Distinctive Features of Rotational Thromboelastometry in Patients with Infective Endocarditis Undergoing on-Pump Cardiac Surgery: A Retrospective Propensity Score-matched Observational Study

Abstract

BackgroundThe haemostatic system plays a role in development of valvular vegetations and systemic activation of coagulation, contributing to both thrombosis and consumption coagulopathy. Patients with infective endocarditis undergoing valvular surgery pose unique challenges to the surgical team. Rotational thromboelastometry (ROTEM), a point-of-care viscoelastic clotting test, can help assess coagulation and guide therapy. This retrospective propensity score-matched study explores ROTEM's distinctive features in endocarditis patients compared to others undergoing cardiac surgery.Materials and MethodsA retrospective analysis was performed on patients undergoing valvular surgery between May 31, 2022, and August 31, 2024. ROTEM assessments were conducted during extracorporeal circulation and post-heparin reversal. The study group consisted of patients with endocarditis, while propensity score matching created a control group of patients without endocarditis. The primary outcome was on-pump ROTEM results; secondary outcomes included utilisation of red blood cells (pRBC), fibrinogen concentrate (FC), prothrombin complex concentrate (PCC), fresh frozen plasma (FFP), and platelets.ResultsIn both groups (23 patients each), endocarditis patients had prolonged EXTEM clotting times (136 vs 96 s, P = .001) and higher FIBTEM-A5 clot firmness (19 vs 13 mm, P = .012). They required more PCC (3000 vs 2500 units, P = .014), while transfusions of platelets (P = .281), FFP (P = 1.000), and FC (P = .109) did not differ significantly.ConclusionEndocarditis patients demonstrate distinct viscoelastic profiles with prolonged clotting times and increased clot firmness, necessitating greater PCC supplementation. Further research is warranted to optimise ROTEM target values to balance bleeding and thrombotic risks.

Keywords: ROTEM; coagulation; endocarditis; patient blood management; viscoelastic tests.

Figure 1.

Flowchart of patient identification, matching and division into groups.

Figure 2.

Illustration of the ROTEM results during the end-phase of the cardiopulmonary bypass. Green lines represent the mean clotting times (CT), with IQR represented by whiskers. Black lines represent the mean clot firmness at a given runtime, with IQR represented by the pink (for clot firmness <20 mm) and blue (for clot firmness >20 mm) areas; IE: infective endocarditis.

Figure 3.

Raincloud plots presenting the results of the main statistical analysis. The clouds of points represent single data points in the dataset, box plots: horizontal line represents the median, box represents the IQR, and whiskers minimum and maximum values. One-sided violin plot depicts the distribution of the data.

Figure 4.

Raincloud plots presenting the analysis of transfused blood products and clotting factors. The clouds of points represent single data points in the dataset, box plots: horizontal line represents the median, box represents the IQR, and whiskers minimum and maximum values. One-sided violin plot depicts the distribution of the data.