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Prognosis models for severe and critical COVID-19 based on the Charlson and Elixhauser comorbidity indices
Wei Zhou1, Xiaoyi Qin2, Xiang Hu3
1Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
Insights
This study developed prognostic scoring models for severe COVID-19 patients using comorbidities. Higher scores predict longer hospital stays and critical illness, aiding in patient management.
Area of Science:
- Infectious Diseases
- Epidemiology
- Clinical Medicine
Background:
- Corona Virus Disease 2019 (COVID-19) emerged as a significant global health crisis.
- Severe and critical COVID-19 cases necessitate effective prognostic tools for management.
- Comorbidities play a crucial role in disease severity and patient outcomes.
Purpose of the Study:
- To establish prognostic scoring models for severe and critical COVID-19 patients.
- To evaluate the association between comorbidity indices and patient outcomes, including length of stay and critical illness.
- To provide a tool for graded patient management based on prognostic scores.
Main Methods:
- Retrospective data collection from 51 severe or critical COVID-19 patients.
- Utilized Charlson (CCI), Elixhauser (ECI), and adjusted versions (ASCCI, ASECI) comorbidity indices.
- Multivariate analysis to identify predictors of prolonged hospital length of stay (LOS) and critical illness.
Main Results:
- The average hospital LOS was 22.82 days, with 37.3% hospitalized over 24 days.
- Older age and smoking were identified as predictors of longer LOS.
- Increasing CCI, ASCCI, and ASECI scores significantly correlated with longer hospital LOS and critical illness outcomes.
Conclusions:
- Prognostic scoring models based on comorbidities can effectively predict outcomes in severe COVID-19.
- These models can assist physicians in identifying high-risk patients requiring closer monitoring.
- The findings support the use of comorbidity-based scores for graded management of COVID-19 patients.
Abstract:
Background: Corona Virus Disease 2019 (COVID-19) has become a global pandemic. This study established prognostic scoring models based on comorbidities and other clinical information for severe and critical patients with COVID-19. Material and Methods: We retrospectively collected data from 51 patients diagnosed as severe or critical COVID-19 who were admitted between January 29, 2020, and February 18, 2020. The Charlson (CCI), Elixhauser (ECI), and age- and smoking-adjusted Charlson (ASCCI) and Elixhauser (ASECI) comorbidity indices were used to evaluate the patient outcomes. Results: The mean hospital length of stay (LOS) of the COVID-19 patients was 22.82 ± 12.32 days; 19 patients (37.3%) were hospitalized for more than 24 days. Multivariate analysis identified older age (OR 1.064, P = 0.018, 95%CI 1.011-1.121) and smoking (OR 3.696, P = 0.080, 95%CI 0.856-15.955) as positive predictors of a long LOS. There were significant trends for increasing hospital LOS with increasing CCI, ASCCI, and ASECI scores (OR 57.500, P = 0.001, 95%CI 5.687-581.399; OR 71.500, P = 0.001, 95%CI 5.689-898.642; and OR 19.556, P = 0.001, 95%CI 3.315-115.372, respectively). The result was similar for the outcome of critical illness (OR 21.333, P = 0.001, 95%CI 3.565-127.672; OR 13.000, P = 0.009, 95%CI 1.921-87.990; OR 11.333, P = 0.008, 95%CI 1.859-69.080, respectively). Conclusions: This study established prognostic scoring models based on comorbidities and clinical information, which may help with the graded management of patients according to prognosis score and remind physicians to pay more attention to patients with high scores.
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