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Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
Published on: November 10, 2023
A Simplified Comorbidity Evaluation Predicting Clinical Outcomes Among Patients With Coronavirus Disease 2019
Jessica J Kirby1,2, Sajid Shaikh3,2, David P Bryant1
1Department of Emergency Medicine, JPS Health Network, 1500 S. Main St., Fort Worth, TX 76104, USA.
Insights
A new simplified comorbidity evaluation, the COVID-related high-risk chronic condition (CCC) score, accurately predicts clinical outcomes in COVID-19 patients. This CCC score performs comparably to established indices like the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI).
Area of Science:
- Medical Research
- Public Health
- Epidemiology
Background:
- Coronavirus disease 2019 (COVID-19) presents varied clinical outcomes.
- Patient comorbidities, particularly multiple chronic diseases, are linked to worse COVID-19 prognosis.
- Existing comorbidity indices may not fully capture COVID-19 specific risks.
Purpose of the Study:
- To develop and validate a simplified comorbidity evaluation for predicting COVID-19 clinical outcomes.
- To assess the accuracy of this new evaluation against established comorbidity indices (CCI, ECI).
- To identify key predictors of severe COVID-19 outcomes such as hospital admission, ICU admission, ventilation, and mortality.
Main Methods:
- A retrospective observational study of emergency department patients with COVID-19.
- Development of a simplified comorbidity evaluation: COVID-related high-risk chronic condition (CCC).
- Comparison of CCC prediction accuracy against Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) using logistic regression and C-statistics.
Main Results:
- The study analyzed 3,864 COVID-19 positive patients from 90,549 ED visits.
- The CCC evaluation demonstrated strong correlation with hospital admission, ICU admission, ventilation, and in-hospital mortality.
- CCC showed a C-statistic of 0.73 for predicting in-hospital mortality, comparable to CCI (0.72) and ECI (0.71).
Conclusions:
- The simplified COVID-related high-risk chronic condition (CCC) evaluation accurately predicts clinical outcomes in COVID-19 patients.
- The predictive performance of CCC is not inferior to established comorbidity indices (CCI, ECI).
- CCC offers a potentially valuable tool for risk stratification in COVID-19 management.
Background:
Patients with coronavirus disease 2019 (COVID-19) have shown a range of clinical outcomes. Previous studies have reported that patient comorbidities are predictive of worse clinical outcomes, especially when patients have multiple chronic diseases. We aim to: 1) derive a simplified comorbidity evaluation and determine its accuracy of predicting clinical outcomes (i.e., hospital admission, intensive care unit (ICU) admission, ventilation, and in-hospital mortality); and 2) determine its performance accuracy in comparison to well-established comorbidity indexes.
Methods:
This was a single-center retrospective observational study. We enrolled all emergency department (ED) patients with COVID-19 from March 1, 2020, to December 31, 2020. A simplified comorbidity evaluation (COVID-related high-risk chronic condition (CCC)) was derived to predict different clinical outcomes using multivariate logistic regressions. In addition, chronic diseases included in the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) were scored, and its accuracy of predicting COVID-19 clinical outcomes was also compared with the CCC.
Results:
Data were retrieved from 90,549 ED patient visits during the study period, among which 3,864 patients were COVID-19 positive. Forty-seven point nine percent (1,851/3,864) were admitted to the hospital, 9.4% (364) patients were admitted to the ICU, 6.2% (238) received invasive mechanical ventilation, and 4.6% (177) patients died in the hospital. The CCC evaluation correlated well with the four studied clinical outcomes. The adjusted odds ratios of predicting in-hospital death from CCC was 2.84 (95% confidence interval (CI): 1.81 - 4.45, P < 0.001). C-statistics of CCC predicting in-hospital all-cause mortality was 0.73 (0.69 - 0.76), similar to those of the CCI's (0.72) and ECI's (0.71, P = 0.0513).
Conclusions:
CCC can accurately predict clinical outcomes among patients with COVID-19. Its performance accuracies for such predictions are not inferior to those of the CCI or ECI's.
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