Evidence map›Paper›PMID 41004422›Full record

ArticlePloS one2025

The value of combined thromboelastography test for the early prediction of disease severity in patients with haemorrhagic fever of renal syndrome and the construction of a critical model.

Longjiao Dou, Yanxia Huang, Haizhou Miao, Songchang Xiu, Fengmin Hu, Hongyi Chen, Daya Luo, Shumei Wang

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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8 authors.

Longjiao DouThe First Department of Infectious Disease, The Affiliated Infection Hospital of Nanchang University, Nanchang, Jiangxi, China.ORCID https://orcid.org/0009-0005-8543-0089
Yanxia HuangThe First Department of Infectious Disease, The Affiliated Infection Hospital of Nanchang University, Nanchang, Jiangxi, China.
Haizhou MiaoSchool of Clinical Medicine, Nanchang University, Nanchang University, Nanchang, Jiangxi, China.
Songchang XiuThe First Department of Infectious Disease, The Affiliated Infection Hospital of Nanchang University, Nanchang, Jiangxi, China.
Fengmin HuThe First Department of Infectious Disease, The Affiliated Infection Hospital of Nanchang University, Nanchang, Jiangxi, China.
Hongyi ChenThe First Department of Infectious Disease, The Affiliated Infection Hospital of Nanchang University, Nanchang, Jiangxi, China.
Daya LuoThe Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Nanchang University, Nanchang, Jiangxi, China.
Shumei WangThe First Department of Infectious Disease, The Affiliated Infection Hospital of Nanchang University, Nanchang, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThromboelostograms (TEG) are indicators that reflect the dynamic changes in blood coagulation objectively. Compared with traditional coagulation tests, TEG are easy to perform; imparting a head start in determining patients'coagulation status. The aim of this study was to explore the role of thromboelastography as an early predictor of disease severity and as a prognostic factor in patients with haemorrhagic fever of renal syndrome (HFRS).

methodsThis was a retrospective study in which we collected clinical data from 342 patients with HFRS who were hospitalized from January 2017 to January 2021. The predictive value of laboratory parameters for HFRS criticalization was assessed via receiver operating characteristic (ROC) curves. After that, a model of criticalization was developed using stepwise analysis, subsequently, the model was evaluated and validated internally as well as externally. This study was approved by the Ethics Committee of the Hospital.

resultsThe study population was categorized into critical and noncritical groups according to their condition during hospitalization, with a median age of 52.00 (39.00-61.50) years for the critical group and 39.00 (16.00-53.25) years for the noncritical group. Both groups had a large proportion of male patients (65.3% and 72.3%, respectively). The median duration of hospitalization was 15.00 (3.50-25.00) days in the critical group and 13.00 (10.00-17.25) days in noncritical group. In the critical group 40.8% of patients died. The incidence of bleeding was greater in critical patients (51.0%) than in noncritical patients (15.1%). The coagulation indices: CI, K, MA, R and angle were significantly different between the two groups (p < 0.05). Critical patients had higher levels of K and R and lower levels of CI, MA and angle. Multivariate analysis revealed that K, ALB, CK, SCR, angle, WBC and LYM were independently associated with disease severity in patients with HFRS. ROC curve analysis revealed that the criticality model equation had an AUC of 0.9058, a sensitivity of 88.9% and a specificity of 80.2%, which were better than that of any single parameter in predicting the patient's outcome. The internal validation C index was 0.866, the GOF P value was 0.825, and the external validation AUC was 0.762, with a sensitivity of 71.4% and a specificity of 74.2%. The results of the calibration plots indicated that there was some agreement between the model-estimated HFRS critical illness rates and the final observed critical illness rates in the study population. Decision curve analysis indicated that the model had significant clinical utility and comparable net benefit over a range of threshold probabilities.

conclusionCritical HFRS have significantly abnormal coagulation function and high incidence of bleeding associated with poor outcome. A criticalization prediction model constructed on the basis of thromboelastography indices in early stages of the disease has a good predictive ability and may be helpful in the early identification of critically ill patients for timely clinical intervention and treatment.

Indexed as

Hemorrhagic Fever with Renal SyndromeThrombelastographyAdultFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesROC CurveSeverity of Illness Index

Identifiers

PMID41004422
PMCPMC12469219

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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.