Zhongguo shuxue zazhi (Jul 2022)

The clinical study of thromboelas-tography combined with coagulation four items and platelet count to guide platelet transfusion in critically ill patients

  • Shuting JIANG,
  • Lingxiao FENG,
  • Jingli SHI,
  • Tingting XU,
  • Hui YAN,
  • Beizhan YAN

DOI
https://doi.org/10.13303/j.cjbt.issn.1004-549x.2022.07.011
Journal volume & issue
Vol. 35, no. 7
pp. 723 – 727

Abstract

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Objective To explore the clinical value of thromboelas-tography, coagulation four items and platelet count in guiding platelet transfusion in critically ill patients. Methods A total of 188 critically ill patients in Intensive Care Unit of our hospital from January 2020 to January 2022 were selected as subjects, and were divided into study group(n=89) and the control(n=99) according to the presence of bleeding symptoms. T-test was used for comparative analysis between the two groups. Spearman was used to analyze the correlation between TEG, coagulation four items and platelet count, and binary Logistic regression analysis was used to predict the influential factors of bleeding in critically ill patients, ROC curve was used to analyze the guiding value of the above-mentioned indexes for platelet transfusion. Results 1) K and PT values in the study group, above the normal range, were significantly higher than those in the control, while the Angle value, MA value, CI value, FIB value and platelet count were significantly lower than those of the control, among which MA value, CI value and platelet count were below the normal range. 2) TEG, coagulation four items and platelet count were correlated. MA and CI values were positively correlated with platelet count, instead, R and K values were negatively correlated. R value was positively correlated with PT and APTT, CI value, on the contrary, was negatively correlated, K value was positively correlated with PT, while Angle value and MA value were negatively correlated. 3) Binary Logistic regression analysis showed that decreased MA value and decreased platelet count were independent risk factors for predicting bleeding in critically ill patients(P<0.05). 4) ROC curve analysis showed that the areas under ROC curve corresponding to Angle value, MA value, CI value, FIB value and platelet count were 0.866, 0.932, 0.9, 0.838 and 0.987(P<0.05). The sensitivity was highest in platelet count and lowest in FIB. The specificity was highest in MA and lowest in Angle. Compared with the single index, the area under the curve of the combined index(K value, MA value, CI value, PT value and platelet count) was 0.995(P<0.05), Yoden index 0.944, sensitivity 100%, specificity 93.3%, all higher than the individual index. Conclusion Thromboelas-tography combined with coagulation four items and platelet count can be used to accurately predict the critically ill patients with bleeding risk. To guide clinical platelets transfusion, the combined use of indexes, including K value, MA, CI value, PT and platelet count, is superior to separate use of them as the former showed better sensitivity and specificity, demonstrating a good clinical value.

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