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. 2024 May 2:11:1356283.
doi: 10.3389/fmed.2024.1356283. eCollection 2024.

Time to maximum amplitude of thromboelastography can predict mortality in patients with severe COVID-19: a retrospective observational study

Lincui Zhong  1 , Qingwei Lin  1 , Longping He  1 , Dongmei Liu  2   3 , Lin Zhu  2   4 , Qingbo Zeng  1 , Jingchun Song  1   2
Affiliations

Time to maximum amplitude of thromboelastography can predict mortality in patients with severe COVID-19: a retrospective observational study

Lincui Zhong et al. Front Med (Lausanne). .

Abstract

Objective: To predict mortality in severe patients with COVID-19 at admission to the intensive care unit (ICU) using thromboelastography (TEG).

Methods: This retrospective, two-center, observational study involved 87 patients with PCR-and chest CT-confirmed severe COVID-19 who were admitted to at Wuhan Huoshenshan Hospital and the 908th Hospital of Chinese PLA Logistic Support Force between February 2020 and February 2023. Clinic demographics, laboratory results, and outcomes were compared between those who survived and those who died during hospitalization.

Results: Thromboelastography showed that of the 87 patients, 14 were in a hypercoagulable state, 25 were in a hypocoagulable state, and 48 were normal, based on the time to maximum amplitude (TMA). Patients who died showed significantly lower α angle, but significantly longer R-time, K-time and TMA than patients who survived. Random forest selection showed that K-time, TMA, prothrombin time (PT), international normalized ratio (INR), D-dimer, C-reactive protein (CRP), aspartate aminotransferase (AST), and total bilirubin (Tbil) were significant predictors. Multivariate logistic regression identified that TMA and CRP were independently associated with mortality. TMA had a greater predictive power than CRP levels based on time-dependent AUCs. Patients with TMA ≥ 26.4 min were at significantly higher risk of mortality (hazard ratio 3.99, 95% Confidence Interval, 1.92-8.27, p < 0.01).

Conclusion: TMA ≥26.4 min at admission to ICU may be an independent predictor of in-hospital mortality for patients with severe COVID-19.

Keywords: coronavirus; critical illness; mortality; thromboelastography; time to maximum amplitude.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Machine learning analysis and selection of biomarker for prognosis.
Figure 2
Figure 2
Correlation matrix.
Figure 3
Figure 3
Time-dependent ROC for TMA and CRP for predicting mortality. AUC, Area under the curve; ROC, Receiver operating curves.
Figure 4
Figure 4
Kaplan–Meier survival curve of resected in severe COVID-19 patients with long TMA (≥26.4 min) and short TMA (<26.4 min).
See this image and copyright information in PMC

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