Sars-CoV2 Associated Thromboinflammatory Biomarkers for the Prediction of in-Hospital and Long-Term Mortality in Acute Coronary Syndrome (ACS): Development of a Risk Assessment Score

Background: In hospitalized patients, the SARS-CoV2 infection induces a thromboinflammatory state characterized by endothelial cell dysfunction, platelet activation, and hypercoagulability, leading to an increased risk of thrombosis. In ACS patients with concomitant SARS-CoV2 infection, a higher in-hospital mortality rate is reported; however, no information on the impact of this infection on the thromboinflammatory profile of patients presenting with ACS is currently available. Similarly, no role of hemostatic biomarkers in predicting in-hospital or long-term mortality risk has been established in this population. Aim: In a prospective cohort of ACS patients, we aimed to 1) characterize the contribution of concomitant SARS-CoV2 infection to the thromboinflammatory status by measuring a panel of hemostatic and inflammatory biomarkers; and 2) assess the role of these biomarkers in predicting in-hospital and/or two-year mortality. Methods: Consecutive patients admitted to interventional cardiology for ACS (i.e., ST-elevation myocardial infarction [STEMI], non-STEMI [NSTEMI], or unstable angina [UA]) during the first wave of the pandemic in Bergamo, Italy, from March to May 2020, were enrolled and followed-up for 2 years. Coronary angiography and percutaneous coronary intervention (PCI) data were collected. At admission, patients underwent complete blood cell count and an extensive coagulation profiling, including biomarkers of endothelial-cell activation (von Willebrand factor [vWF] antigen and activity, and ADAMTS13); hypercoagulation (prothrombin fragment 1+2 [F1+2], and D-dimer); and fibrinolytic proteins (tissue plasminogen activator [t-PA], and inhibitor [PAI-1]). In addition, the inflammatory biomarkers fibrinogen, factor VIII (FVIII), neutrophil extracellular traps (NETs), and C reactive protein (CRP) were tested. The occurrence of in-hospital and two-year mortality was prospectively recorded. Results: A total of 99 (76M/23F, median age 67 years) ACS patients (56 STEMI, 34 NSTEMI, 9 UA) were analyzed. Based on nasal swabs, 24 positive and 75 negative SARS-CoV-2 patients were identified. At admission, all patients showed significantly (p<0.05) higher levels of thromboinflammatory biomarkers compared to normal range values. Furthermore, ACS SARS-CoV-2-positive patients displayed significantly (p< 0.05) higher levels of fibrinogen, FVIII, D-dimer, vWF, t-PA, PAI-1, CRP, and NETs, together with significantly (p<0.05) lower levels of lymphocytes, hemoglobin, platelets, and ADAMTS-13 as compared to negative patients. The STEMI SARS-CoV2-positive group exhibited the highest values of the biomarkers. When performed, PCI ended more frequently with partial coronary reperfusion (TIMI grade flow <3) in SARS-CoV2-positive compared to negative patients (p= 0.004). The cumulative incidence of in-hospital mortality was 10%. The univariable analysis identified SARS-CoV-2 positivity as the strongest independent risk factor for mortality (HR 5.9 [95%CI 1.2-31.1]). Regarding the other clinical and laboratory parameters, the multivariable analysis identified dyspnea at presentation, vWF antigen, and leukocytes as independent risk factors for in-hospital mortality. These variables were used to develop a continuous score. Based on this score, the cumulative incidence of mortality was 0 % in the low-risk group, 19% in the intermediate-risk group (95% CI 6.1- 48.2%), and 71% in the high-risk group (95% CI 28.2-113.2%). After a 2-year observation, the mortality rate was 8%. Age was the sole independent risk factor for a 2-year mortality, with a HR of 1.2 (95% CI 1.04-1.3), regardless of the initial SARS-CoV2 status. Conclusions: For the first time, our study demonstrates that SARS-CoV2 infection worsens the thromboinflammatory state of ACS patients. This harmful effect might explain the observed heightened mortality rate among ACS patients concomitantly infected with SARS-CoV-2, which in our study was six times higher than in non-infected ACS patients. Additionally, the proposed scoring system, based on thromboinflammatory biomarkers, has proven effective in identifying ACS patients with elevated risks of in-hospital mortality. The potential role of this scoring system in identifying high-risk patients may possibly extend beyond our study to other highly inflammatory settings.

Authors

Institutions

Publication Details

Journal
Blood
Published
2024-11-05
DOI
https://doi.org/10.1182/blood-2024-199159
Primary Topic
COVID-19 Clinical Research Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sars-CoV2 Associated Thromboinflammatory Biomarkers for the Prediction of in-Hospital and Long-Term Mortality in Acute Coronary Syndrome (ACS): Development of a Risk Assessment Score

Sara Gamba, Giulio Guagliumi, Anna Falanga, Dario Pellegrini et al.
Blood
COVID-19 Clinical Research Studies
article

Sars-CoV2 Associated Thromboinflammatory Biomarkers for the Prediction of in-Hospital and Long-Term Mortality in Acute Coronary Syndrome (ACS): Development of a Risk Assessment Score

Sara Gamba, Giulio Guagliumi, Anna Falanga, Dario Pellegrini, Luigi Fiocca, Laura Russo, Irene Pescetelli, Francesco Moretti, Cristina Verzeroli, Patricia Gómez-Rosas, Aurelia Grosu, Marina Marchetti
article en

Abstract

Background: In hospitalized patients, the SARS-CoV2 infection induces a thromboinflammatory state characterized by endothelial cell dysfunction, platelet activation, and hypercoagulability, leading to an increased risk of thrombosis. In ACS patients with concomitant SARS-CoV2 infection, a higher in-hospital mortality rate is reported; however, no information on the impact of this infection on the thromboinflammatory profile of patients presenting with ACS is currently available. Similarly, no role of hemostatic biomarkers in predicting in-hospital or long-term mortality risk has been established in this population. Aim: In a prospective cohort of ACS patients, we aimed to 1) characterize the contribution of concomitant SARS-CoV2 infection to the thromboinflammatory status by measuring a panel of hemostatic and inflammatory biomarkers; and 2) assess the role of these biomarkers in predicting in-hospital and/or two-year mortality. Methods: Consecutive patients admitted to interventional cardiology for ACS (i.e., ST-elevation myocardial infarction [STEMI], non-STEMI [NSTEMI], or unstable angina [UA]) during the first wave of the pandemic in Bergamo, Italy, from March to May 2020, were enrolled and followed-up for 2 years. Coronary angiography and percutaneous coronary intervention (PCI) data were collected. At admission, patients underwent complete blood cell count and an extensive coagulation profiling, including biomarkers of endothelial-cell activation (von Willebrand factor [vWF] antigen and activity, and ADAMTS13); hypercoagulation (prothrombin fragment 1+2 [F1+2], and D-dimer); and fibrinolytic proteins (tissue plasminogen activator [t-PA], and inhibitor [PAI-1]). In addition, the inflammatory biomarkers fibrinogen, factor VIII (FVIII), neutrophil extracellular traps (NETs), and C reactive protein (CRP) were tested. The occurrence of in-hospital and two-year mortality was prospectively recorded. Results: A total of 99 (76M/23F, median age 67 years) ACS patients (56 STEMI, 34 NSTEMI, 9 UA) were analyzed. Based on nasal swabs, 24 positive and 75 negative SARS-CoV-2 patients were identified. At admission, all patients showed significantly (p<0.05) higher levels of thromboinflammatory biomarkers compared to normal range values. Furthermore, ACS SARS-CoV-2-positive patients displayed significantly (p< 0.05) higher levels of fibrinogen, FVIII, D-dimer, vWF, t-PA, PAI-1, CRP, and NETs, together with significantly (p<0.05) lower levels of lymphocytes, hemoglobin, platelets, and ADAMTS-13 as compared to negative patients. The STEMI SARS-CoV2-positive group exhibited the highest values of the biomarkers. When performed, PCI ended more frequently with partial coronary reperfusion (TIMI grade flow <3) in SARS-CoV2-positive compared to negative patients (p= 0.004). The cumulative incidence of in-hospital mortality was 10%. The univariable analysis identified SARS-CoV-2 positivity as the strongest independent risk factor for mortality (HR 5.9 [95%CI 1.2-31.1]). Regarding the other clinical and laboratory parameters, the multivariable analysis identified dyspnea at presentation, vWF antigen, and leukocytes as independent risk factors for in-hospital mortality. These variables were used to develop a continuous score. Based on this score, the cumulative incidence of mortality was 0 % in the low-risk group, 19% in the intermediate-risk group (95% CI 6.1- 48.2%), and 71% in the high-risk group (95% CI 28.2-113.2%). After a 2-year observation, the mortality rate was 8%. Age was the sole independent risk factor for a 2-year mortality, with a HR of 1.2 (95% CI 1.04-1.3), regardless of the initial SARS-CoV2 status. Conclusions: For the first time, our study demonstrates that SARS-CoV2 infection worsens the thromboinflammatory state of ACS patients. This harmful effect might explain the observed heightened mortality rate among ACS patients concomitantly infected with SARS-CoV-2, which in our study was six times higher than in non-infected ACS patients. Additionally, the proposed scoring system, based on thromboinflammatory biomarkers, has proven effective in identifying ACS patients with elevated risks of in-hospital mortality. The potential role of this scoring system in identifying high-risk patients may possibly extend beyond our study to other highly inflammatory settings.

BloodVol. 144(Supplement 1)
Mexican Social Security Institute (MX), University of Pavia (IT), Maastricht University (NL), Istituto Clinico Sant'Ambrogio (IT), Ospedale Papa Giovanni XXIII (IT), Centro Medico Nacional Siglo XXI (MX), Policlinico San Matteo Fondazione (IT), Istituti di Ricovero e Cura a Carattere Scientifico (IT), University of Milano-Bicocca (IT)
Openalex Percentile: Top 72%
COVID-19 Clinical Research Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.