A model based on PT-INR and age serves as a promising predictor for evaluating mortality risk in patients with SARS-CoV-2 infection

COVID-19 caused by the coronavirus SARS-CoV-2 has resulted in a global pandemic. Considering some patients with COVID-19 rapidly develop respiratory distress and hypoxemia, early assessment of the prognosis for COVID-19 patients is important, yet there is currently a lack of research on a comprehensive multi-marker approach for disease prognosis assessment. Here, we utilized a large sample of hospitalized individuals with COVID-19 to systematically compare the clinical characteristics at admission and developed a nomogram model that was used to predict prognosis. In all cases, those with pneumonia, older age, and higher PT-INR had a poor prognosis. Besides, pneumonia patients with older age and higher PT-INR also had a poor prognosis. A nomogram model incorporating presence of pneumonia, age and PT-INR could evaluate the prognosis in all patients with SARS-CoV-2 infections well, while a nomogram model incorporating age and PT-INR could evaluate the prognosis in those with pneumonia well. Together, our study establishes a prognostic prediction model that aids in the timely identification of patients with poor prognosis and helps facilitate the improvement of treatment strategies in clinical practice in the future.

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Publication Details

Journal
Frontiers in Cellular and Infection Microbiology
Published
2025-04-03
DOI
https://doi.org/10.3389/fcimb.2025.1499154
Primary Topic
COVID-19 Clinical Research Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

A model based on PT-INR and age serves as a promising predictor for evaluating mortality risk in patients with SARS-CoV-2 infection

Minjie Tang, Wei‐Cheng You, Wei Cai, Xiangdong Tang et al.
Frontiers in Cellular and Infection Microbiology
COVID-19 Clinical Research Studies
article

A model based on PT-INR and age serves as a promising predictor for evaluating mortality risk in patients with SARS-CoV-2 infection

Minjie Tang, Wei‐Cheng You, Wei Cai, Xiangdong Tang, Yan Pan, Zishun Li, Yanping Lin, Ferric C. Fang, Lu Lai, Lin Lin, Liang Wang, FU Ya, Yue Shi, Hongyan Guo, Yongjie Xu, Jialin Song, Zhaopei Guo
article en

Abstract

COVID-19 caused by the coronavirus SARS-CoV-2 has resulted in a global pandemic. Considering some patients with COVID-19 rapidly develop respiratory distress and hypoxemia, early assessment of the prognosis for COVID-19 patients is important, yet there is currently a lack of research on a comprehensive multi-marker approach for disease prognosis assessment. Here, we utilized a large sample of hospitalized individuals with COVID-19 to systematically compare the clinical characteristics at admission and developed a nomogram model that was used to predict prognosis. In all cases, those with pneumonia, older age, and higher PT-INR had a poor prognosis. Besides, pneumonia patients with older age and higher PT-INR also had a poor prognosis. A nomogram model incorporating presence of pneumonia, age and PT-INR could evaluate the prognosis in all patients with SARS-CoV-2 infections well, while a nomogram model incorporating age and PT-INR could evaluate the prognosis in those with pneumonia well. Together, our study establishes a prognostic prediction model that aids in the timely identification of patients with poor prognosis and helps facilitate the improvement of treatment strategies in clinical practice in the future.

Frontiers in Cellular and Infection MicrobiologyVol. 15
Fujian Medical University (CN), First Affiliated Hospital of Fujian Medical University (CN), Fuzhou Maternity and Child Health Care Hospital (CN), Xiamen Chang Gung Hospital (CN), Third Hospital of Changsha (CN)
National Natural Science Foundation of China, Natural Science Foundation of Fujian Province
Good health and well-being
Openalex Percentile: Top 91%
COVID-19 Clinical Research Studies
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