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Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study
Yi Bai Xiong1, Ya Xin Tian1, Yan Ma1
1Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
Insights
A new risk score using neutrophil to lymphocyte ratio, albumin, and chest CT scans can predict severe coronavirus disease 2019 (COVID-19) early. This helps in timely treatment for patients at high risk of severe illness.
Area of Science:
- Infectious Diseases
- Pulmonology
- Critical Care Medicine
Background:
- Early identification of severe coronavirus disease 2019 (COVID-19) is crucial for effective patient management.
- Limited studies exist on clinical risk score systems for predicting severe COVID-19 progression.
Purpose of the Study:
- To develop and validate a clinical risk score system for predicting severe illness in COVID-19 patients.
- To optimize treatment strategies through early risk stratification.
Main Methods:
- Retrospective single-center study of 295 COVID-19 patients.
- Utilized demographic, clinical, and laboratory data.
- Employed LASSO regression and logistic regression for prognostic factor screening and risk score development, validated using 10-fold cross-validation.
Main Results:
- Identified three key predictors for severe COVID-19: neutrophil to lymphocyte ratio, albumin levels, and chest computed tomography abnormalities.
- The developed risk score demonstrated an Area Under the Curve (AUC) of 0.822 in the validation cohort.
- Neutrophil to lymphocyte ratio (OR, 1.27) and chest CT abnormalities (OR, 2.01) increased severe illness risk, while albumin (OR, 0.76) decreased it.
Conclusions:
- The developed risk score effectively predicts the potential for severe illness in COVID-19 patients at an early stage.
- Neutrophil to lymphocyte ratio, albumin, and chest CT findings are significant indicators for severe COVID-19 development.
- This tool can aid clinicians in early risk assessment and timely intervention for COVID-19 patients.
Objective:
Early triage of patients with coronavirus disease 2019 (COVID-19) is pivotal in managing the disease. However, studies on the clinical risk score system of the risk factors for the development of severe disease are limited. Hence, we conducted a clinical risk score system for severe illness, which might optimize appropriate treatment strategies.
Methods:
We conducted a retrospective, single-center study at the JinYinTan Hospital from January 24, 2020 to March 31, 2020. We evaluated the demographic, clinical, and laboratory data and performed a 10-fold cross-validation to split the data into a training set and validation set. We then screened the prognostic factors for severe illness using the least absolute shrinkage and selection operator (LASSO) and logistic regression, and finally conducted a risk score to estimate the probability of severe illness in the training set. Data from the validation set were used to validate the score.
Results:
A total of 295 patients were included. From 49 potential risk factors, 3 variables were measured as the risk score: neutrophil to lymphocyte ratio ( OR, 1.27; 95% CI, 1.15-1.39), albumin ( OR, 0.76; 95% CI, 0.70-0.83), and chest computed tomography abnormalities ( OR, 2.01; 95% CI, 1.41-2.86) and the AUC of the validation cohort was 0.822 (95% CI, 0.7667-0.8776).
Conclusion:
This report may help define the potential of developing severe illness in patients with COVID-19 at an early stage, which might be related to the neutrophil to lymphocyte ratio, albumin, and chest computed tomography abnormalities.
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