Evidence map›Paper›PMID 38756947›Full record

ArticleFrontiers in medicine2024

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

Lincui Zhong, Qingwei Lin, Longping He, Dongmei Liu, Lin Zhu, Qingbo Zeng, Jingchun Song

Abstract read
In one paragraph

Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Observational
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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Lincui ZhongIntensive Care Unit, The 908th Hospital of Chinese PLA Logistic Support Force, Nanchang, Jiangxi, China.
Qingwei LinIntensive Care Unit, The 908th Hospital of Chinese PLA Logistic Support Force, Nanchang, Jiangxi, China.
Longping HeIntensive Care Unit, The 908th Hospital of Chinese PLA Logistic Support Force, Nanchang, Jiangxi, China.
Dongmei LiuIntensive Care Unit, Huoshenshan Hospital, Wuhan, Hubei, China.
Lin ZhuIntensive Care Unit, Huoshenshan Hospital, Wuhan, Hubei, China.
Qingbo ZengIntensive Care Unit, The 908th Hospital of Chinese PLA Logistic Support Force, Nanchang, Jiangxi, China.
Jingchun SongIntensive Care Unit, The 908th Hospital of Chinese PLA Logistic Support Force, Nanchang, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Indexed as

coronaviruscritical illnessmortalitythromboelastographytime to maximum amplitude

Identifiers

PMID38756947
PMCPMC11097111

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.