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

## TL;DR

A model using PT-INR and age helps predict mortality risk in SARS-CoV-2 patients, aiding in early prognosis assessment.

## Contribution

A novel nomogram model combining PT-INR and age is developed for predicting prognosis in SARS-CoV-2 patients.

## Key findings

- Patients with pneumonia, older age, and higher PT-INR had a poor prognosis.
- A nomogram model with pneumonia, age, and PT-INR effectively predicts prognosis in all SARS-CoV-2 patients.
- A model with age and PT-INR effectively predicts prognosis in pneumonia patients.

## 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.