Abstract
Pulmonary embolism (PE) is a heterogenous condition with variable clinical presentations. Thrombin generation potential (TGP) and biomarkers, and blood cellular indices can reflect the underlying pathophysiology and risk stratification of PE. This case–control study analyzed TGP in 209 PE patients from Loyola University, Pulmonary Embolism Response Team program compared to normal human plasma (NHP) controls. The present study evaluates TGP and biomarkers, and cellular indices in relation to PE severity, according to the European Society of Cardiology (ESC) guidelines. Statistical analysis including median with interquartile range (IQR), 2-tailed Wilcoxon Mann–Whitney test, Chi-square test, and Spearman Correlational analysis were performed. There were 209 patients with PE, with an almost equal distribution between sex, and a median age of 63 years. Significant downregulation in peak thrombin and endogenous thrombin potential (ETP), as well as upregulation in lag time, were observed in PE patients versus controls. Biomarker analysis revealed pronounced elevations, with D-dimer demonstrating the most significant increase. Blood cellular indices also rose in PE patients, correlating with disease severity. PE severity was associated with higher TGP and biomarker levels. Mortality rates differed significantly across risk categories and were highest in patients with elevated cellular indices. TGP and biomarkers are intricately linked to PE severity and can aid in risk stratification. Elevated cellular indices are associated with increased mortality, highlighting their potential as prognostic markers. These findings could enhance the precision of PE management strategies.
Keywords: D-dimer, prothrombin fragment 1 + 2 (F1+2), thrombin–antithrombin complex (TAT), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII, NLR*platelets)
Introduction
Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), presents a significant global healthcare challenge. 1 Estimates indicate that PE affects approximately 10 million people worldwide each year. In the United States alone, the Center for Disease Control (CDC) reports an annual incidence of approximately 900,000 VTE cases, with mortality rates ranging between 60,000 and 100,000. 2 PE is associated with a sudden death rate of about 25%, and a high recurrence rate, with approximately 33% of patients experiencing a repeat episode within 10 years. The pathogenesis of thromboembolism in PE is complex, involving various mechanisms including inflammation, hemostatic dysregulation, fibrinolytic deficit, cellular, and vascular dysfunctions.3–5 Additionally, risk factors such as obesity, contraceptive use, pregnancy, immobilization, chemotherapy, and anticoagulation also contribute to VTE development.6–15 Furthermore, genetic predispositions like FV-Leiden, prothrombin gene mutation (G20210), and deficiencies in anti-thrombin III, protein C, and protein S), alongside hyperhomocysteinemia and MTHFR mutation, play significant roles in VTE pathophysiology.16–20
Thrombo-inflammation is a critical aspect in PE pathophysiology, characterized by the generation of several inflammatory mediators. These mediators are often upregulated by thrombin and its products, contributing to the disease process.21,22 The interaction between tissue factor, cell activation, and endothelial dysfunction is central to anticoagulation,23–25 primarily through the activation of Factor VII and subsequent conversion of Factor X to Xa, leading to thrombin formation.26,27 Coagulation activation pathways, both intrinsic and extrinsic, are integral to this process. These pathways are outlined in Figure 1. The hypothesis explored in this study postulates that a decrease in thrombin generation is correlated with an increase in thrombin generation biomarkers, which in turn may reflect the severity and mortality rates in acute PE cases.
Figure 1.
Mechanism of generation of thrombin and thrombin generation marker during activation of coagulation system. Generation of thrombin is due to the contact factor or intrinsic pathway (presented in orange), tissue factor pathway or extrinsic pathway (presented in green), activation of any of the 2 pathways leads to the activation of common pathway towards the generation of thrombin and clot formation (presented in blue). Moreover, clot formation initiates the fibrinolytic pathway (presented in purple). Abbreviations: AT, antithrombin; TF, tissue factor; Ca+2, calcium; FPA, fibrinopeptide A; FPB, fibrinopeptide B; PAI-1a, plasminogen activator inhibitor-1 antigen; tPA, tissue-plasminogen activator; FDP, fibrin degradation product.
Thrombin itself exerts a multifaceted role in VTE pathophysiology,28,29 not only in clot formation and stabilization but also in the activation of platelets, monocytes, and macrophages. 30 These activated cells release products that can cause localized effects, such as vasoconstriction and blood flow impedance. Recent studies have linked blood cellular counts and indices, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammatory index (SII), with the pathophysiology of VTE. 31 Activated platelets transition through phases of aggregation and procoagulant activity,32–36 with platelet-derived extracellular vesicles further contributing to coagulation activation. Additionally, leukocyte- and monocyte-derived extracellular vesicles are implicated in thrombin generation,37–39 with neutrophils also playing a significant role through NETosis and subsequent formation of neutrophil extracellular traps (NETs), which possess prothrombotic and proinflammatory effects.40,41
The treatment of PE involves anticoagulation therapy in addition to different interventional or surgical treatment approaches in selected patient groups. For successful treatment outcomes the risk stratification of PE patients has critical importance to identify high-risk patients who require closer monitoring and more aggressive treatment. Echocardiographic assessment of the right ventricle (RV) and right ventricular/left ventricular (RV/LV) ratio is widely recognized as a valuable tool for the prognostic assessment of acute PE patients in clinical practice. The European Society of Cardiology (ESC) guidelines use patient age, cardiopulmonary impairment, and comorbidities in addition to elevated myocardial biomarkers (troponin and brain natriuretic peptide) and RV dysfunction to stratify PE patients as low-, intermediate-, and high-risk groups. But there is an ongoing need for better risk stratification systems to guide intensity of the initial therapy, treatment duration, and long-term follow-up.
The prognostic value of cellular indices in various pathological states, including their relationship with thrombotic and endothelial markers, necessitates further investigation. This manuscript aims to elucidate the correlations between thrombin generation biomarkers and potential with cellular indices, advancing our understanding of the role of thrombin in cellular activation within the context of VTE.
Methods
Study design: This case–control study investigated thrombin generation potential (TGP) in patients with PE, employing normal human plasma (NHP) as a control. This study also explored the relationship between TGP and disease severity through a comparative analysis by clinical risk and comorbidities. Secondary aim was to correlate baseline thrombin generation biomarkers, including cellular indices, with TGP in the context of acute PE. Moreover, this study also stratified TGP, biomarkers, and blood cellular indices by PE severity and cancer-associated thrombosis (CAT).
Patient population: The study cohort consisted of PE patients enrolled in the Pulmonary Embolism Response Team (PERT) program; consultative service in a tertiary care center (Loyola University Medical Center, Gottlieb Memorial Hospital, and MacNeal Hospital). PE diagnosis was confirmed via CT, VQ scan, or angiography. Following ER diagnosis, and PERT activation, consenting patients provided blood samples post-admission. Samples were collected from a 2-hospital tertiary health care center (Loyola University Medical Center and Gottlieb Memorial Hospital).This study utilized a prospective approach for clinical and imaging data collection, with patients selected randomly via a number generator. IRB-approved study (IRB#: 209457032217) included patients aged 18 to 101 years and were discharged with a principal discharge diagnosis of PE (ICD-10 codes: 415.1, 415.11, 415.12, 415.19) from 2018 onwards.
Sample collection: Citrated blood samples (3.2% sodium citrate tubes) from 209 patients obtained for the routine patient's care collected with 24 to 72 h of diagnosis were used in this study. Samples were de-identified, and platelet-poor plasma was obtained by centrifugation, then stored at −70 °C. Control plasma from 50 healthy volunteers was sourced from George King Biomedical, Inc. (Overland Park, KS, USA).
Measured variables: Demographic data, VTE risk factors, concomitant disorders, clinical presentation, laboratory parameters, and PE severity were electronically gathered. Demographics included gender, age, weight, and body mass index (BMI). Risk factors included cancer, recent surgery, prolonged immobility, and pregnancy. Concomitant disorders covered a spectrum from leg varicosities to chronic diseases, smoking status. Clinical presentations were diverse, encompassing vital signs and symptomatic indicators. Laboratory assessment included complete blood counts and cardiac markers, while PE severity was graded following the ESC 2019 guidelines. 42 All-cause mortality was determined from review of electronic medical record.
Quantification of biomarker levels: Biomarker levels were analyzed using commercially available Sandwich Enzyme Linked Immunosorbent Assays (ELISA). D-dimer, prothrombin fragment 1.2 (F1+2), and thrombin–antithrombin complex (TAT) were obtained from HYPHEN BioMed (Neuville dur Oise, France), and Siemens Healthcare Diagnostic Products (Marburg, Germany)
TGP: TGP was assessed using the calibrated automated thrombogram assay on a Fluoroskan Ascent fluorimeter. Assays were conducted with specified reagents, measuring peak thrombin, lag time, and endogenous thrombin potential (ETP)/area under the curve (AUC) from 96-well plates. Samples were retrospectively analyzed using the manufacturer's protocol.
Blood cellular indices: Blood cellular indices were derived from baseline complete blood count (CBC) data, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune inflammation index (SII; NLR × platelet count).
Data analysis: Data were processed using IBM® SPSS and GraphPad Prism Software. We determined distribution patterns, median, and IQR for all variables. Fold changes in PE patients versus NHP were calculated and ranked. Statistical comparisons utilized 2-tailed Wilcoxon Mann–Whitney tests, with P < .05 denoting significance. These analyses were replicated across PE severity groups and CAT status. Spearman's correlation analyses were performed to delineate relationships among biomarkers and between PE patients.
Results
Demographics
Table 1 represents demographic data, co-morbidities, clinical presentation, laboratory parameters, PE risk stratification, and mortality within the Loyola PERT cohort. The cohort consisted of 209 patients, with a nearly equal distribution of males (51.2%) and females (48.8%), a median age of 63 years, and a median BMI of 30.2. Risk stratification according to the ESC guidelines revealed 11.5% low-risk, 80.9% intermediate-risk, and 7.7% high-risk PE patients. This table details co-morbidities, clinical presentations, and complete blood count (CBC) values. The most common presentations were dyspnea (89%), chest pain (29.2%), and syncope (12.4%). The NLR is presented as both an average value and for those which values greater than 7. PLR and SII are also reported as average values and for values exceeding 220 and 1600, respectively.
Table 1.
Basic Clinical Characteristics and Laboratory Parameters in the Loyola PERT Cohort.
| Variables | PE group |
|---|---|
| Median (IQR), N (%) | |
| Demographics | |
| Patients | 209 |
| Age | 63 (51–73) |
| Sex Male Female |
107 (51.2%) 102 (48.8%) |
| BMI | 30.2 (25.5–35.9) |
| Clinical presentation | |
| Systolic blood pressure (mm Hg) | 116.0 (101.5–127.0) |
| Heart rate (beats/min) | 97.0 (82.0–110.0) |
| Oxygen saturation (%) | 92.0 (90.0–95.0) |
| Dyspnea | 186 (89.0%) |
| Predictors of PE severity | |
| Right ventricular dysfunction | 0.9 (0.8–1.1) |
| Troponin | 0.2 (0.1–0.2) |
| Brain natriuretic peptide | 114.0 (40.0–385.0) |
| PESI score | 107.0 (81.0–141.5) |
| Risk stratification | |
| Low-risk PE | 24 (11.5%) |
| Intermediate-risk PE | 169 (80.9%) |
| High-risk PE | 16 (7.7%) |
| Comorbidities | |
| Active cancer | 43 (20.6%) |
| MI/angina | 21 (10.0%) |
| Coronary artery disease | 23 (11.0%) |
| Hypertension | 120 (57.4%) |
| Arterial fibrillation | 14 (6.7%) |
| Chronic heart failure | 37 (14.8%) |
| Chronic lung disease | 24 (11.5%) |
| Chronic kidney disease | 21 (10.0%) |
| Cerebral ischemia | 22 (10.5%) |
| Peripheral artery disease | 4 (1.9%) |
| COVID-19 | 14 (6.7%) |
| Mortality | |
| 30-day mortality | 16 (7.7%) |
| 3-months mortality | 28 (13.4%) |
| 6-months mortality | 34 (16.3%) |
| 9-months mortality | 34 (16.3%) |
| 12-months mortality | 34 (16.3%) |
| Laboratory parameters | |
| Hemoglobin (g/dl) | 12.4 (10.3–14.5) |
| Neutrophils (×1000/mm3) | 6.9 (4.2–9.7) |
| Leukocytes (×1000/mm3) | 9.7 (7.0–12.9) |
| Lymphocytes (×1000/mm3) | 1.5 (0.9–2.1) |
| Monocytes (×1000/mm3) | 0.7 (0.5–0.9) |
| Eosinophils (×1000/mm3) | 0.1 (0.0–0.2) |
| Basophils (×1000/mm3) | 0.0 (0.0–0.1) |
| Platelets (×1000/mm3) | 228.0 (165.5–320.5) |
| NLR (×1000/mm3) | 5.0 (2.7–7.6) |
| NLR >7 | 59 (28.2%) |
| PLR (×1000/mm3) | 174.4 (106.2–260.9) |
| PLR > 220 | 75 (35.9%) |
| SII (×1000/mm3) | 1175.3 (557.0–2042.7) |
| SII > 1600 | 76 (36.4%) |
Abbreviations: PE, pulmonary embolism; IQR, interquartile range; BMI, body mass index; PESI, pulmonary embolism severity index; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; SII, systemic immune inflammation index.
PE Cohort Analysis
Table 2 compares TGP, biomarkers, and blood cellular indices in PE patients to healthy controls, presenting data as median (IQR), fold change, and significance level. TGP exhibited significant variation with PE patients showing lower peak thrombin and ETP, and increased lag time. All biomarkers were elevated in PE patients, with D-dimer, F1+2, and TAT displaying significant increases compared to controls. Blood cellular indices also rose in PE patients, with varying levels of increase for NLR, and SII compared to the controls. Figure 2 illustrates correlations between TGP, biomarkers, and blood cellular indices. Thrombin levels strongly correlated with ETP and showed weaker correlations with F1+2 and TAT. ETP correlated with F1+2. Lag time correlated with NLR. D-dimer showed weak to moderate correlations with F1+2, and moderate correlation with TAT, F1+2 also showed moderate correlation and TAT. Blood cellular indices NLR and PLR showed moderate to strong correlations with PLR.
Table 2.
Comparison of TGP, Biomarkers, and Blood Cellular Indices in PE Patients Compared to Healthy Controls.
| PE group | Control group | Fold change | P value | |
|---|---|---|---|---|
| Variables | Median (IQR) | Median (IQR) | ||
| Patients (N) | 209 | 50 | — | — |
| Thrombin generation potential | ||||
| Thrombin (nM*min) | 61.3 (5.3–130.5) | 138.4 (125.4–157.2) | −0.557 | <.0001 |
| ETP (nM*min) | 476.7 (119.2–738.3) | 583.7 (529.8–658.3) | −0.183 | .0126 |
| Lag time (min) | 2.7 (2.0–3.7) | 1.7 (1.7–2.0) | 0.588 | <.0001 |
| Thrombin generation biomarkers | ||||
| D-dimer (ng/ml) | 5400.0 (2550.6–10327.9) | 108.3 (0.0–52.6) | 48.86 | <.0001 |
| F1+2 (pmol/L) | 507.3 (286.6–944.2) | 274.9 (199.3–329.8) | 0.845 | <.0001 |
| TAT (ug/L) | 13.7 (7.9–36.1) | 2.8 (1.6–3.4) | 3.892 | <.0001 |
| Blood cellular indices | ||||
| NLR (×1000/mm3) | 5.0 (2.7–7.6) | 2.1 (1.2–3.0) | 1.381 | <.0001 |
| PLR (×1000/mm3) | 174.4 (106.2–260.9) | 129.0 (100.3–157.4) | 0.352 | ns |
| SII (×1000/mm3) | 1175.3 (557.0–2042.7) | 790.4 (423.0–8854.0) | 0.487 | .0004 |
Abbreviations: PE, pulmonary embolism; IQR, interquartile range; ETP, endogenous thrombin potential; F1+2, prothrombin fragment 1 + 2; TAT, thrombin–antithrombin complex; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; SII, systemic immune inflammation index; ns, not significant.
Figure 2.
Correlation analysis of TGP, biomarkers, and blood cellular indices in PE patients. Abbreviations: PE, pulmonary embolism; ETP, endogenous thrombin potential; F1+2, prothrombin fragment 1 + 2; TAT, thrombin–antithrombin complex; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; SII, systemic immune inflammation index.
Stratification of PE Patients by ESC Severity
Table 3 presents data on TGP, biomarkers, and blood cellular indices stratified by ESC-defined PE severity among a cohort of 209 patients. Patients were classified as low-risk (n = 24), intermediate-risk (n = 166), and high-risk PE (n = 16). TGP, characterized by thrombin levels and lag time, varied with PE severity. Low-risk PE showed 73.1 (44.0-144.4) nM for thrombin levels and 2.8 (2.1-3.9) min for lag time, intermediate-risk PE exhibited 56.1 (4.7-131.4) nM and 2.7 (2.0-3.7) min, and high-risk PE presented 65.0 (0.4-127.0) nM and 2.7 (2.1-3.8) min, respectively. A decreasing trend in ETP was observed with increasing PE severity: low-risk at 590.0 (427.5-724.6) nM*min, intermediate-risk at 453.1 (113.0-748.3) nM*min, and high-risk at 370.5 (0.00-700.7) nM*min. Biomarker levels, including D-dimer, F1 + 2, and TAT generally increased with PE severity. This was reflected in the gradient of elevations across low-risk, intermediate-risk, and high-risk PE groups. Blood cellular indices varied in relation to risk severity, with NLR and PLR levels increasing in intermediate-risk PE but decreasing in the high-risk PE. SII levels inversely correlated with the escalation of PE severity. Mortality rates differed by risk category, with low-risk PE showing a 4.2% mortality rate extending from 3 months to 12 months. Intermediate-risk PE mortality increased from 7.7% at 30 days to 17% at 6 months, persisting through 12 months. High-risk PE maintained a constant mortality rate of 18.8% from 30 days to 12 months.
Table 3.
Comparison of TGP, Biomarkers, and Blood Cellular Indices in PE Patients Based on the PE Severity.
| Variables | Low-risk PE | Intermediate-risk PE | High-risk PE | Significance |
|---|---|---|---|---|
| Median (IQR), N (%) | Median (IQR), N (%) | Median (IQR), N (%) | ||
| Patients (N) | 24 | 166 | 16 | |
| Thrombin generation potential | ||||
| Thrombin (nM*min) | 73.1 (44.0–144.4) | 56.1 (4.7–131.4) | 65.0 (0.4–127.0) | ns |
| ETP (nM*min) | 590.0 (427.5–724.6) | 453.1 (113.0–748.3) | 370.5 (0.00–700.7) | ns |
| Lag time (min) | 2.8 (2.1–3.9) | 2.7 (2.0–3.7) | 2.7 (2.1–3.8) | ns |
| Thrombin generation biomarkers | ||||
| D-dimer (ng/ml) | 4407.6 (2319.0–7164.0) | 5135.4 (2169.3–10100.5) | 13338.2 (8581.2–15976.6) | $, % |
| F1+2 (pmol/L) | 426.0 (268.1–580.8) | 507.3 (275.9–989.6) | 722.0 (411.4–1945.7) | $ |
| TAT (ug/L) | 11.5 (6.2–18.6) | 13.3 (7.9–36.1) | 38.5 (15.0–59.1) | $, % |
| Blood cellular indices | ||||
| NLR (×1000/mm3) | 4.2 (3.5–6.1) | 5.3 (2.7–7.8) | 3.1 (1.6–10.0) | ns |
| PLR (×1000/mm3) | 145.1 (117.2–234.7) | 183.3 (110.4–273.2) | 68.4 (47.7–170.8) | $, % |
| SII (×1000/mm3) | 1233.1 (607.5–1653.0) | 1188.6 (600.4–2164.5) | 545.3 (250.5–1654.7) | % |
| Predictors of PE severity | ||||
| RV/LV ratio | 0.8 (0.7–0.9) | 0.9 (0.8–1.1) | 1.3 (1.0–1.5) | #, $, % |
| Troponin | 0.016 (0.01–0.03) | 0.036 (0.02–0.23) | 0.29 (0.05–3.64) | #, $, % |
| BNP | 31.0 (10.0–64.0) | 128.0 (56.0–387.0) | 415.0 (53.0–597.0) | #, $ |
| SBP (mm/Hg) | 121.0 (107.8–136.8) | 118.0 (102.0–126.0) | 84.5 (75.5–105.5) | $, % |
| PESI score | 54.0 (38.0–67.0) | 112.0 (93.0–141.5) | 148.0 (100.5–187.5) | #, $ |
| Mortality | ||||
| 30-day mortality | 0 (0.0%) | 13 (7.7%) | 3 (18.8%) | — |
| 3-months mortality | 1 (4.2%) | 24 (14.2%) | 3 (18.8%) | — |
| 6-months mortality | 1 (4.2%) | 30 (17.8%) | 3 (18.8%) | — |
| 9-months mortality | 1 (4.2%) | 30 (17.8%) | 3 (18.8%) | — |
| 12-months mortality | 1 (4.2%) | 30 (17.8%) | 3 (18.8%) | — |
Abbreviations: PE, pulmonary embolism; IQR, interquartile range; ETP, endogenous thrombin potential; F1+2, prothrombin fragment 1 + 2; TAT, thrombin–antithrombin complex; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; SII, systemic immune inflammation index; RV/LV ratio, right ventricular/left ventricular ratio; BNP, brain natriuretic peptide; SBP, systolic blood pressure; PESI, pulmonary embolism severity index; ns, not significant.
# P value <0.05 between low- versus intermediate-risk PE; $ P value <0.05 between low- versus high-risk PE; % P value <0.05 between intermediate- versus high-risk PE.
Stratification of PE Patients by CAT and Non-CAT Groups
Table 4 contrasts TGP, biomarkers, and blood cellular indices between CAT and non-CAT sub-groups within the PE cohort, which comprises an equal distribution of males and females, with a median age of 63 years, and a BMI of 30.2%. Among these patients, 20.6% were categorized in the CAT group, showing a decrease in TGP as evidenced by lower peak thrombin and ETP, and an increase in lag time compared to the non-CAT group. Biomarker levels, including D-dimer and TAT, were lower in the CAT group, whereas F1+2 was higher. Blood cellular indices, particularly NLR, PLR, and SII, were markedly elevated in the CAT group, correlating with an increased mortality rate from 30 days to 6 months. This data suggests a significant difference in the pathophysiology and prognosis between CAT-associated and non-CAT PE patients.
Table 4.
Levels of TGP, Biomarkers, and Blood Cellular Indices in PE Patients Based on Cancer- and Non-Cancer-Associated Thrombosis.
| Variables | PE group | CAT group | Non-CAT group | P value* |
|---|---|---|---|---|
| Median (IQR), N (%) | Median (IQR), N (%) | Median (IQR), N (%) | ||
| Patients (N) | 209 | 43 | 166 | |
| Thrombin generation potential | ||||
| Thrombin (nM*min) | 61.3 (5.3–130.5) | 51.5 (5.0–125.3) | 69.0 (5.5–136.1) | ns |
| ETP (nM*min) | 476.7 (119.2–738.3) | 428.6 (103.5–706.5) | 491.1 (119.8–774.0) | ns |
| Lag time (min) | 2.67 (2.0–3.7) | 2.9 (2.2–4.4) | 2.7 (2.0–3.4) | ns |
| Thrombin generation biomarkers | ||||
| D-dimer (ng/ml) | 5400.0 (2550.6–10327.9) | 4261.2 (1822.8–9069.7) | 5745.8 (2757.9–10905.5) | ns |
| F1 + 2 (pmol/L) | 507.3 (286.6–944.2) | 520.7 (274.8–818.6) | 490.0 (286.7–960.7) | ns |
| TAT (ug/L) | 13.7 (7.9–36.1) | 12.8 (7.5–43.5) | 14.3 (8.1–31.6) | ns |
| Blood cellular indices | ||||
| NLR (×1000/mm3) | 5.0 (2.7–7.6) | 7.6 (4.5–12.0) | 4.4 (2.5–6.7) | <.001 |
| PLR (×1000/mm3) | 174.4 (106.2–260.9) | 246.4 (148.0–406.7) | 156.0 (99.8–233.6) | <.001 |
| SII (×1000/mm3) | 1175.3 (557.0–2042.7) | 1708.0 (792.7–3963.4) | 959.4 (518.4–1893.8) | .003 |
| Predictors of PE severity | ||||
| RV/LV ratio | 0.91 (0.78–1.11) | 0.90 (0.77–1.00) | 0.91 (0.79–1.13) | ns |
| Troponin | 0.03 (0.01–0.23) | 0.03 (0.01–0.06) | 0.04 (0.02–0.29) | .026 |
| BNP | 114.0 (40.0–385.0) | 96.0 (37.0–173.0) | 130.0 (40.5–468.5) | ns |
| SBP (mm/Hg) | 116.0 (1015–127.0) | 118.0 (99.0–124.0) | 116.0 (102.0–128.0) | ns |
| PESI score | 107.0 (81.0–141.5) | 134.0 (108.0–168.0) | 101.5 (72.0–135.0) | <.001 |
| Mortality | ||||
| 30-day mortality | 16 (7.7%) | 9 (20.9%) | 7 (4.2%) | <.001 |
| 3-months mortality | 28 (13.4%) | 17 (39.5%) | 11 (6.6%) | <.001 |
| 6-months mortality | 34 (16.3%) | 20 (46.5%) | 14 (8.4%) | <.001 |
| 9-months mortality | 34 (16.3%) | 20 (46.5%) | 14 (8.4%) | <.001 |
| 12-months mortality | 34 (16.3%) | 20 (46.5%) | 14 (8.4%) | <.001 |
Abbreviations: PE, pulmonary embolism; CAT, cancer-associated thrombosis; IQR, interquartile range; ETP, endogenous thrombin potential; F1+2, prothrombin fragment 1 + 2; TAT, thrombin–antithrombin complex; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; SII, systemic immune inflammation index; RV/LV ratio, right ventricular/left ventricular ratio; BNP, brain natriuretic peptide; SBP, systolic blood pressure; PESI, pulmonary embolism severity index; ns, not significant.
P value between CAT versus non-CAT group.
Discussion
This study provides a comprehensive analysis of TGP, biomarkers, and cellular indices in a well-defined cohort of PE patients. Our findings underscore the heterogeneity of PE pathophysiology, as evidenced by the wide variations in TGP between patients and healthy controls. The significant downregulation of peak thrombin and ETP, alongside the prolongation of lag time in PE patients, indicates a distinct thrombin generation profile that is associated with the disease. Importantly, the upsurge in lag time suggests a delayed initiation of coagulation, potentially contributing to the progression of thromboembolic events.
The marked elevation of biomarkers, especially D-dimer, in PE patients points to an ongoing hypercoagulable state. The strong positive correlation between D-dimer levels and TGP underlines the clinical utility of these markers in assessing disease severity and the effectiveness of therapeutic interventions. Notably, the biomarkers studied, including F1+2 and TAT, have demonstrated their prognostic relevance, which could be integrated in risk stratification models to improve patient management and outcomes.
The stratification of patients based on the ESC guidelines revealed a gradient of TGP and biomarker levels in accordance with the severity of PE. This stratification not only confirms the escalated thrombo-inflammatory response in higher-risk categories but also reflects the potential for these markers to guide therapeutic decisions. For instance, the observed decrease in ETP with increasing PE severity may offer insights into the intensity of anticoagulant therapy required.
The study further delves into the role of blood cellular indices such as the NLR, PLR, and SII in PE. The association of elevated NLR and PLR with intermediate-risk PE could point to their involvement in thrombo-inflammation and their potential as early markers for acute PE. These findings are in line with emerging literature that suggests a link between inflammation and thrombosis in the pathogenesis of PE This may involve NETosis and related extra vesicle formation along with degranulation and release of histones and damage-associated molecular patterns (DAMPs).40,41 Moreover microparticles derived from monocytes and platelets may trigger procoagulant and proinflammatory responses.
Our data also highlight the prognostic value of cellular indices in mortality rates, which were shown to be consistently higher in patients with higher NLR, PLR, and SII. The significant increase in mortality rates observed in the CAT subgroup necessitates a closer examination of these indices as potential predictors of adverse outcomes. The utility of these indices in clinical practice, however, requires further validation in larger, prospective studies to determine their role in the routine evaluation of PE patients.
The findings of this study may also have some important clinical implications for PE management. Firstly, the normalization of TGP, thrombin generation biomarkers, and blood cellular indices may be more precise predictors of optimal treatment response in PE patients. Additionally, these parameters can also be used for better risk stratification of PE patients. Although not all of them are available for routine clinical practice, blood cellular indices can easily be incorporated into risk assessment models to help identify high-risk patients who require closer monitoring and more aggressive treatment. Additionally, our results in CAT patients clearly demonstrates a more prominent downregulation of TGP with elevation of thrombin generation biomarkers and blood cellular indices which may be helpful to explain the increased rates of VTE and bleeding complications observed in this patient population.
This study has several limitations. The study is based on a small cohort of only 209 patients with a diverse patient population. In addition, the time for the sample collection varied from 24 to 72 h after the onset of PE and moreover, the samples were stored for prolong time. The study based on single sample analysis, and sequential samples were not collected. In terms of thrombin generation markers, D-dimer, F1+2, and TAT were analyzed while other markers such as tissue factor, fibrinopeptide A, fibrinopeptide B, and soluble monomer were not studied. One of the major limitations is that we did not study prothrombinase complex and its contribution toward thrombin generation and the biomarkers. The patient distribution with respect to the PE severity was disproportional as 24 patients in low-risk, 166 in intermediate-risk, and 16 patients in high-risk PE. History and type of drugs and anticoagulation management is not taken into account as they were used immediately after the diagnosis. Other considerations including the diagnostic procedures and use of intravenous fluids and factors contributing to hemodilution are not taken into account. Despite these limitations, this study has validated that increase thrombin generation biomarkers are associated with PE with the simultaneous decrease in thrombin generation parameters.
In conclusion, the relationships between TGP, biomarkers, and cellular indices not only reinforce their pathophysiological relevance in PE but also emphasize the complexity of the disease. The integration of these markers into clinical practice could enhance the precision of PE risk stratification and management, ultimately improving patient care. The current study included only 209 patients and because of the complex nature of PE, a larger cohort may further strengthen these findings, thus a multicenter trial may be helpful before any recommendations offered to the clinicians. Future studies should focus on the longitudinal assessment of these markers to validate their predictive value and to refine the therapeutic strategies for PE.
Acknowledgments
The authors are thankful to the staff of the Hemostasis and Thrombosis Research Laboratory for their expert assistance in completing this study. We are grateful to the Clinical Laboratory staff for their support in sample collection. We are thankful to Mrs. Erin Healy Erickson for her skillful assistance in preparing this manuscript. This project was internally funded by Cardiovascular Research Institute, Loyola University Chicago, Health Science Division. We are also thankful to Dr Eva Wojcik, chair-person Department of Pathology, and Dr Lowell Stein, Division Director Section of Cardiology and Department of Medicine for their support in facilitating this study.
Footnotes
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The authors received no financial support for the research, authorship, and/or publication of this article.
ORCID iDs: Fakiha Siddiqui https://orcid.org/0000-0002-2219-7049
Bulent Kantarcioglu https://orcid.org/0000-0003-3060-721X
Debra Hoppensteadt https://orcid.org/0000-0001-9342-4213
Jawed Fareed https://orcid.org/0000-0003-3465-2499
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