Assessment of aPTT-based clot waveform analysis for the detection of haemostatic changes in different types of infections

Abstract

Infections cause varying degrees of haemostatic dysfunction which can be detected by clot waveform analysis (CWA), a global haemostatic marker. CWA has been shown to predict poor outcomes in severe infections with disseminated intravascular coagulopathy. The effect of less severe bacterial and viral infections on CWA has not been established. We hypothesized that different infections influence CWA distinctively. Patients admitted with bacterial infections, dengue and upper respiratory tract viral infections were recruited if they had an activated partial thromboplastin time (aPTT) measured on admission. APTT-based CWA was performed on Sysmex CS2100i automated analyser using Dade Actin FSL reagent. CWA parameters [(maximum velocity (min1), maximum acceleration (min2) and maximum deceleration (max2)] were compared against control patients. Infected patients (n = 101) had longer aPTT than controls (n = 112) (34.37 ± 7.72 s vs 27.80 ± 1.59 s, p < 0.001), with the mean (± SD) aPTT longest in dengue infection (n = 36) (37.99 ± 7.93 s), followed by bacterial infection (n = 52) (33.96 ± 7.33 s) and respiratory viral infection (n = 13) (29.98 ± 3.92 s). Compared to controls (min1; min2; max2) (5.53 ± 1.16%/s; 0.89 ± 0.19%/s 2 ; 0.74 ± 0.16%/s 2 ), bacterial infection has higher CWA results (6.92 ± 1.60%/s; 1.04 ± 0.28%/s 2 ; 0.82 ± 0.24%/s 2 , all p < 0.05); dengue infection has significantly lower CWA values (3.93 ± 1.32%/s; 0.57 ± 0.17%/s 2 ; 0.43 ± 0.14%/s 2 , all p < 0.001) whilst respiratory virus infection has similar results (6.19 ± 1.32%/s; 0.95 ± 0.21%/s 2 ; 0.73 ± 0.18%/s 2 , all p > 0.05). CWA parameters demonstrated positive correlation with C-reactive protein levels (min1: r = 0.54, min2: r = 0.44, max2: r = 0.34; all p < 0.01). Different infections affect CWA distinctively. CWA could provide information on the haemostatic milieu triggered by infection and further studies are needed to better define its application in this area.

Hemostasis Proteins in Invasive Meningococcal and Nonmeningococcal Infections: A Prospective Multicenter Study

“…In our study, we expected to find more severe hemostatic disturbances in meningococcal infections, but only higher levels of thrombomodulin were observed for meningococcal infections. Similar to our study, Tan et al ( 44 ) found that patients with different types of bacterial infections had alterations in hemostatic mechanisms measured by clot waveform analysis. Differences between Gram-positive infections and Gram-negative infections were also not observed in their study, although they included a different variety of pathogens and did not include N. meningitidis .…”

Clinical and laboratory features of hypercoagulability in COVID-19 and other respiratory viral infections amongst predominantly younger adults with few comorbidities

“…To further evaluate the thrombotic potential in COVID-19, we analysed available CWA parameters as a global haemostatic assessment. It has been reported that CWA parameters differ in various types of infections 34 and increased CWA is associated with hypercoagulability 35 , 36 . Our findings suggest that there were no significant changes in the overall haemostatic functions in mild COVID-19 but severe COVID-19 was associated with a prothrombotic state and this hypercoagulability gradually normalizes during the convalescent phase.…”

Differences in the Composition of Activated Partial Thromboplastin Time (APTT) Reagents Affect Clot Waveform Analysis

“…Some trials have comprehensively used CWA to predict hemostatic effects in emicizumab prophylaxis. 7,18,19 Further, CWA can be used to obtain specific parameters even in infections without disseminated intravascular coagulation (DIC), to distinguish bacterial or viral infection and facilitate selection and early administration of optimal antibiotics for each infection 20 ; moreover, CWA has been associated with the diagnosis of COVID-19, pathological conditions, and prognosis prediction. 21,22 CWA can reflect the entire process of clot formation and is expected to be clinically applied for the differential diagnosis of diseases, severity determination, prognosis prediction, and treatment monitoring in the future.…”