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

SCIENTIFIC REPORTS(2020)

引用 9|浏览4
暂无评分
摘要
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.
更多
查看译文
关键词
Biomarkers,Infectious diseases,Science,Humanities and Social Sciences,multidisciplinary
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要