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Laboratory findings and a combined multifactorial approach to predict death in critically ill patients with COVID-19:
1Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Insights
Laboratory findings like decreased lymphocyte ratio, elevated blood urea nitrogen, and raised D-dimer are key indicators for predicting death in severe coronavirus disease 2019 (COVID-19) patients. A new scoring system effectively identifies at-risk individuals.
Area of Science:
- Infectious Diseases
- Clinical Medicine
- Biochemistry
Background:
- Coronavirus disease 2019 (COVID-19) poses a significant global health threat, particularly in severe and critical cases.
- Understanding laboratory predictors of mortality is crucial for managing COVID-19 patients.
Purpose of the Study:
- To identify laboratory findings associated with mortality in severe/critical COVID-19 patients.
- To develop and validate a scoring system for predicting death in these patients.
Main Methods:
- Retrospective observational study of 336 adult COVID-19 patients with severe or critical illness.
- Logistic regression analysis to identify mortality-related factors.
- Validation of a combined prediction model using receiver operating characteristic curves.
Main Results:
- 34 out of 336 patients (10.1%) died during hospitalization.
- Decreased lymphocyte ratio (Lymr), elevated blood urea nitrogen (BUN), and raised D-dimer (DD) were significantly associated with death.
- The prediction model achieved 100.0% sensitivity and 97.2% specificity.
Conclusions:
- Decreased Lymr, elevated BUN, and raised DD are key indicators of mortality in critically ill COVID-19 patients.
- A validated scoring system can effectively predict clinical outcomes and mortality risk.
Abstract:
To describe the laboratory findings of cases of death with coronavirus disease 2019 (COVID-19) and to establish a scoring system for predicting death, we conducted this single-centre, retrospective, observational study including 336 adult patients (≥18 years old) with severe or critically ill COVID-19 admitted in two wards of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology in Wuhan, who had definite outcomes (death or discharge) between 1 February 2020 and 13 March 2020. Single variable and multivariable logistic regression analyses were performed to identify mortality-related factors. We combined multiple factors to predict mortality, which was validated by receiver operating characteristic curves. As a result, in a total of 336 patients, 34 (10.1%) patients died during hospitalisation. Through multivariable logistic regression, we found that decreased lymphocyte ratio (Lymr, %) (odds ratio, OR 0.574, P < 0.001), elevated blood urea nitrogen (BUN) (OR 1.513, P = 0.009), and raised D-dimer (DD) (OR 1.334, P = 0.002) at admission were closely related to death. The combined prediction model was developed by these factors with a sensitivity of 100.0% and specificity of 97.2%. In conclusion, decreased Lymr, elevated BUN, and raised DD were found to be in association with death outcomes in critically ill patients with COVID-19. A scoring system was developed to predict the clinical outcome of these patients.
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