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External Validation of the 4C (Coronavirus Clinical Characterization Consortium) Mortality Score in a Teaching
Karima E Bruno1, Henrique Mussi1, Amanda E Bruno1
1Medicina Clinica, Hospital Universitário Antônio Pedro (Ebserh/Universidade Federal Fluminense), Niteroi, BRA.
Insights
The 4C Mortality Score accurately predicted in-hospital deaths for COVID-19 patients in Brazil. This clinical tool showed excellent discrimination, proving effective for risk stratification in diverse populations.
Area of Science:
- Infectious Diseases
- Clinical Medicine
- Epidemiology
Background:
- The 4C (Coronavirus Clinical Characterization Consortium) Mortality Score aids in predicting COVID-19 in-hospital mortality.
- Validation in Brazil was limited, necessitating local assessment.
- The score uses clinical and laboratory data for risk stratification.
Purpose of the Study:
- To evaluate the accuracy of the 4C Mortality Score in a Brazilian university teaching hospital.
- To determine the score's discriminative ability for COVID-19 mortality in this population.
Main Methods:
- Observational, longitudinal, retrospective study in Rio de Janeiro, Brazil.
- Included 208 hospitalized COVID-19 patients.
- Calculated 4C Mortality Score using age, sex, Charlson index, respiratory rate, oxygen saturation, Glasgow Coma Scale, urea, and CRP.
Main Results:
- Overall mortality was 39.9%.
- Independent predictors of mortality included age, hemoglobin, CRP, mechanical ventilation, and vasopressor use.
- The 4C Mortality Score achieved an area under the receiver operating characteristic curve (AUC-ROC) of 89.9%.
Conclusions:
- The 4C Mortality Score demonstrated excellent discrimination for COVID-19 mortality in a Brazilian teaching hospital.
- The findings support its use for risk stratification in similar settings.
- Further validation across diverse Brazilian populations is warranted.
Abstract:
Background The 4C (Coronavirus Clinical Characterization Consortium) Mortality Score has demonstrated good discrimination in COVID-19 but has not been widely validated in Brazil. The 4C Mortality Score is a clinical tool developed during the COVID-19 pandemic to predict in-hospital mortality for patients admitted with COVID-19. It was derived from a large dataset of hospitalized patients in the United Kingdom and provides a simple yet effective way to stratify patients based on their risk of death. Objective This study aimed to determine the accuracy of the 4C Mortality Score in patients admitted with COVID-19 in a university teaching hospital. Methods The study was observational, longitudinal, and retrospective, conducted in a 180-bed university teaching hospital in Rio de Janeiro, Brazil. We included all patients admitted with COVID-19 and followed them until discharge. The 4C Mortality Score was calculated based on age, sex, Charlson index, respiratory rate, peripheral oxygen saturation (room air), Glasgow Coma Scale, serum urea, and C-reactive protein (CRP) level. The primary outcome was mortality. Results We included 208 participants, with a median age of 63 years. Among them, 111 (53%) were male; 52 (25%) had cardiovascular disease, and 83 (39%) had cancer. Mortality was 39.9%. Independent predictors of mortality were age, hemoglobin, CRP, mechanical ventilation, and the need for vasopressors. The 4C Mortality Score's area under the receiver operating characteristic curve (AUC-ROC) was 89.9%. Conclusion The 4C Mortality Score demonstrated excellent discrimination in a teaching hospital population.
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