Association of Preoperative Basal Inflammatory State, Measured by Plasma suPAR Levels, with Intraoperative Sublingual Microvascular Perfusion in Patients Undergoing Major Non-Cardiac Surgery
Abstract
:1. Introduction
2. Materials and Methods
2.1. Design
2.2. Study Objectives
2.3. Patient Eligibility
2.4. Anesthetic Management
2.5. Sampling and Laboratory Measurements
2.6. Sublingual Microcirculation Analysis
2.7. Data Collection, Monitoring, and Management
2.8. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Granger, D.N.; Senchenkova, E. Inflammation and the Microcirculation. In Colloquium Series on Integrated Systems Physiology: From Molecule to Function to Disease; Granger, D.N., Granger, J.P., Eds.; Morgan & Claypool Life Sciences: San Rafael, CA, USA, 2010; pp. 1–65. [Google Scholar]
- Payne, G.W. Effect of inflammation on the aging microcirculation: Impact on skeletal muscle blood flow control. Microcirculation 2006, 13, 343–352. [Google Scholar] [CrossRef] [PubMed]
- Armstead, W.M.; Cines, D.B.; Bdeir, K.; Kulikovskaya, I.; Stein, S.C.; Higazi, A.A. uPA impairs cerebrovasodilation after hypoxia/ischemia through LRP and ERK MAPK. Brain. Res. 2008, 1231, 121–131. [Google Scholar] [CrossRef] [Green Version]
- Nassar, T.; Yarovoi, S.; Fanne, R.A.; Waked, O.; Allen, T.C.; Idell, S.; Cines, D.B.; Higazi, A.A. Urokinase plasminogen activator regulates pulmonary arterial contractility and vascular permeability in mice. Am. J. Respir. Cell. Mol. Biol. 2011, 45, 1015–1021. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Takeishi, N.; Imai, Y.; Nakaaki, K.; Yamaguchi, T.; Ishikawa, T. Leukocyte margination at arteriole shear rate. Physiol. Rep. 2014, 2, e12037. [Google Scholar] [CrossRef] [PubMed]
- Becker, B.F.; Jacob, M.; Leipert, S.; Salmon, A.H.; Chappell, D. Degradation of the endothelial glycocalyx in clinical settings: Searching for the sheddases. Br. J. Clin. Pharmacol. 2015, 80, 389–402. [Google Scholar] [CrossRef] [PubMed]
- Guven, G.; Hilty, M.P.; Ince, C. Microcirculation: Physiology, Pathophysiology, and Clinical Application. Blood. Purif. 2020, 49, 143–150. [Google Scholar] [CrossRef] [PubMed]
- Bouattour, K.; Teboul, J.L.; Varin, L.; Vicaut, E.; Duranteau, J. Preload Dependence Is Associated with Reduced Sublingual Microcirculation during Major Abdominal Surgery. Anesthesiology 2019, 130, 541–549. [Google Scholar] [CrossRef] [PubMed]
- Bansch, P.; Flisberg, P.; Bentzer, P. Changes in the sublingual microcirculation during major abdominal surgery and post-operative morbidity. Acta. Anaesthesiol. Scand. 2014, 58, 89–97. [Google Scholar] [CrossRef] [PubMed]
- Kristensen, S.D.; Knuuti, J.; Saraste, A.; Anker, S.; Bøtker, H.E.; De Hert, S.; Ford, I.; Gonzalez Jua-natey, J.R.; Gorenek, B.; Heyndrickx, G.R.; et al. 2014 ESC/ESA Guidelines on noncardiac surgery: Cardiovascular assessment and management: The Joint Task Force on non-cardiac surgery: Cardiovascular assessment and management of the European Society of Cardiology (ESC) and the European Society of Anaesthesiology (ESA). Eur. J. Anaesthesiol. 2014, 31, 517–573. [Google Scholar] [PubMed] [Green Version]
- Gragnano, F.; Cattano, D.; Calabrò, P. Perioperative care of cardiac patient’s candidate for non-cardiac surgery: A critical appraisal of emergent evidence and international guidelines. Intern. Emerg. Med. 2018, 13, 1185–1190. [Google Scholar] [CrossRef] [PubMed]
- Chalkias, A.; Laou, E.; Kolonia, K.; Ragias, D.; Angelopoulou, Z.; Mitsiouli, E.; Kallemose, T.; Smith-Hansen, L.; Eugen-Olsen, J.; Arnaoutoglou, E. Elevated preoperative suPAR is a strong and independent risk marker for postoperative complications in high-risk patients undergoing major non-cardiac surgery (SPARSE). Surgery 2021, 171, 1619–1625. [Google Scholar] [CrossRef] [PubMed]
- Lomholt, A.F.; Christensen, I.J.; Høyer-Hansen, G.; Nielsen, H.J. Prognostic value of intact and cleaved forms of the urokinase plasminogen activator receptor in a retrospective study of 518 colorectal cancer patients. Acta. Oncol. 2010, 49, 805–811. [Google Scholar] [CrossRef] [PubMed]
- Henic, E.; Borgfeldt, C.; Christensen, I.J.; Casslén, B.; Høyer-Hansen, G. Cleaved forms of the urokinase plasminogen activator receptor in plasma have diagnostic potential and predict postoperative survival in patients with ovarian cancer. Clin. Cancer. Res. 2008, 14, 5785–5793. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Loosen, S.H.; Tacke, F.; Binnebosel, M.; Leyh, C.; Vucur, M.; Heitkamp, F.; Schoening, W.; Ulmer, T.F.; Alizai, P.H.; Trautwein, C.; et al. Serum levels of soluble urokinase plasminogen activator receptor (suPAR) predict outcome after resection of colorectal liver metastases. Oncotarget 2018, 9, 27027–27038. [Google Scholar] [CrossRef] [Green Version]
- Hodges, G.W.; Bang, C.N.; Eugen-Olsen, J.; Olsen, M.H.; Boman, K.; Ray, S.; Kesäniemi, A.Y.; Jeppesen, J.L.; Wachtell, K. SuPAR predicts postoperative complications and mortality in patients with asymptomatic aortic stenosis. Open. Heart. 2018, 5, e000743. [Google Scholar] [CrossRef] [PubMed]
- Morath, C.; Hayek, S.S.; Döhler, B.; Nusshag, C.; Sommerer, C.; Zeier, M.; Reiser, J.; Süsal, C. Soluble Urokinase Receptor and Mortality in Kidney Transplant Recipients. Transpl. Int. 2022, 35, 10071. [Google Scholar] [CrossRef] [PubMed]
- Schuettfort, V.M.; Pradere, B.; D’Andrea, D.; Grossmann, N.C.; Quhal, F.; Mostafaei, H.; Laukhtina, E.; Mori, K.; Rink, M.; Karakiewicz, P.I.; et al. Prognostic Impact of Preoperative Plasma Levels of Urokinase Plasminogen Activator Proteins on Disease Outcomes after Radical Cystectomy. J. Urol. 2021, 206, 1122–1131. [Google Scholar] [CrossRef] [PubMed]
- Rasmussen, S.R.; Nielsen, R.V.; Møgelvang, R.; Ostrowski, S.R.; Ravn, H.B. Prognostic value of suPAR and hsCRP on acute kidney injury after cardiac surgery. BMC Nephrol. 2021, 22, 120. [Google Scholar] [CrossRef] [PubMed]
- Lazarević, M.; Golubović, M.; Milić, D.; Stanojević, D.; Kostić, T.; Đorđević, M.; Marjanović, V.; Perić, V. Preoperative Levels of the Soluble Urokinase-Type Plasminogen Activator Receptor as Predictor for New Episodes of Atrial Fibrillation after Vascular Surgery. Vasc. Endovascular. Surg. 2021, 55, 461–466. [Google Scholar] [CrossRef] [PubMed]
- Schultz-Swarthfigure, C.T.; McCall, P.; Docking, R.; Galley, H.F.; Shelley, B. Can soluble urokinase plasminogen receptor predict outcomes after cardiac surgery? Interact. Cardiovasc. Thorac. Surg. 2021, 32, 236–243. [Google Scholar] [CrossRef] [PubMed]
- Laou, E.; Papagiannakis, N.; Tsiaka, A.; Tsapournioti, S.; Chatzikallinikidis, K.; Mantzaflaras, G.; Karadontas, I.; Eugen-Olsen, J.; Chalkias, A. Soluble urokinase receptor levels are not affected by the systemic inflammatory response to anesthesia and operative trauma. Eur. Surg. Res. 2022, in press. [CrossRef] [PubMed]
- Mekonnen, G.; Corban, M.T.; Hung, O.Y.; Eshtehardi, P.; Eapen, D.J.; Al-Kassem, H.; Rasoul-Arzrumly, E.; Gogas, B.D.; McDaniel, M.C.; Pielak, T.; et al. Plasma soluble urokinase-type plasminogen activator receptor level is independently associated with coronary microvascular function in patients with non-obstructive coronary artery disease. Atherosclerosis 2015, 239, 55–60. [Google Scholar] [CrossRef] [PubMed]
- Legány, N.; Toldi, G.; Distler, J.H.; Beyer, C.; Szalay, B.; Kovács, L.; Vásárhelyi, B.; Balog, A. Increased plasma soluble urokinase plasminogen activator receptor levels in systemic sclerosis: Possible association with microvascular abnormalities and extent of fibrosis. Clin. Chem. Lab. Med. 2015, 53, 1799–1805. [Google Scholar] [CrossRef] [PubMed]
- Chalkias, A.; Pavlopoulos, F.; Papageorgiou, E.; Tountas, C.; Anania, A.; Panteli, M.; Beloukas, A.; Xanthos, T. Development and Testing of a Novel Anaesthesia Induction/Ventilation Protocol for Patients with Cardiogenic Shock Complicating Acute Myocardial Infarction. Can. J. Cardiol. 2018, 34, 1048–1058. [Google Scholar] [CrossRef] [PubMed]
- Chalkias, A.; Xanthos, T.; Papageorgiou, E.; Anania, A.; Beloukas, A.; Pavlopoulos, F. Intraoperative initiation of a modified ARDSNet protocol increases survival of septic patients with severe acute respiratory distress syndrome. Heart. Lung. 2018, 47, 616–621. [Google Scholar] [CrossRef] [PubMed]
- Kertai, M.D.; White, W.D.; Gan, T.J. Cumulative duration of “triple low” state of low blood pressure, low bispectral index, and low minimum alveolar concentration of volatile anesthesia is not associated with increased mortality. Anesthesiology 2014, 121, 18–28. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Willingham, M.; Ben Abdallah, A.; Gradwohl, S.; Helsten, D.; Lin, N.; Villafranca, A.; Jacobsohn, E.; Avidan, M.; Kaiser, H. Association between intraoperative electroencephalographic suppression and postoperative mortality. Br. J. Anaesth. 2014, 113, 1001–1008. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Milstein, D.M.; Helmers, R.; Hackmann, S.; Belterman, C.N.; van Hulst, R.A.; de Lange, J. Sublingual microvascular perfusion is altered during normobaric and hyperbaric hyperoxia. Microvasc. Res. 2016, 105, 93–102. [Google Scholar] [CrossRef]
- Schwarte, L.A.; Schober, P.; Loer, S.A. Benefits and harms of increased inspiratory oxygen concentrations. Curr. Opin. Anaesthesiol. 2019, 32, 783–791. [Google Scholar] [CrossRef] [PubMed]
- Orbegozo Cortés, D.; Puflea, F.; Donadello, K.; Taccone, F.S.; Gottin, L.; Creteur, J.; Vincent, J.L.; De Backer, D. Normobaric hyperoxia alters the microcirculation in healthy volunteers. Microvasc. Res. 2015, 98, 23–28. [Google Scholar] [CrossRef] [PubMed]
- Alstrup, M.; Meyer, J.; Schultz, M.; Rasmussen, L.J.H.; Rasmussen, L.S.; Køber, L.; Forberg, J.L.; Eugen-Olsen, J.; Iversen, K. Soluble Urokinase Plasminogen Activator Receptor (suPAR) as an Added Predictor to Existing Preoperative Risk Assessments. World. J. Surg. 2019, 43, 780–790. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Massey, M.J.; Shapiro, N.I. A guide to human in vivo microcirculatory flow image analysis. Crit. Care 2016, 20, 35. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Massey, M.J.; Larochelle, E.; Najarro, G.; Karmacharla, A.; Arnold, R.; Trzeciak, S.; Angus, D.C.; Shapiro, N.I. The microcirculation image quality score: Development and preliminary evaluation of a proposed approach to grading quality of image acquisition for bedside videomicroscopy. J. Crit. Care 2013, 28, 913–917. [Google Scholar] [CrossRef] [PubMed]
- Dobbe, J.G.; Streekstra, G.J.; Atasever, B.; van Zijderveld, R.; Ince, C. Measurement of functional microcirculatory geometry and velocity distributions using automated image analysis. Med. Biol. Eng. Comput. 2008, 46, 659–670. [Google Scholar] [CrossRef] [Green Version]
- Ince, C.; Boerma, E.C.; Cecconi, M.; De Backer, D.; Shapiro, N.I.; Duranteau, J.; Pinsky, M.R.; Artigas, A.; Teboul, J.L.; Reiss, I.K.M.; et al. Cardiovascular Dynamics Section of the ESICM. Second consensus on the assessment of sublingual microcirculation in critically ill patients: Results from a task force of the European Society of Intensive Care Medicine. Intensive Care. Med. 2018, 44, 281–299. [Google Scholar] [CrossRef] [Green Version]
- Bruno, R.R.; Masyuk, M.; Muessig, J.M.; Binneboessel, S.; Bernhard, M.; Bäz, L.; Franz, M.; Kelm, M.; Jung, C. Sublingual microcirculation detects impaired perfusion in dehydrated older patients. Clin. Hemorheol. Microcirc. 2020, 75, 475–487. [Google Scholar] [CrossRef]
- Bruno, R.R.; Schemmelmann, M.; Wollborn, J.; Kelm, M.; Jung, C. Evaluation of a shorter algorithm in an automated analysis of sublingual microcirculation. Clin. Hemorheol. Microcirc. 2020, 76, 287–297. [Google Scholar] [CrossRef]
- Mirna, M.; Bimpong-Buta, N.Y.; Hoffmann, F.; Abusamrah, T.; Knost, T.; Sander, O.; Hew, Y.M.; Lichtenauer, M.; Muessig, J.M.; Bruno, R.R.; et al. Exposure to acute normobaric hypoxia results in adaptions of both the macro- and microcirculatory system. Sci. Rep. 2020, 10, 20938. [Google Scholar] [CrossRef]
- Chalkias, A.; Laou, E.; Mermiri, M.; Michou, A.; Ntalarizou, N.; Koutsona, S.; Chasiotis, G.; Garoufalis, G.; Agorogiannis, V.; Kyriakaki, A.; et al. Microcirculation-guided treatment improves tissue perfusion and hemodynamic coherence in surgical patients with septic shock. Eur. J. Trauma. Emerg. Surg. 2022, in press. [CrossRef]
- Bolliger, M.; Kroehnert, J.A.; Molineus, F.; Kandioler, D.; Schindl, M.; Riss, P. Experiences with the standardized classification of surgical complications (Clavien-Dindo) in general surgery patients. Eur. Surg. 2018, 50, 256–261. [Google Scholar] [CrossRef] [Green Version]
- Clavien, P.A.; Vetter, D.; Staiger, R.D.; Slankamenac, K.; Mehra, T.; Graf, R.; Puhan, M.A. The Comprehensive Complication Index (CCI®): Added Value and Clinical Perspectives 3 Years “Down the Line”. Ann. Surg. 2017, 265, 1045–1050. [Google Scholar] [CrossRef] [PubMed]
- Agha, R.; Abdall-Razak, A.; Crossley, E.; Dowlut, N.; Iosifidis, C.; Mathew, G.; STROCSS Group. STROCSS 2019 Guideline: Strengthening the reporting of cohort studies in surgery. Int. J. Surg. 2019, 72, 156–165. [Google Scholar] [CrossRef] [PubMed]
- Chalkias, A.; Papagiannakis, N.; Mavrovounis, G.; Kolonia, K.; Mermiri, M.; Pantazopoulos, I.; Laou, E.; Arnaoutoglou, E. Sublingual microcirculatory alterations during the immediate and early postoperative period: A systematic review and meta-analysis. Clin. Hemorheol. Microcirc. 2021, 80, 253–265. [Google Scholar] [CrossRef] [PubMed]
- Pietzner, M.; Kaul, A.; Henning, A.K.; Kastenmüller, G.; Artati, A.; Lerch, M.M.; Adamski, J.; Nauck, M.; Friedrich, N. Comprehensive metabolic profiling of chronic low-grade inflammation among generally healthy individuals. BMC Med. 2017, 15, 210. [Google Scholar] [CrossRef] [Green Version]
- Rasmussen, L.J.H.; Petersen, J.E.V.; Eugen-Olsen, J. Soluble Urokinase Plasminogen Activator Receptor (suPAR) as a Biomarker of Systemic Chronic Inflammation. Front. Immunol. 2021, 12, 780641. [Google Scholar] [CrossRef]
- Rasmussen, L.J.H.; Caspi, A.; Ambler, A.; Danese, A.; Elliott, M.; Eugen-Olsen, J.; Hariri, A.R.; Harrington, H.; Houts, R.; Poulton, R.; et al. Association Between Elevated suPAR, a New Biomarker of Inflammation, and Accelerated Aging. J. Gerontol. A Biol. Sci. Med. Sci. 2021, 76, 318–327. [Google Scholar] [CrossRef]
- Jhanji, S.; Lee, C.; Watson, D.; Hinds, C.; Pearse, R.M. Microvascular flow and tissue oxygenation after major abdominal surgery: Association with post-operative complications. Intensive Care. Med. 2009, 35, 671–677. [Google Scholar] [CrossRef]
- Magnin, M.; Foulon, É.; Lurier, T.; Allaouchiche, B.; Bonnet-Garin, J.M.; Junot, S. Evaluation of microcirculation by Sidestream Dark Field imaging: Impact of hemodynamic status on the occurrence of pressure artifacts—A pilot study. Microvasc. Res. 2020, 131, 104025. [Google Scholar] [CrossRef]
- Sapoznikov, A.; Gal, Y.; Evgy, Y.; Aftalion, M.; Katalan, S.; Sabo, T.; Kronman, C.; Falach, R. Intramuscular Exposure to a Lethal Dose of Ricin Toxin Leads to Endothelial Glycocalyx Shedding and Microvascular Flow Abnormality in Mice and Swine. Int. J. Mol. Sci. 2021, 22, 12345. [Google Scholar] [CrossRef]
- Magnin, M.; Bonnet-Garin, J.M.; Laurenza, C.; Didier, C.; Gavet, M.; Nectoux, A.; Allaouchiche, B.; Junot, S. Evaluation of pimobendan effect on sublingual microcirculation in an experimental pharmacology induced hypotension porcine model. Res. Vet. Sci. 2022, 148, 7–14. [Google Scholar] [CrossRef]
Age, years (mean ± SD) | 67.2 ± 12.5 | |
Sex (Male), n (%) | 68 (68%) | |
ASA physical status, n (%) | II | 17 (17%) |
III | 43 (43%) | |
IV | 40 (40%) | |
Type of surgery, n (%) | Endocrinological | 1 (1%) |
Gastrointestinal | 42 (42%) | |
Gastrointestinal/Gynecological | 1 (1%) | |
Gynecological | 5 (5%) | |
Thoracic | 1 (1%) | |
Urological | 16 (16%) | |
Vascular | 32 (32%) | |
Various | 2 (2%) | |
Medication | ||
Aspirin, n (%) | No | 74 (74%) |
Yes | 26 (26%) | |
Beta blocker, n (%) | No | 64 (64%) |
Yes | 36 (36%) | |
ACEi, n (%) | No | 86 (86%) |
Yes | 14 (14%) | |
Diuretic, n (%) | No | 78 (78%) |
Yes | 22 (22%) | |
Comorbidities | ||
Ischemic heart disease, n (%) | No | 78 (78%) |
Yes | 22 (22%) | |
Arterial hypertension, n (%) | No | 36 (36%) |
Yes | 64 (64%) | |
Hypercholesterolemia, n (%) | No | 51 (51%) |
Yes | 49 (49%) | |
Diabetes, n (%) | No | 86 (86%) |
Yes | 14 (14%) | |
Stroke, n (%) | No | 93 (93%) |
Yes | 7 (7%) | |
COPD, n (%) | No | 76 (76%) |
Yes | 24 (24%) | |
Asthma, n (%) | No | 98 (98%) |
Yes | 2 (2%) | |
Other, n (%) | No | 37 (37%) |
Yes | 63 (63%) | |
suPAR (ng mL−1), mean ± SD | 8.09 ± 3.69 |
Beta Coefficient * | Standard Error | p-Value | |
---|---|---|---|
De Backer score | −0.716 | 0.041 | <0.001 |
Consensus PPV | −2.490 | 0.159 | <0.001 |
Consensus PPV (small) | −2.835 | 0.1713 | <0.001 |
Preoperatively—30 min after Induction of General Anesthesia (Before Surgical Incision) | |||
Spearman’s Rho | Adjusted p-Value | ||
De Backer score | Modified Frailty Index | −0.156 | 0.12 |
Comprehensive Complication Index | −0.251 | 0.012 | |
Consensus PPV (%) | Modified Frailty Index | −0.102 | 0.315 |
Comprehensive Complication Index | −0.28 | 0.005 | |
Consensus PPV (small) (%) | Modified Frailty Index | −0.075 | 0.456 |
Comprehensive Complication Index | −0.277 | 0.005 | |
Postoperatively—before Emergence from Anesthesia | |||
Spearman’s Rho | Adjusted p-Value | ||
De Backer score | Modified Frailty Index | −0.184 | 0.067 |
Comprehensive Complication Index | −0.289 | 0.003 | |
Consensus PPV (%) | Modified Frailty Index | −0.221 | 0.027 |
Comprehensive Complication Index | −0.328 | 0.001 | |
Consensus PPV (small) (%) | Modified Frailty Index | −0.189 | 0.06 |
Comprehensive Complication Index | −0.327 | 0.001 |
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Chalkias, A.; Papagiannakis, N.; Saugel, B.; Flick, M.; Kolonia, K.; Angelopoulou, Z.; Ragias, D.; Papaspyrou, D.; Bouzia, A.; Ntalarizou, N.; et al. Association of Preoperative Basal Inflammatory State, Measured by Plasma suPAR Levels, with Intraoperative Sublingual Microvascular Perfusion in Patients Undergoing Major Non-Cardiac Surgery. J. Clin. Med. 2022, 11, 3326. https://doi.org/10.3390/jcm11123326
Chalkias A, Papagiannakis N, Saugel B, Flick M, Kolonia K, Angelopoulou Z, Ragias D, Papaspyrou D, Bouzia A, Ntalarizou N, et al. Association of Preoperative Basal Inflammatory State, Measured by Plasma suPAR Levels, with Intraoperative Sublingual Microvascular Perfusion in Patients Undergoing Major Non-Cardiac Surgery. Journal of Clinical Medicine. 2022; 11(12):3326. https://doi.org/10.3390/jcm11123326
Chicago/Turabian StyleChalkias, Athanasios, Nikolaos Papagiannakis, Bernd Saugel, Moritz Flick, Konstantina Kolonia, Zacharoula Angelopoulou, Dimitrios Ragias, Dimitra Papaspyrou, Aikaterini Bouzia, Nicoletta Ntalarizou, and et al. 2022. "Association of Preoperative Basal Inflammatory State, Measured by Plasma suPAR Levels, with Intraoperative Sublingual Microvascular Perfusion in Patients Undergoing Major Non-Cardiac Surgery" Journal of Clinical Medicine 11, no. 12: 3326. https://doi.org/10.3390/jcm11123326
APA StyleChalkias, A., Papagiannakis, N., Saugel, B., Flick, M., Kolonia, K., Angelopoulou, Z., Ragias, D., Papaspyrou, D., Bouzia, A., Ntalarizou, N., Stamoulis, K., Kyriakaki, A., Eugen-Olsen, J., Laou, E., & Arnaoutoglou, E. (2022). Association of Preoperative Basal Inflammatory State, Measured by Plasma suPAR Levels, with Intraoperative Sublingual Microvascular Perfusion in Patients Undergoing Major Non-Cardiac Surgery. Journal of Clinical Medicine, 11(12), 3326. https://doi.org/10.3390/jcm11123326