic influence [6‒8]. Of note, it has been associated with inflammatory activity and prognosis across a variety of conditions, including kidney disease, cardiovascular disease, cancer, diabetes, and others [4]. suPAR is not linked to a particular disease, but can be used as a quantifiable intermediate outcome between early risk factors and outcomes, e.g., mortality, and has been suggested as the best single marker of chronic organ damage and physiologic reserve [4]. Although these characteristics favor the use of suPAR within a personalized, physiology-guided perioperative strategy, it remains unknown if anesthesia and surgery impact its levels and therefore its prognostic capability.
In the present study, we assessed the impact of general anesthesia and surgical trauma on perioperative suPAR and CRP levels focusing on whether suPAR can be a reliable and stable marker of basal systemic inflammation in perioperative medicine.
Materials and Methods
Design
This prospective observational study was conducted at the University Hospital of Larisa, Larisa, Greece, from February 2019 to September 2020. Ethical approval was provided by the Ethics Committee of the University Hospital of Larisa (IRB No. 60580). The original study was designed in accordance with the declaration of Helsinki and was registered at ClinicalTrials.gov (NCT03851965). Written informed consent was obtained from all patients or next-of-kin.
Study Objectives
The primary objective was to characterize the relationship between preoperative and postoperative suPAR and CRP levels in patients undergoing elective major noncardiac surgery under general anesthesia. Secondary objective was to compare the correlation of suPAR and CRP with risk assessment models.
Patient Eligibility
We considered consecutive adult patients who were scheduled to undergo elective major noncardiac surgery with an expected duration of ≥2 h under general anesthesia. Patients were American Society of Anesthesiologists (ASA) physical status I to IV. All operative approaches were eligible, including open and laparoscopic procedures.
We excluded patients with infections within the previous month; severe liver disease; need for renal replacement therapy; allergies; inflammatory or immune disorders; asthma; obesity (BMI ≥30 kg m−2); mental disability or severe psychiatric disease; alcohol abuse; connective tissue disease including rheumatoid arthritis, ankylosing spondylitis, and systemic lupus erythematosus. We also excluded patients who had previously received an organ transplant; who were treated with steroids, antipsychotic or anti-inflammatory/immunomodulatory medication within the previous three months or with opioids during the past week; and who were involved in another study.
Anesthetic Management
Briefly, induction of anesthesia was in the supine position and included i.v. midazolam 0.15–0.35 mg kg−1 over 20–30 s, fentanyl 1 μg kg−1, ketamine 0.2 mg kg−1, propofol 1.5–2 mg kg−1, rocuronium 0.6 mg kg−1, and a fraction of inspired oxygen of 0.7. All drugs were prepared in labeled syringes, and induction was achieved by administration of a predetermined i.v. bolus dose on the basis of the patient’s weight and/or age. Laryngoscopy and intubation proceeded in a standard fashion, while the position of the endotracheal tube was confirmed by auscultation and capnography/capnometry. After tracheal intubation, patients were mechanically ventilated using a lung-protective strategy with tidal volume of 7 mL kg−1, positive end-expiratory pressure of 6–8 cm H2O, and plateau pressures <30 cm H2O (Draeger Perseus A500®; Drägerwerk AG & Co., Lübeck, Germany).
General anesthesia was maintained by inhalation of desflurane at an initial 1.0 minimal alveolar concentration. Thereafter, depth of anesthesia was adjusted to maintain Bispectral Index (BIS, Covidien, France) between 40 and 60 [9‒11]. Intraoperative fraction of inspired oxygen was then adjusted to maintain an arterial oxygen partial pressure of 80–100 mm Hg and normocapnia was maintained by adjusting the respiratory rate as needed [12‒15]. Normothermia (37°C) and normoglycemia were maintained during the perioperative period. Vasoactive drugs were administrated, if necessary, to maintain mean arterial pressure >65 mm Hg.
Sampling and Laboratory Measurements
Participants underwent sampling of peripheral venous blood 30 min prior to induction of anesthesia (preoperatively), as well as 30 min after emergence from anesthesia, at the postanesthesia care unit (postoperatively). For suPAR, blood samples were collected in EDTA tubes and were centrifuged at 3,000 g for 1 min. Plasma suPAR levels were then determined using the suPARnostic® Quick Triage lateral flow assay (ViroGates, Birkerød, Denmark), a point of care test that provides quantitative results in 20 min using an optical aLF Reader (QIAGEN, Hilden, Germany) [16]. CRP levels were determined by particle-enhanced immunoturbidimetric assay with the cobas C 702 analyzer, using the Tina-quant C-Reactive Protein IV kit (Roche Diagnostics, Mannheim, Germany). All assays were performed according to the manufacturers’ instructions.
Data Collection
Data collection included baseline demographics, ASA score, anesthesia parameters, general blood count, biochemistry profile, suPAR, CRP, Modified Frailty Index, POSSUM, and ACS-NSQIP risk score. Patients were followed for 1 year, and postoperative complications were registered using the Clavien-Dindo Classification and Comprehensive Complication Index (CCI) [17, 18].
Statistical Analysis
Statistical analysis was performed using R v4.0. Spearman’s method was used to perform linear correlations of suPAR and CRP levels with different clinical characteristics. The Benjamini-Hochberg false discovery rate correction was applied in the resulting p values to account for the multiple numbers of tests. The Wilcoxon sign-rank test was used to assess differences between pre- and postoperative characteristics, while the Kruskal-Wallis test was applied in comparisons involving more than two categories. Adjusted p values <0.05 were deemed significant.
Results
One hundred patients were included in the current analysis. Median age was 70 (62.5–75.5) years and 68 (68%) were men. We included 17 (17%) ASA II, 43 (43%) ASA III, and 40 (40%) ASA IV patients, while mean duration of surgical procedures was 133.8 ± 85.2 min. One hundred samples were collected preoperatively and 100 postoperatively. Median (range) time between preoperative and postoperative samples was 165.4 ± 31.5 min. Baseline characteristics and the type of surgery are shown in Table 1.
Perioperative suPAR Levels
The difference in preoperative and postoperative suPAR levels was not statistically significant (7.7 [5.28–10.4] ng/mL vs. 7.15 [5.68–9.8] ng/mL, p = 0.462) (shown in Fig. 1). We observed a statistically significant increase in preoperative suPAR levels with increasing ASA score (p = 0.014) (shown in online suppl. Fig. 1; see www.karger.com/doi/10.1159/000524433 for all online suppl. material). Of the other risk assessment models, CCI and POSSUM score were highly correlated with preoperative and postoperative suPAR levels (online suppl. Table 1).
Anesthesia and major noncardiac surgery did not affect perioperative suPAR levels (p= 0.462).
Anesthesia and major noncardiac surgery did not affect perioperative suPAR levels (p= 0.462).
Perioperative CRP Levels and Correlation with Risk Assessment Models and suPAR
CRP levels increased significantly during surgery (0.81 [0.24–2.1] mg/dL vs. 5.76 [2.2–8.75] mg/dL, p < 0.001) (shown in Fig. 2). Preoperative CRP levels were correlated with the Modified Frailty Index, while postoperative CRP levels were correlated with POSSUM score and the CCI (online suppl. Table 1). However, no correlation was observed between CRP and suPAR levels, both preoperatively (rho = 0.127; p = 0.208) and postoperatively (rho = 0.017; p = 0.87). Of note, the stability of suPAR was significantly higher compared to this of CRP (0.755, p < 0.001 vs. 0.268, p = 0.007).
Difference between preoperative and postoperative CRP levels (p< 0.001).
Perioperative White Blood Cell Count
A statistically significant increase in white blood cell count was observed after anesthesia and surgery (7.576 vs. 10.711, p < 0.001; shown in Fig. 3). No statistically significant correlation was observed between WBC and suPAR (p = 0.439) or between WBC and CRP (p = 0.38), either preoperatively or postoperatively.
Difference between preoperative and postoperative white blood cell count (p< 0.001).
Difference between preoperative and postoperative white blood cell count (p< 0.001).
Discussion
In this prospective observational study with patients undergoing major noncardiac surgery, anesthesia and surgical trauma did not affect perioperative suPAR levels despite the activation of systemic inflammatory response. In contrast, CRP levels significantly increased postoperatively. Preoperative and postoperative suPAR levels were also positively correlated with the risk assessment models. Furthermore, the stability of suPAR was significantly higher compared to this of CRP.
Although the inflammatory response may be exaggerated during surgery, investigations so far had not identified a biomarker that is not affected by anesthesia and/or surgical stress. With regard to surgical intervention outcome risk prediction, several authors have previously shown that the preoperative suPAR levels are highly predictable of postoperative complications [9, 19]. However, it was unknown if suPAR can be a reliable marker of basal systemic inflammation in perioperative medicine. The present study clearly suggests that perioperative circulating suPAR levels remain stable and are not affected by general anesthesia and/or the surgical stress response. A similar stability has also been reported in smaller cohorts, including patients undergoing elective coronary bypass graft surgery under cardiopulmonary bypass, septic surgical patients with bloodstream infection, and patients with anastomotic leakage after elective colorectal surgery [20‒22]. The present study includes a larger sample and various types of major non-cardiac surgery, highlighting the utility of suPAR in advanced perioperative management and planning.
Of note, genetic links have been reported between suPAR-measured chronic inflammation and phenotypes, such as diabetes, obesity, and chronic kidney disease, with the predictive value of suPAR being present years before the development of disease [4, 6, 9]. In the surgical population, suPAR may not only reflect the preoperative state of immune activation, but may also be associated with postoperative organ damage and complications [9, 23]. Indeed, we observed higher suPAR levels in patients with an ASA IV compared to those with an ASA II or III score, suggesting that suPAR also reflects the underlying comorbidities or more advanced disease. suPAR levels are elevated in a wide variety of diseases including cancer, where expression is increased in tumor cells and tumor-associated stromal cells [20]. Interestingly, the prognostic value of suPAR for incident cancer or mortality remains significant when controlling for CRP [4, 24]. Also, preoperative suPAR levels have been associated with increased mortality in kidney transplant recipients independent of kidney function [5, 25]. It is worth mentioning that suPAR retains its prognostic value even at low glomerular filtration rates, indicating that it is not just a marker of kidney function [4]. Furthermore, an inverse correlation between preoperative suPAR levels and intraoperative sublingual microcirculatory perfusion may exist in patients undergoing major noncardiac surgery [26, 27]. All these may explain the positive correlation of suPAR with the ASA score, the CCI, and the POSSUM scoring system in our study.
The temporal and kinetic stability of suPAR indicate that it reflects a more chronic aspect of inflammation. suPAR has low within-person variability, is characterized by small changes over time, and maintains a steady sample concentration after repeated freezing/thawing cycles [4]. In healthy individuals, suPAR has an excellent intraclass correlation coefficient (0.91, 95% CI 0.88–0.93) over months [28], as well as a high intra-individual correlation in samples taken 5–7 years apart [7, 29]. In addition, several studies have shown slower suPAR level increases in response to acute inflammatory stimuli compared to traditional inflammation markers [4]. Therefore, patients with increased baseline suPAR at the time of anesthesia/surgery may have lower capacity to tolerate the associated immunological challenges.
This study showed a significant difference between the kinetics of suPAR and that of CRP. Perioperative CRP levels were not correlated with perioperative suPAR levels, suggesting that suPAR can be used to distinguish the persistent chronic inflammation from the acute inflammatory response in surgical patients. Our deduction is further strengthened by the stability of suPAR, which was significantly stronger compared to this of CRP. Other authors have also shown that suPAR is only modestly associated with CRP and is less sensitive to acute inflammation, implying that these biomarkers may represent different pathways along the inflammatory cascade [30]. Of note, CRP is known to increase postoperatively because of the surgical trauma but tends to normalize rapidly due to the effects of anesthetics, its short plasma half-life, or in cases of minimally invasive procedures or uncomplicated postoperative course [20, 31‒33]. In contrast, perioperative suPAR levels remain stable. Adding suPAR measurements to existing blood test panels and/or risk scores may allow further stratification of preoperative inflammation and perioperative risk [4, 9, 19, 22].
We acknowledge that this is a single-center study with extensive exclusion criteria. However, this is the largest prospective cohort investigating the correlation between preoperative and postoperative suPAR levels. Despite the limitations, the present analysis revealed important associations and results that can be used in future studies. suPAR is an exciting new biomarker that may provide a robust and reliable measure of chronic systemic inflammation and improve perioperative management.
In conclusion, anesthesia and operative trauma did not affect perioperative suPAR levels despite the activation of systemic inflammatory response. The characteristics of suPAR can prove extremely important for the development of patient-specific strategies and inflammation-based scores, as well as for reducing cost and improving outcomes.
Acknowledgments
The authors would like to thank the medical and nursing stuff of the Department of Anesthesiology for their assistance during the study period.
Statement of Ethics
The protocol of the original study was reviewed and approved by the Ethics Committee of the University Hospital of Larisa, approval number 60580. Written informed consent was obtained from all patients or next-of-kin.
Conflict of Interest Statement
Dr. Eugen-Olsen is a co-founder, shareholder and CSO of ViroGates A/S, and is mentioned inventor on patents on suPAR owned by Copenhagen University Hospital Hvidovre, Denmark. All the other authors have no conflicts of interest to declare.
Funding Sources
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Author Contributions
A. Chalkias and J. Eugen-Olsen designed the study. E. Laou, A. Tsiaka, S. Tsapournioti, K. Chatzikallinikidis, G. Mantzaflaras, I. Karadontas, and A. Chalkias collected the data. N. Papagiannakis analyzed the data. E. Laou and A. Chalkias wrote the manuscript. E. Laou, N. Papagiannakis, A. Tsiaka, S. Tsapournioti, K. Chatzikallinikidis, G. Mantzaflaras, I. Karadontas, J. Eugen-Olsen, and A. Chalkias revised the intellectual content.
Data Availability Statement
Data can be made available upon request after publication through a collaborative process. Researchers should provide a methodically sound proposal with specific objectives in an approval proposal. Please contact the corresponding author for additional information.