Next Article in Journal
A Story of PA/BSA and Biomarkers to Diagnose Pulmonary Hypertension in Patients with Severe Aortic Valve Stenosis—The Rise of IGF-BP2 and GDF-15
Previous Article in Journal
SCUBA Diving in Adult Congenital Heart Disease
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Increased Plasma Concentrations of Extracellular Vesicles Are Associated with Pro-Inflammatory and Pro-Thrombotic Characteristics of Left and Right Ventricle Mechanical Support Devices

by
Tomasz Urbanowicz
1,*,
Anna Olasińska-Wiśniewska
1,
Kajetan Grodecki
2,
Aleksandra Gąsecka
2,
Krzysztof J. Filipiak
3,
Maciej Gawlikowski
4,
Łukasz Mucha
5 and
Marek Jemielity
1
1
Cardiac Surgery and Transplantology Department, Poznan University of Medical Sciences, 61-848 Poznan, Poland
2
1st Department of Cardiology, Medical University of Warsaw, 02-097 Warsaw, Poland
3
Institute of Clinical Science, Maria Sklodowska-Curie Medical Academy, 00-136 Warsaw, Poland
4
Faculty of Biomedical Engineering, Silesian University of Technology, 44-100 Gliwice, Poland
5
F.R.K. Intra-Cordis Professor Zbigniew Religa Foundation of Cardiac Surgery Development, 41-800 Zabrze, Poland
*
Author to whom correspondence should be addressed.
J. Cardiovasc. Dev. Dis. 2023, 10(1), 21; https://doi.org/10.3390/jcdd10010021
Submission received: 21 November 2022 / Revised: 31 December 2022 / Accepted: 4 January 2023 / Published: 5 January 2023
(This article belongs to the Section Electrophysiology and Cardiovascular Physiology)

Abstract

:
Mechanical circulatory support (MCS) allows for functional left and right heart ventricle replacement. MCS induces a systemic inflammatory reaction and prothrombotic state leading to an increased risk of thrombus formation. The extracellular vesicles (EVs) are nanoparticles released from active/injured cells characterized by prothrombotic properties. Simple inflammatory parameters from whole blood count analysis have established a clinical role in everyday practice to describe immune-inflammatory activation. We hypothesized that increased plasma concentrations of EVs might be associated with the proinflammatory and pro-thrombotic characteristics of left ventricle assist device (LVAD) and right ventricle assist device (RVAD) devices. We presented a pilot study showing the concentration of peripheral blood serum, right and left ventricle mechanical assist device extracellular concentration in relation to thrombotic complication in patients treated with a biventricular pulsatile assist device (BIVAD). The observation was based on 12 replacements of pulsatile pumps during 175 days of observation. The proinflammatory characteristics of LVAD were noted. The proinflammatory and procoagulant activation by RVAD was observed. The results may provide possible explanations for the worse results of right-sided mechanical supports observed in clinical practice.

1. Introduction

A continuous remarkable development in mechanical circulatory support (MCS) has become an interesting alternative to heart transplantation, achieving satisfactory long-term results [1,2]. The superiority of the centrifugal pump in comparison to organ transplantation was postulated in a recent trial [3] since the centrifugal pump presents satisfactory results with a relatively low risk for complications [4].
MCS can be configurated to support the left, right, or both ventricles, giving a chance for both physiological pumps’ function replacement. Currently, the HeartMate3 (Abbott, Chicago, IL, USA) as a centrifugal pump is routinely applied to support the left heart chamber [5]. The pulsatile paracorporeal pumps, though not routinely applied, are available, including Excor (Berlin Heart Company, Berlin, Germany) [6] for pediatric patients or POLVAD (FRK IntraCordis, Zabrze, Polska) for adults [7], and allow for long-term support in contrast to results obtained from the combined two left ventricle assist devices [8].
Pulsatile pneumatic pumps presented optimal results in children [9] including pulmonary hypertension reversal and satisfactory post-transplantation survival. The comparable results between the use of axial pumps and paracorporeal pulsatiles were presented in adults [10], though the increased risk for thrombus formation required frequent (every 30 days) pumps exchange [11] and in-hospital stays are of the greatest concern.
MCS induces systemic inflammatory reaction and prothrombotic state [12] leading to an increased risk for thrombus formation [13]. Inflammatory activation may be measured by simple indexes obtained from the whole blood count, such as neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), or indexes, such as systemic inflammatory index (SII), aggregate index of systemic inflammation (AISI) and systemic inflammatory response index (SIRI) [14,15,16]. However, these indicated markers were previously evaluated and did not allow one to identify patients treated with MCS who are at high risk of thrombotic complications. Hence, new biomarkers are needed to improve risk stratification in this challenging patient population [17].
Extracellular vesicles (EVs) are heterogenous nanoparticles released from cells to body fluids, composed of cellular membrane fragments and cytoplasmic material [18]. They contain phospholipids, proteins, and non-coding fragments of ribonucleic acid (RNA) and expose surface antigens such as CD45+ [19], CD61+ [20], CD235+ [21] derived from the parent cells, which allow one to identify their cellular origin [22,23]. EVs are released by erythrocytes, endothelial cells, leucocytes, and platelets [24] as fragments of a submicron size following activation or apoptosis. EVs contribute to intercellular communication, inflammation, and coagulation processes [25,26,27,28,29,30,31,32]. The increased concentrations of plasma EVs were postulated to reflect cells’ activations and to be associated with an increased risk of cardiovascular complications, including acute myocardial infarction or stroke [33]. We hypothesized that increased plasma concentrations of EVs might be associated with the proinflammatory and pro-thrombotic characteristics of left ventricle assist device (LVAD) and right ventricle assist device (RVAD).

The Aim of the Study

The aim of the study was to analyze plasma concentration of EVs from leukocytes (CD45+), platelets (CD61+) and erythrocytes (CD235+) in the peripheral blood, LVAD, and RVAD chambers and to evaluate EVs correlation with (i) peripheral blood inflammatory parameters and indices (C-reactive protein (CRP), procalcitonin, large unstained cells (LUC), NLR, MLR, PLR, SII, AISI, SIRI) and (ii) thrombotic debris detected in RVADs and LVADs.

2. Materials and Methods

The study was performed on 12 pumps (POLVAD-MED, FRK Intra-cordis, Poland) analysis in one patient awaiting heart transplantation. The 42-years-old patient with dilated cardiomyopathy, with the end-stage heart failure (class IV according to New York Heart Association Functional Classification), and a history of aortic valve replacement with mechanical prosthesis three years before, was referred for qualification to heart transplantation. The imaging examinations (echocardiography, coronary angiography and computed tomography) revealed a severely dilated left ventricle (93 mm) with reduced ejection fraction (15%), a proper function of mechanical aortic prosthesis, and no atherosclerotic changes in coronary arteries. Despite aggressive pharmacotherapy, he developed cardiac arrest and after successful resuscitation, extracorporeal membrane oxygenation (ECMO) therapy was implemented, followed by BIVAD by implantation of POLVAD after 7 days. The patient was on an urgent heart transplant list; however, he waited for an organ donor for 175 days. During the whole hospitalization, he required 12 pump exchanges due to fibrotic debris collections which were observed during daily checkups. The typical heart failure pharmacotherapy was used, as well as antiplatelet therapy (aspirin, 75 mg daily) combined with oral anticoagulation (reference international normalized ratio (INR) 2.0–3.0). The aim of the study was to analyze the relation between inflammatory markers as extracellular vesicles and the risk of clots formation. The study was approved by the local Institutional Ethics Committee (approval number 695/20).
In patients with POLVAD, the pumps’ replacement during the POLVAD function was related to visual signs of thrombus formation on paracorporeal chambers observed during daily controls [11].
During each procedure of deplantation, blood samples were taken simultaneously from both chambers and peripheral blood samples were collected and processed according to the current guidelines for studying EVs [34]. The peripheral blood and intra-pump EVS concentration were measured during each deplantation. The following day, the peripheral blood for EVs concentration was measured again to distinguish the EVs concentration related to pumps by themselves and by the clots gathering in the chambers.

2.1. EVs Examination

Briefly, blood samples for EVs concentration were collected in 10 mL 0.109 mol/L citrated plastic tubes (S-Monovette, Sarstedt, Hildesheim, Germany) and 4.9 mL K3-EDTA plastic probes (S-Monovette, Sarstedt, Hildesheim, Germany). Within a maximum of 15 min from blood collection, platelet-depleted plasma was prepared by double centrifugation (Centrifuge MPW-56, MPW Med. Instruments, Warsaw, Poland). The centrifugation parameters were: 2500× g, 15 min, 20 °C, acceleration speed 1, no brake. The first centrifugation step was done with 10 mL whole blood collection tubes. Supernatant was collected 10 mm above the buffy coat. The second centrifugation step was done with 3.5 mL plasma in 15 mL polypropylene centrifuge tubes (Greiner Bio-One B.V). Supernatant (platelet-depleted plasma) was collected 5 mm above the buffy coat, transferred into 5 mL polypropylene centrifuge tubes (Greiner Bio-One B.V., Vilvoorde, Belgium), mixed by pipetting, transferred to 1.5 mL low-protein binding Eppendorfs (Thermo Fisher Scientific, Waltham, MA, USA), and stored in −80 °C until analyzed.
Concentrations of EVs were measured by flow cytometry (A60-Micro, Apogee Flow Systems, Hertfordshire, UK). We diluted samples 2-fold to 1500-fold in in Dulbecco phosphate-buffered saline (DPBS) to achieve a count rate of less than 3000 events/s to prevent swarm detection [35]. Diluted samples were measured during 120 s at a flow rate of 3.01 μL per min. The trigger threshold was set at 14 arbitrary units of the side scatter detector, which corresponds to a side scattering cross section of 10 nm2. The reported concentrations describe the number of particles (a) that exceed the side scatter threshold, (b) have a diameter >200 nm as determined by Flow-SR [36], (c) have a refractive index <1.42 to exclude positively labelled chylomicrons [37], and (d) that are positive at the fluorescence detector(s) corresponding to the used label(s), per mL of platelet-depleted plasma. We measured concentrations of EVs from erythrocytes (CD235a+), leukocytes (CD45+), and platelets (CD61+). To ensure the reproducibility of our EV flow cytometry experiments, we applied the new reporting framework for the standardized reporting of EV flow cytometry experiments (MIFlowCyt-EV) [38], calibrated all detectors, determined the EV diameter and refractive index by the flow cytometry scatter ratio (Flow-SR) [36], and applied custom-built software to fully automate data calibration and processing.

2.2. Inflammatory Biomarkers

Peripheral blood samples were collected during each deplantation and 24 h after the procedure to assess standard inflammatory parameters and indices, which were measured with a routine hematology analyzer (Sysmex Europe GmbH, Norderstedt, Germany). C-reactive protein (CRP) and procalcitonin levels were measured by a high-sensitive enzyme-linked immunosorbent assay technique (ELISA) according to the manufacturer’s instructions. The indices, including NLR, MLR, PLR, SIRI, AISI, SII, were calculated according to the usual formulas as presented in previous reports [39].

2.3. Statistical Analysis

Data were tested for normality using the Shapiro–Wilk test. Continuous variables were expressed as mean (standard deviation (SD)) or median (interquartile range [IQR]), as appropriate. Categorical variables were presented as numbers (percentage). Unpaired continuous variables were compared using t-test or nonparametric Mann–Whitney test, as appropriate. Paired variables (pre- versus post-deplantation) were compared with the Wilcoxon signed-rank test. For multiple groups, one-way ANOVA was used with post hoc Bonferroni correction. The correlation between two continuous variables was measured with the bivariate Pearson correlation. All reported probability values were 2-tailed. A P value less than 0.05 was considered significant. Data were processed using the SPSS software, version 23 (IBM SPSS Statistics, New York, NY, USA).

3. Results

3.1. Extracellular Vesicles

The EVs concentration in peripheral blood (1.38 (1.35–1.51) × 109/mL) in LVAD (2.77 (1.25–4.24) × 109/mL) and in RVAD (3.88 (2.41–4.24) × 109/mL) were noted. The results of EVs-CD45 concentration were (3.2 (2.45–5.3) × 107/mL vs. 3.12 (2.67–4.42) × 107/mL vs. 5.12 (4.31–5.32) × 107/mL in peripheral blood, LVAD, and RVAD, respectively. The EVs-CD61 peripheral blood, LVAD, and RVAD concentration was measured and presented the following concentrations: 8.35 (8.15–14.23) × 107/mL vs. 7.68 (7.21–8.41) × 107/mL vs. 9.41 (8.28–14.71) × 107/mL, respectively. The EVs-CD235 concentrations were noticed in peripheral blood with mean values of 1.27 (1.24–2.68) × 107/mL, in an LVAD concentration of 1.41 (1.31–2.79) × 107/mL, and in an RVAD concentration of 2.04 (1.49–3.28) × 107/mL, respectively. The graphical comparison of EVs, CD45, CD61, and CD235 concentrations in peripheral blood, LVAD, and RVAD represent Figure 1A–D.

3.2. Whole Blood Count and Indices Analysis

The mean values of peripheral whole blood count and inflammatory markers measured during deplantation and one day (24 h) after the procedure are presented in Table 1.

Pumps Analysis

During a total of 175 days of pump function, 29 thrombi were found in the LVAD, including 6 large and 23 small thrombi located in the inflow tract (n = 7) and the outflow tract (n = 10). In the RVAD, 5 large and 14 small thrombi were detected, including 5 located in the inflow tract and 6 in the outflow tract. Figure 2A–C present the representative images of the thrombotic material. The mean (SD) time for pump function was 25 (9) days.

3.3. Left Ventricle Assist Device (LVAD)

The correlation between obtained data regarding EVs detected in the left chamber was performed and presented in Table 2.
The eVs including (separate measurements of CD61, CD45, CD235) concentrations in RVAD and LVAD compared to peripheral blood eVs concentration during every system deplantation are presented in Figure 3.

3.4. Right Ventricle Assist Device (RVAD)

The results of correlation between EVs concentrations in the RVAD and laboratory data are presented in Table 3.

4. Discussion

The results of our study present the first, to our best knowledge, results of EVs concentration in mechanical circulatory support and their relation to inflammatory and thrombotic indices. Left-sided mechanical support proinflammatory characteristics were noted in our analysis as reflected by platelet EVs (CD61+) and erythrocytes EVs (CD235+) concentrations, which correlated with peripheral blood MLR. The right-sided mechanical pumps (RVAD) had proinflammatory and procoagulant activation, as reflected by leukocyte EVs (CD45+) and platelet EVs (CD61+) concentrations and peripheral blood NLR and SII. The proinflammatory and prothrombotic results in RVADs may explain the worse clinical results in RVADs [40] also after heart transplantation [41].
Extracellular vesicles (EVs) are involved in atherosclerosis, thrombosis, and inflammation. We evaluated EVs exposed from red cells (CD235+), platelets (CD61+), lymphocytes (CD45+), a total concentration of EVs above the detection threshold of our flow cytometer, and showed their proinflammatory and prothrombotic significance during biventricular mechanical support use.
Our analysis results indicate that inflammatory activation in the left-sided mechanical system is triggered by red cells and platelets. The CD235+/CD41− erythrocyte-derived antigens concentrations are related to inflammatory markers procalcitonin and MLR. The CD235+ antigens belong to red cell fragments of the submicron size that can be regarded as a prothrombotic marker [42].
The increased levels of procalcitonin and MLR were [43,44] obtained from left-sided MCS [45,46]. Procalcitonin is a marker for sepsis but has a limited sensitivity since its secretion was also observed in non-infectious states [47] and was suggested as a prognostic factor of poor prognosis in acute coronary syndromes [48]. Its increased levels were proposed, by Xiong et al., as a risk biomarker for thrombotic complications following surgery [49]. Monocyte to lymphocyte ratio (MLR) is a simple index that is mainly related to inflammatory activation, however increased thrombotic risk was also postulated [50,51].
In our study, the relation was noted between LUC and platelet CD61 in left-sided mechanical support analysis. The LUC are large unstained peroxidase negative cells that reflect to activated lymphocytes, monocytes, and lymphoblasts [52]. Their increase was observed in different clinical situations related to acute immune activation [53,54]. CD61 (platelet glycoprotein IIIa) plays a significant role in aggregation. CD61 is a protein that indicate platelets secretion due to activation secondary to the procoagulant surface presented in the Reddel et al. study [55]. The complex GP IIb-IIIa binds to fibronectin, fibrinogen, and to vitronectin and von Willebrand factor [56]. CD61 was related to microparticles released as the result more of activation than of apoptosis by Vasina et al. [57].
Right sided mechanical circulatory support stimulates pro-thrombotic action by CD61 that plays a crucial role in platelets aggregation [58]. Our finding indicates the neutrophil to lymphocyte ratio (NLR) and systemic inflammatory index (SII) as two inflammatory indices related to EVs detected in RVAD chambers. The NLR was presented as an ominous prognostic marker for inflammatory activation in previous reports [59,60,61]. It can be regarded as a novel prospective marker related to ongoing antagonism between adaptive and innate immunity [62]. The relation between RVAD and SII indicate activation of three components: neutrophils, platelets, and lymphocytes [63]. The CD45 as a marker for lymphocytes activation by signal transduction [64] was related to RVAD in our study, emphasizing the significance for inflammatory activation. CD45+ lymphocyte-derived EVs play a significant role in vascular function. They are characterized by potential paracrine function [65]. The RVAD chamber content revealed significance for EVs. Based on our results, we suggest proinflammatory and pro-thrombotic characteristics of RVAD.
Our results indicate the relation between platelets activation in RVAD expressed by CD61+ and its peripheral response by extracellular vesicles (EVs) serum concentration. EVs were revealed to transfer functional receptors as triggering platelets antigen CD61, promoting target cells proliferation and adhesion [66].
After left -sided mechanical support (LVAD) implantation, the decrease of circulating EVs was presented in follow-up irrespectively to disease etiology or gender [67], suggesting a potential improvement of endothelial function. A Roka-Moiia et al. study [68] presented the platelets dysfunction as related to EVs shear stress generation in mechanical support. Radley et al. in their review postulated leukocytes activation as a significant contribution to thrombus formation in mechanical support [69]. The proinflammatory and prothrombogenic EVs are released by leukocytes after foreign surfaces contact and shear stress. We noticed differences in erythrocytes, leucocytes, and platelet activation related to mechanical support location (RVAD vs. LVAD). Moreover, we found a relation with inflammatory activation presented by MLR, NLR, and SII indexes.

Study Limitation

Patients with heart failure are extremely different in origin and advancement of disease, treatment regiments and pathophysiological response to pharmacotherapy. Indeed, this observation led us to evaluate changes in EVs in one particular patient, in whom the thrombotic and inflammatory milieu would not result from patient-to-patient differences but from disease and response to therapy. We avoided the risk of discrepancies between patients in terms of different hematological and inflammatory conditions in course of mechanical support. Moreover, our observations show thrombotic phenomena related to inflammatory activation which occur in BIVAD therapy and may be assigned to this population of patients.
We are, however, aware about possible limitations and difficulties in applying the conclusions of this patient study to the treatment of others. Therefore, we believe that larger studies are necessary to confirm our assumptions in different types of heart failure and transfer our results into therapeutic applications.
Despite the fact that the pulsatile pneumatic paracorporeal pumps are considered outdated due to centrifugal incorporable systems, this type of mechanical support allows satisfactory maintenance of both ventricles.

5. Conclusions

The proinflammatory characteristics of LVAD was presented based on CD235 as compared to peripheral blood MLR. The proinflammatory and procoagulant activation by RVAD were revealed based on CD45 and peripheral blood NLR, SII, SIRI, indicating an increased risk of thrombus formation. The results may provide the possible explanations of the worst results of right-sided mechanical supports observed in clinical practice. We are aware that these preliminary patient study results may be individual and should be confirmed in the analysis of larger population of heart failure patients.

Author Contributions

Conceptualization, T.U., A.O.-W. and A.G.; methodology, A.G.; software, M.G. and Ł.M.; validation, K.G. and A.G.; formal analysis, K.G.; investigation, T.U., A.O.-W. and A.G.; resources, A.G., M.G. and Ł.M.; data curation, T.U., A.G. and A.O.-W.; writing—original draft preparation, T.U.; writing—review and editing, A.O.-W., A.G., K.J.F. and M.J.; visualization, T.U.; supervision, M.J.; project administration, M.J.; funding acquisition, K.J.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Poznan University of Medical Sciences in Poznan, Poland Ethics Committee (protocol code 695/20, 4 November 2020 date of approval).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data will be available for 3 years following publication via contacting the corresponding author (tomasz.urbanowicz@skpp.edu.pl) after reasonable requirements.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Mehra, M.R.; Cleveland, J.C., Jr.; Uriel, N.; Cowger, J.A.; Hall, S.; Horstmanshof, D.; Naka, Y.; Salerno, C.T.; Chuang, J.; Williams, C.; et al. Primary results of long-term outcomes in the MOMENTUM 3 pivotal trial and continued access protocol study phase: A study of 2200 HeartMate 3 left ventricular assist device implants. Eur. J. Heart Fail. 2021, 23, 1392–1400. [Google Scholar] [CrossRef]
  2. Vieira, J.L.; Ventura, H.O.; Mehra, M.R. Mechanical circulatory support devices in advanced heart failure: 2020 and beyond. Prog. Cardiovasc. Dis. 2020, 63, 630–639. [Google Scholar] [CrossRef] [PubMed]
  3. Pettit, S.J. HeartMate 3: Real-world performance matches pivotal trial. Eur. Heart J. 2020, 41, 3810–3812. [Google Scholar] [CrossRef]
  4. Florisson, D.S.; Conte, S.M.; De Bono, J.A.; Newcomb, A.E. Do patients with the centrifugal flow HeartMate 3 or HeartWare left ventricular assist device have better outcomes compared to those with axial flow HeartMate II? Interact. Cardiovasc. Thorac.Surg. 2019, 29, 844–851. [Google Scholar] [CrossRef] [PubMed]
  5. Schmitto, J.D.; Mariani, S.; Li, T.; Dogan, G.; Hanke, J.S.; Bara, C.; Pya, Y.; Zimpfer, D.; Garbade, J.; Rao, V.; et al. Five-year outcomes of patients supported with HeartMate 3: A single-centre experience. Eur. J. Cardiothorac. Surg. 2021, 59, 1155–1163. [Google Scholar] [CrossRef]
  6. Hetzer, R.; Kaufmann, F.; Delmo Walter, E.M. Paediatric mechanical circulatory support with Berlin Heart EXCOR: Development and outcome of a 23-year experience. Eur. J. Cardiothorac. Surg. 2016, 50, 203–210. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Urbanowicz, T.K.; Baszyńska-Wachowiak, H.; Olasińska-Wiśniewska, A.; Misterski, M.; Stefaniak, S.; Ligowski, M.; Jemielity, M. Long-term biventricular circulatory support with POLVAD-MEV paracorporeal pulsatile pumps. Single-centre experience. Kardiochir. Torakochirurgia Pol. 2020, 17, 101–104. [Google Scholar] [CrossRef] [PubMed]
  8. Lavee, J.; Mulzer, J.; Krabatsch, T.; Marasco, S.; McGiffin, D.; Garbade, J.; Schmitto, J.; Zimpfer, D.; Potapov, E.V. An international multicenter experience of biventricular support with HeartMate 3 ventricular assist systems. J. Heart Lung Transplant. 2018, 37, 1399–1402. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Amodeo, A.; Brancaccio, G.; Michielon, G.; Filippelli, S.; Ricci, Z.; Morelli, S.; Gagliardi, M.G.; Iacobelli, R.; Pongiglione, G.; Di Donato, R.M. Pneumatic pulsatile ventricular assist device as a bridge to heart transplantation in pediatric patients. Artif. Organs 2010, 34, 1017–1022. [Google Scholar] [CrossRef]
  10. Nadziakiewicz, P.; Pacholewicz, J.; Zakliczynski, M.; Niklewski, T.; Borkowski, J.; Hrapkowicz, T.; Zembala, M. Comparison of Mechanical Circulatory Support by the Use of Pulsatile Left Ventricular Assist Devices Polvad MEV and Continuous Flow Heart Ware and Heart Mate II in a Single-Center Experience. Transplant. Proc. 2016, 48, 1770–1774. [Google Scholar] [CrossRef]
  11. Urbanowicz, T.; Olasińska-Wiśniewska, A.; Michalak, M.; Bociański, M.; Krawczyk, D.; Straburzyńska-Migaj, E.; Wachowiak-Baszyńska, H.; Jemielity, M. Risk of Thrombus Formation in Patients on Mechanical Circulatory Support with POLVAD-MEV. Ann. Transplant. 2021, 26, e926555–e926563. [Google Scholar] [CrossRef]
  12. Millar, J.E.; Fanning, J.P.; McDonald, C.I.; McAuley, D.F.; Fraser, J.F. The inflammatory response to extracorporeal membrane oxygenation (ECMO): A review of the pathophysiology. Crit. Care 2016, 20, 387–397. [Google Scholar] [CrossRef] [Green Version]
  13. Kounis, N.G.; Soufras, G.D.; Davlouros, P.; Tsigkas, G.; Hahalis, G. Thrombus Formation Patterns in HeartMate II Continuous-Flow Left Ventricular Assist Devices: A Multifactorial Phenomenon Involving Kounis Syndrome? ASAIO J. 2014, 60, 369–371. [Google Scholar] [CrossRef]
  14. Szymanska, P.; Rozalski, M.; Wilczynski, M.; Golanski, J. Systemic immune-inflammation index (SII) and neutrophil to lymphocyte ratio (NLR) are useful markers for assessing effects of anti-inflammatory diet in patients before coronary artery bypass grafting. Rocz. Panstw. Zakl. Hig. 2021, 72, 327–335. [Google Scholar] [CrossRef]
  15. Urbanowicz, T.; Michalak, M.; Gąsecka, A.; Perek, B.; Rodzki, M.; Bociański, M.; Straburzyńska-Migaj, E.; Jemielity, M. Postoperative Neutrophil to Lymphocyte Ratio as an Overall Mortality Midterm Prognostic Factor following OPCAB Procedures. Clin. Pract. 2021, 11, 587–597. [Google Scholar] [CrossRef]
  16. Urbanowicz, T.; Michalak, M.; Olasińska-Wiśniewska, A.; Rodzki, M.; Witkowska, A.; Gąsecka, A.; Buczkowski, P.; Perek, B.; Jemielity, M. Neutrophil Counts, Neutrophil-to-Lymphocyte Ratio, and Systemic Inflammatory Response Index (SIRI) Predict Mortality after Off-Pump Coronary Artery Bypass Surgery. Cells 2022, 11, 1124. [Google Scholar] [CrossRef] [PubMed]
  17. Kalogeropoulos, A.P.; Georgiopoulou, V.V.; Butler, J. Clinical adoption of prognostic biomarkers: The case for heart failure. Prog. Cardiovasc. Dis. 2012, 55, 3–13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Burger, D.; Touyz, R.M. Cellular biomarkers of endothelial health: Microparticles, endothelial progenitor cells, and circulating endothelial cells. J. Am. Soc. Hypertens. 2012, 6, 85–99. [Google Scholar] [CrossRef] [PubMed]
  19. Ahmad, S.F.; Ansari, M.A.; Nadeem, A.; Bakheet, S.A.; Al-Ayadhi, L.Y.; Alasmari, A.F.; Alanazi, M.M.; Al-Mazroua, H.A.; Attia, S.M. Involvement of CD45 cells in the development of autism spectrum disorder through dysregulation of granulocyte-macrophage colony-stimulating factor, key inflammatory cytokines, and transcription factors. Int. Immunopharmacol. 2020, 83, 106466–106571. [Google Scholar] [CrossRef] [PubMed]
  20. Jurado-Escobar, R.; Doña, I.; Bogas-Herrera, G.; Pérez-Sánchez, N.; Salas, M.; Laguna, J.J.; Muñoz-Cano, R.; Mayorga, C.; Torres, M.J.; Cornejo-García, J.A. Platelet-Adherent Leukocytes Associated with Cutaneous Cross-Reactive Hypersensitivity to Nonsteroidal Anti-Inflammatory Drugs. Front. Pharmacol. 2020, 11, 594427–594437. [Google Scholar] [CrossRef]
  21. Kent, M.W.; Kelher, M.R.; West, F.B.; Silliman, C.C. The pro-inflammatory potential of microparticles in red blood cell units. Transfus. Med. 2014, 24, 176–181. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Błażejowska, E.; Urbanowicz, T.; Gąsecka, A.; Olasińska-Wiśniewska, A.; Jaguszewski, M.J.; Targoński, R.; Szarpak, Ł.; Filipiak, K.J.; Perek, B.; Jemielity, M. Diagnostic and Prognostic Value of miRNAs after Coronary Artery Bypass Grafting: A Review. Biology 2021, 10, 1350. [Google Scholar] [CrossRef] [PubMed]
  23. Hu, Q.; Lyon, C.J.; Fletcher, J.K.; Tang, W.; Wan, M.; Hu, T.Y. Extracellular vesicle activities regulating macrophage- and tissue-mediated injury and repair responses. Acta Pharm. Sin. B 2021, 11, 1493–1512. [Google Scholar] [CrossRef]
  24. Van Der Pol, E.; Böing, A.N.; Harrison, P.; Sturk, A.; Nieuwland, R. Classification, Functions, and Clinical Relevance of Extracellular Vesicles. Pharmacol. Rev. 2012, 64, 676–705. [Google Scholar] [CrossRef] [Green Version]
  25. van der Pol, E.; Böing, A.N.; Gool, E.L.; Nieuwland, R. Recent developments in the nomenclature, presence, isolation, detection and clinical impact of extracellular vesicles. J. Thromb. Haemost. 2016, 14, 48–56. [Google Scholar] [CrossRef] [Green Version]
  26. Dignat-George, F.; Boulanger, C.M. The many faces of endothelial microparticles. Arterioscler. Thromb. Vasc. Biol. 2022, 31, 27–33. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Yuana, Y.; Sturk, A.; Nieuwland, R. Extracellular vesicles in physiological and pathological conditions. Blood Rev. 2013, 27, 31–39. [Google Scholar] [CrossRef] [Green Version]
  28. Buzas, E.I.; György, B.; Nagy, G.; Falus, A.; Gay, S. Emerging role of extracellular vesicles in inflammatory diseases. Nat. Rev. Rheumatol. 2014, 10, 356–364. [Google Scholar] [CrossRef]
  29. Dey-Hazra, E.; Hertel, B.; Kirsch, T.; Woywodt, A.; Lovric, S.; Haller, H.; Haubitz, M.; Erdbruegger, U. Detection of circulating microparticles by flow cytometry: Influence of centrifugation, filtration of buffer, and freezing. Vasc. Health Risk Manag. 2010, 6, 1125–1133. [Google Scholar] [PubMed] [Green Version]
  30. Morel, O.; Morel, N.; Jesel, L.; Freyssinet, J.M.; Toti, F. Microparticles: A critical component in the nexus between inflammation, immunity, and thrombosis. Semin. Immunopathol. 2011, 33, 469–486. [Google Scholar] [CrossRef] [PubMed]
  31. Sadallah, S.; Eken, C.; Schifferli, J.A. Erythrocyte-derived ectosomes have immunosuppressive properties. J. Leukoc. Biol. 2008, 84, 1316–1325. [Google Scholar] [CrossRef] [PubMed]
  32. Kondratov, K.; Nikitin, Y.; Fedorov, A.; Kostareva, A.; Mikhailovskii, V.; Isakov, D.; Ivanov, A.; Golovkin, A. Heterogeneity of the nucleic acid repertoire of plasma extracellular vesicles demonstrated using high-sensitivity fluorescence-activated sorting. J. Extracell. Vesicles 2020, 9, 1743139–1743156. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Amabile, N.; Cheng, S.; Renard, J.M.; Larson, M.G.; Ghorbani, A.; McCabe, E.; Griffin, G.; Guerin, C.; Ho, J.E.; Shaw, S.Y.; et al. Association of circulating endothelial microparticles with cardiometabolic risk factors in the Framingham Heart Study. Eur. Heart J. 2014, 42, 2972–2979. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Coumans, F.A.W.; Brisson, A.R.; Buzas, E.I.; Dignat-George, F.; Drees, E.E.E.; El-Andaloussi, S.; Emanueli, C.; Gasecka, A.; Hendrix, A.; Hill, A.F.; et al. Methodological Guidelines to Study Extracellular Vesicles. Circ. Res. 2017, 120, 1632–1648. [Google Scholar] [CrossRef]
  35. van der Pol, E.; Van Gemert, M.J.C.; Sturk, A.; Nieuwland, R.; Van Leeuwen, T.G.; Nieuwl; Van Leeuwen, T.G. Single vs. swarm detection of microparticles and exosomes by flow cytometry. J. Thromb. Haemost. 2012, 10, 919–930. [Google Scholar] [CrossRef]
  36. van der Pol, E.; de Rond, L.; Coumans, F.A.W.; Gool, E.L.; Böing, A.N.; Sturk, A.; Nieuwland, R.; van Leeuwen, T.G. Absolute sizing and label-free identification of extracellular vesicles by flow cytometry. Nanomedicine 2018, 14, 801–810. [Google Scholar] [CrossRef] [PubMed]
  37. de Rond, L.; Libregts, S.F.M.W.; Rikkert, L.G.; Hau, C.M.; van der Pol, E.; Nieuwland, R.; van Leeuwen, T.G.; Coumans, F.A.W. Refractive index to evaluate staining specificity of extracellular vesicles by flow cytometry. J. Extracell. Vesicles 2019, 8, 1643671–1643680. [Google Scholar] [CrossRef] [Green Version]
  38. Welsh, J.A.; Van Der Pol, E.; Arkesteijn, G.J.A.; Bremer, M.; Brisson, A.; Coumans, F.; Dignat-George, F.; Duggan, E.; Ghiran, I.; Giebel, B.; et al. MIFlowCyt-EV: A framework for standardized reporting of extracellular vesicle flow cytometry experiments. J. Extracell. Vesicles 2020, 9, 1713526. [Google Scholar] [CrossRef] [PubMed]
  39. Urbanowicz, T.; Olasińska-Wiśniewska, A.; Michalak, M.; Rodzki, M.; Witkowska, A.; Straburzyńska-Migaj, E.; Perek, B.; Jemielity, M. The Prognostic Significance of Neutrophil to Lymphocyte Ratio (NLR), Monocyte to Lymphocyte Ratio (MLR) and Platelet to Lymphocyte Ratio (PLR) on Long-Term Survival in Off-Pump Coronary Artery Bypass Grafting (OPCAB) Procedures. Biology 2021, 11, 34. [Google Scholar] [CrossRef]
  40. Vierecke, J.; Gahl, B.; de By, T.; Antretter, H.; Beyersdorf, F.; Caliskan, K.; Krachak, V.; Loforte, F.; Potapov, E.; Schoenrath, F.; et al. Results of primary biventricular support: An analysis of data from the EUROMACS registry. Eur. J. Cardiothorac. Surg. 2019, 56, 1037–1045. [Google Scholar] [CrossRef]
  41. Taghavi, S.; Jayarajan, S.N.; Komaroff, E.; Mangi, A.A. Right ventricular assist device results in worse post-transplant survival. J. Heart Lung Transplant. 2016, 35, 236–241. [Google Scholar] [CrossRef] [PubMed]
  42. El-Menshawy, N.; Eissa, M.; Farag, R.; Aboalyazed, A. CD235a (Glycophorin-A) Is the Most Predictive Value among Different Circulating Cellular Microparticles in Thrombocytopenic Human Immunodeficiency Virus Type 1. J. Clin. Lab. Anal. 2016, 30, 235–243. [Google Scholar] [CrossRef]
  43. Demirbaş, A.; Elmas, O.F.; Atasoy, M.; Türsen, U.; Lotti, T. Can monocyte to HDL cholesterol ratio and monocyte to lymphocyte ratio be markers for inflammation and oxidative stress in patients with vitiligo? A preliminary study. Arch. Dermatol. Res. 2021, 313, 491–498. [Google Scholar] [CrossRef] [PubMed]
  44. Saricam, M. Efficiency of Lymphocyte-to-Monocyte Ratio in Differential Diagnosis of Parapneumonic Effusion and Thoracic Empyema. Surg. Infect. 2020, 21, 891–894. [Google Scholar] [CrossRef]
  45. Kan, W.C.; Huang, Y.T.; Wu, V.C.; Shiao, C.C. Predictive Ability of Procalcitonin for Acute Kidney Injury: A Narrative Review Focusing on the Interference of Infection. Int. J. Mol. Sci. 2021, 22, 6903. [Google Scholar] [CrossRef]
  46. Kobayashi, H.; Amrein, K.; Lasky-Su, J.A.; Christopher, K.B. Procalcitonin metabolomics in the critically ill reveal relationships between inflammation intensity and energy utilization pathways. Sci. Rep. 2021, 11, 23194–23204. [Google Scholar] [CrossRef]
  47. Mierzchała-Pasierb, M.; Lipińska-Gediga, K. Sepsis diagnosis and monitoring—Procalcitonin as standard, but what next? Anaesthesiol. Intensive Ther. 2019, 51, 299–305. [Google Scholar] [CrossRef]
  48. Dai, J.; Xia, B.; Wu, X. Elevated plasma procalcitonin level predicts poor prognosis of ST elevation myocardial infarction in Asian elderly. Scand. J. Clin. Lab. Investig. 2018, 78, 49–54. [Google Scholar] [CrossRef] [PubMed]
  49. Xiaoyu, D.; Kai, C.; Zhihui, H.; Huan, L.; Naidong, Z.; Wenge, D. Predictive value of preoperative erythrocyte electrophoresis exponent for acute deep vein thrombosis after total knee arthroplasty in patients with knee osteoarthritis. J. Orthop. Surg. Res. 2020, 15, 496–503. [Google Scholar] [CrossRef]
  50. Zhu, X.; Yao, Y.; Yao, C.; Jiang, Q. Predictive value of lymphocyte to monocyte ratio and monocyte to high-density lipoprotein ratio for acute deep vein thrombosis after total joint arthroplasty: A retrospective study. J. Orthop. Surg. Res. 2018, 13, 211–218. [Google Scholar] [CrossRef]
  51. Balan, D.; Vartolomei, M.D.; Magdás, A.; Balan-Bernstein, N.; Voidăzan, S.T.; Mártha, O. Inflammatory Markers and Thromboembolic Risk in Patients with Non-Muscle-Invasive Bladder Cancer. J. Clin. Med. 2021, 22, 5270. [Google Scholar] [CrossRef] [PubMed]
  52. Martin, P.J.; Anderson, C.C.; Jones, H.M.; Lai, A.P.; Linch, D.C.; Goldstone, A.H. A rise in the percentage of large unstained cells in the peripheral blood determined by the Hemalog D90 automated differential counter is a feature of impending myeloid engraftment following bone marrow transplantation. Clin. Lab. Haematol. 1986, 8, 1–8. [Google Scholar] [CrossRef]
  53. Vanker, N.; Ipp, H. Large unstained cells: A potentially valuable parameter in the assessment of immune activation levels in HIV infection. Acta Haematol. 2014, 131, 208–212. [Google Scholar] [CrossRef] [PubMed]
  54. Shin, D.D.; Lee, M.S.; Kim, D.Y.; Lee, M.G.; Kim, D.S. Increased large unstained cells value in varicella patients: A valuable parameter to aid rapid diagnosis of varicella infection. J. Dermatol. 2015, 42, 795–799. [Google Scholar] [CrossRef] [PubMed]
  55. Reddel, C.J.; Pennings, G.J.; Curnow, J.L.; Chen, V.M.; Kritharides, L. Procoagulant Effects of Low-Level Platelet Activation and Its Inhibition by Colchicine. Thromb. Haemost. 2018, 118, 723–733. [Google Scholar]
  56. Fullard, J.F. The role of the platelet glycoprotein IIb/IIIa in thrombosis and haemostasis. Curr. Pharm. Des. 2004, 10, 1567–1576. [Google Scholar] [CrossRef]
  57. Vasina, E.; Cauwenberghs, S.; Feijge, M.A.; Heemskerk, J.W.; Weber, C.; Koenen, R.R. Microparticles from apoptotic platelets promote resident macrophage differentiation. Cell Death Dis. 2011, 9, e210–e220. [Google Scholar] [CrossRef] [Green Version]
  58. Noisakran, S.; Onlamoon, N.; Pattanapanyasat, K.; Hsiao, H.M.; Songprakhon, P.; Angkasekwinai, N.; Chokephaibulkit, K.; Villinger, F.; Ansari, A.A.; Perng, G.C. Role of CD61+ cells in thrombocytopenia of dengue patients. Int. J. Hematol. 2012, 96, 600–610. [Google Scholar] [CrossRef] [Green Version]
  59. Huang, Z.; Fu, Z.; Huang, W.; Huang, K. Prognostic value of neutrophil-to-lymphocyte ratio in sepsis: A meta-analysis. Am. J. Emerg. Med. 2020, 38, 641–647. [Google Scholar] [CrossRef]
  60. Lagunas-Rangel, F.A. Neutrophil-to-lymphocyte ratio and lymphocyte-to-C-reactive protein ratio in patients with severe coronavirus disease 2019 (COVID-19): A meta-analysis. J. Med. Virol. 2020, 92, 1733–1734. [Google Scholar] [CrossRef] [Green Version]
  61. Templeton, A.J.; McNamara, M.G.; Šeruga, B.; Vera-Badillo, F.E.; Aneja, P.; Ocaña, A.; Leibowitz-Amit, R.; Sonpavde, G.; Knox, J.J.; Tran, B.; et al. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: A systematic review and meta-analysis. J. Natl. Cancer Inst. 2014, 106, 124–135. [Google Scholar] [CrossRef] [PubMed]
  62. Zahorec, R. Neutrophil-to-lymphocyte ratio, past, present and future perspectives. Bratisl. Lek. Listy 2021, 122, 474–488. [Google Scholar] [CrossRef] [PubMed]
  63. Fu, S.; Yan, J.; Tan, Y.; Liu, D. Prognostic value of systemic immune-inflammatory index in survival outcome in gastric cancer: A meta-analysis. J. Gastrointest. Oncol. 2021, 12, 344–354. [Google Scholar] [CrossRef]
  64. Hermiston, M.L.; Xu, Z.; Weiss, A. CD45: A critical regulator of signaling thresholds in immune cells. Annu. Rev. Immunol. 2003, 21, 107–137. [Google Scholar] [CrossRef] [PubMed]
  65. Suades, R.; Padró, T.; Alonso, R.; López-Miranda, J.; Mata, P.; Badimon, L. Circulating CD45+/CD3+ lymphocyte-derived microparticles map lipid-rich atherosclerotic plaques in familial hypercholesterolaemia patients. Thromb. Haemost. 2014, 111, 111–121. [Google Scholar] [CrossRef] [PubMed]
  66. Baj-Krzyworzeka, M.; Majka, M.; Pratico, D.; Ratajczak, J.; Vilaire, G.; Kijowski, J.; Reca, R.; Janowska-Wieczorek, A.; Ratajczak, M.Z. Platelet-derived microparticles stimulate proliferation, survival, adhesion, and chemotaxis of hematopoietic cells. Exp. Hematol. 2002, 30, 450–459. [Google Scholar] [CrossRef]
  67. Ivak, P.; Pitha, J.; Netuka, I. Circulating microparticles as a predictor of vascular properties in patients on mechanical circulatory support; hype or hope? Physiol. Res. 2016, 65, 727–735. [Google Scholar] [CrossRef]
  68. Roka-Moiia, Y.; Miller-Gutierrez, S.; Palomares, D.E.; Italiano, J.E.; Sheriff, J.; Bluestein, D.; Slepian, M.J. Platelet Dysfunction during Mechanical Circulatory Support: Elevated Shear Stress Promotes Downregulation of αIIbβ3 and GPIb via Microparticle Shedding Decreasing Platelet Aggregability. Arterioscler. Thromb. Vasc. Biol. 2021, 41, 1319–1336. [Google Scholar] [CrossRef]
  69. Radley, G.; Ali, S.; Pieper, I.; Thornton, C.A. Mechanical shear stress and leukocyte phenotype and function: Implications for ventricular assist device development and use. Int. J. Artif. Organs 2019, 42, 133–142. [Google Scholar] [CrossRef]
Figure 1. The comparison of EVs (A), CD61 (B), CD45 (C), CD235 (D) concentration in peripheral blood, left ventricle assist device (LVAD), and right ventricle assist device (RVAD). Abbreviations: LVAD—left ventricle assist device, RVAD—right ventricle assist device.
Figure 1. The comparison of EVs (A), CD61 (B), CD45 (C), CD235 (D) concentration in peripheral blood, left ventricle assist device (LVAD), and right ventricle assist device (RVAD). Abbreviations: LVAD—left ventricle assist device, RVAD—right ventricle assist device.
Jcdd 10 00021 g001
Figure 2. Thrombotic materials in right and left ventricle mechanical assist device. (A) thrombotic material (arrow) in the RVAD pump, (B) thrombotic material (arrow) in the LVAD pump, (C) no pathological debris in the mechanical assist device.
Figure 2. Thrombotic materials in right and left ventricle mechanical assist device. (A) thrombotic material (arrow) in the RVAD pump, (B) thrombotic material (arrow) in the LVAD pump, (C) no pathological debris in the mechanical assist device.
Jcdd 10 00021 g002
Figure 3. EVs, CD45, CD61, CD235 concentration in LVAD, RVAD, and peripheral blood presented in a timely manner. Abbreviations: eVs—extracellular vesicles, LVAD—left ventricle assist device. Blue line—right ventricle assist device (RVAD), red line—left ventricle assist device (LVAD), gray line—peripheral blood.
Figure 3. EVs, CD45, CD61, CD235 concentration in LVAD, RVAD, and peripheral blood presented in a timely manner. Abbreviations: eVs—extracellular vesicles, LVAD—left ventricle assist device. Blue line—right ventricle assist device (RVAD), red line—left ventricle assist device (LVAD), gray line—peripheral blood.
Jcdd 10 00021 g003
Table 1. Laboratory results obtained from the peripheral blood samples during deplantation and 24 h following the procedure.
Table 1. Laboratory results obtained from the peripheral blood samples during deplantation and 24 h following the procedure.
ParametersDeplantationAt 24 hp
Whole blood count:
WBC (median (IQR) (K/μL))7.67 (5.55–8.18)6.70 (5.72–7.83)0.236
Neutrophils (median (IQR) (K/μL))5.16 (3.10–5.67)4.84 (3.27–5.03)0.444
Lymphocytes (median (IQR) (K/μL))1.34 (1.24–1.47)1.22 (0.86–1.28)0.026 *
Monocytes (median (IQR) (K/μL))0.59 (0.57–0.74)0.57 (0.46–0.66)0.034 *
NLR (median (IQR))3.52 (2.31–4.51)3.89 (2.88–4.67)0.073
MLR (median (IQR))0.44 (0.41–0.51)0.54 (0.36–0.65)0.088
PLR (median (IQR))185 (159–195)222 (203–331)0.003 *
SII (median (IQR))823 (539–1118)1014 (822–1382)0.023 *
SIRI (median (IQR))2.09 (1.41–2.60)2.37 (1.62–2.85)0.197
AISI (median (IQR))555 (318–637)562 (460–737)0.728
LUC (median (IQR) (K/μL))0.21 (0.18–0.29)0.29 (0.17–0.40)0.273
Hb (median (IQR) (mmol/μL))6.2 (5.70–6.50)6.30 (6.00–6.40)0.533
Hct (median (IQR) (%))30 (28–32)31 (30–32)0.243
MCHC (median (IQR) (mmol/L))20.54 (20.15–20.80)20.39 (19.92–20.58)0.012 *
RDW (median (IQR) (%))15.7 (14.3–18.0)16.9 (14.4–19.1)0.006 *
Platelets (median (IQR) (K/μL))235 (233–265)271 (237–285)0.161
MPV (median (IQR) (fL))7.4 (7.1–7.5)7.30 (6.90–7.60)0.497
Inflammatory markers:
CRP (median (IQR) (mg/L))46 (24–62)46 (38–84)0.754
Procalcitonin (median (IQR) (ng/mL))0.21 (0.03–1.33)0.86 (0.03–2.48)0.221
Abbreviations: AISI—aggregation inflammatory systemic index, CRP—C reactive protein, Hb—hemoglobin, Hct—hematocrit, MCHC—mean corpuscular hemoglobin concentration, MLR—monocyte to lymphocyte ratio, MPV—mean platelet volume, NLR—neutrophil to lymphocyte ratio, PLR—platelets to lymphocyte ratio, RDW—red cells width, SII—systemic inflammatory index, SIRI—systemic inflammatory response index, WBC—white blood count. * statistical significance.
Table 2. Correlation matrix for LVAD and peripheral blood parameters and EVs.
Table 2. Correlation matrix for LVAD and peripheral blood parameters and EVs.
EVsCD61CD45CD235
CRP pre−0.541−0.1620.5590.739
CRP post−0.286−0.7140.2140.857
PCT pre−0.018−0.2160.7750.937
PCT post0.144−0.2340.7390.955
Crea pre0.750−0.1790.2860.250
Crea post0.071−0.286−0.2140.286
WBC−0.571−0.321−0.1790.464
Neutrophils−0.643−0.2500.1790.679
Lymphocytes−0.071−0.536−0.1790.464
Monocytes−0.4320.378−0.703−0.595
NLR−0.5360.1070.3570.607
MLR−0.3930.536−0.571−0.821
PLR−0.0360.7500.286−0.393
SII−0.5360.1070.3570.607
SIRI−0.7140.0360.0360.393
AISI−0.7500.107−0.0710.250
LUC−0.071−0.8570.1430.714
Rbc00.5360.3930.250
Hb0.5230.5050.126−0.180
Hct0.5090.4730.036−0.255
MCHC−0.214−0.107−0.179−0.107
RDW−0.072−0.2700.7750.847
Platelets−0.3930.5360.2860.179
MPV0.3240.1440.9010.541
Abbreviations: AISI—aggregation inflammatory systemic index, crea—serum creatinine, CRP—C reactive protein, Hb—hemoglobin, Hct—hematocrit, LUC—large unstained cells, MCHC—mean corpuscular hemoglobin concentration, MLR—monocyte to lymphocyte ratio, MPV—mean platelet volume, NLR—neutrophil to lymphocyte ration, PCT—procalcitonin, PLR—platelets to lymphocyte ratio, post—24 h after deplantation, pre—before deplantation, RDW—red cells width, SII—systemic inflammatory index, SIRI—systemic inflammatory response index, WBC—white blood count.
Table 3. Correlation matrix for RVAD blood biomarkers and microparticles.
Table 3. Correlation matrix for RVAD blood biomarkers and microparticles.
EVsCD61CD45CD235
CRP pre−0.108−0.7030.5950.667
CRP post−0.429−0.7860.3570.987
PCT pre−0.342−0.7750.4320.685
PCT post−0.144−0.8470.5230.739
Crea pre−0.214−0.429−0.1790.179
Crea post0.07100.2500.357
WBC−0.143−0.1070.5360.607
Neutrophils−0.143−0.4640.7140.750
Lymphoctes−0.321−0.0710.1070.536
Monocytes0.5050.6670.324−0.342
NLR0.036−0.3930.8570.536
MLR0.6070.6430.107−0.607
PLR0.5710.0710.214−0.536
SII0.036−0.3930.8570.536
SIRI0.286−0.3210.8930.536
AISI0.28600.7500.321
LUC−0.357−0.71400.857
Rbc0.1790.1430.536−0.107
Hb0.1080.523−0.090−0.541
Hct0.0360.600−0.182−0.582
MCHC−0.2500.429−0.321−0.179
RDW−0.216−0.9550.3780.703
Platelets0.5360.0710.750−0.036
MPV0.306−0.6850.2520.180
Abbreviations: AISI—aggregation inflammatory systemic index, crea—serum creatinine, CRP—C reactive protein, Hb—hemoglobin, Hct—hematocrit, LUC- large unstained cells, MCHC—mean corpuscular hemoglobin concentration, MLR—monocyte to lymphocyte ratio, MPV—mean platelet volume, NLR—neutrophil to lymphocyte ration, PCT—procalcitonin, PLR—platelets to lymphocyte ratio, post—24 h after deplantation, pre—before deplantation, RDW—red cells width, SII—systemic inflammatory index, SIRI—systemic inflammatory response index, WBC—white blood count.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Urbanowicz, T.; Olasińska-Wiśniewska, A.; Grodecki, K.; Gąsecka, A.; Filipiak, K.J.; Gawlikowski, M.; Mucha, Ł.; Jemielity, M. Increased Plasma Concentrations of Extracellular Vesicles Are Associated with Pro-Inflammatory and Pro-Thrombotic Characteristics of Left and Right Ventricle Mechanical Support Devices. J. Cardiovasc. Dev. Dis. 2023, 10, 21. https://doi.org/10.3390/jcdd10010021

AMA Style

Urbanowicz T, Olasińska-Wiśniewska A, Grodecki K, Gąsecka A, Filipiak KJ, Gawlikowski M, Mucha Ł, Jemielity M. Increased Plasma Concentrations of Extracellular Vesicles Are Associated with Pro-Inflammatory and Pro-Thrombotic Characteristics of Left and Right Ventricle Mechanical Support Devices. Journal of Cardiovascular Development and Disease. 2023; 10(1):21. https://doi.org/10.3390/jcdd10010021

Chicago/Turabian Style

Urbanowicz, Tomasz, Anna Olasińska-Wiśniewska, Kajetan Grodecki, Aleksandra Gąsecka, Krzysztof J. Filipiak, Maciej Gawlikowski, Łukasz Mucha, and Marek Jemielity. 2023. "Increased Plasma Concentrations of Extracellular Vesicles Are Associated with Pro-Inflammatory and Pro-Thrombotic Characteristics of Left and Right Ventricle Mechanical Support Devices" Journal of Cardiovascular Development and Disease 10, no. 1: 21. https://doi.org/10.3390/jcdd10010021

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop