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Does the Charlson comorbidity index help predict the risk of death in COVID-19 patients?
1Department of Infectious Diseases and Clinical Microbiology, SBU Umraniye Training and Research Hospital, Istanbul, Turkey.
Insights
The Charlson comorbidity index (CCI) effectively predicts COVID-19 mortality. Higher CCI scores significantly correlate with increased death risk in COVID-19 patients, highlighting the importance of managing comorbidities.
Area of Science:
- Medical research
- Epidemiology
- Public health
Background:
- Comorbidities significantly impact disease prognosis and treatment choices.
- The Charlson comorbidity index (CCI) is a widely used metric for assessing comorbid conditions.
Purpose of the Study:
- To evaluate the predictive value of the Charlson comorbidity index (CCI) score for mortality in patients diagnosed with COVID-19.
Main Methods:
- Retrospective analysis of 1,559 hospitalized COVID-19 patients (April-December 2020).
- Comorbidity severity categorized using CCI scores (0, 1-2, 3-4, 5-6, ≥7).
- Logistic regression and ANOVA used to analyze mortality factors and group differences.
Main Results:
- Overall mortality rate was 4.49% (70 deaths).
- Deceased patients had a higher average CCI score (3.8±2.7) compared to survivors (1.3±1.9).
- Each point increase in CCI score correlated with a 2.5% rise in mortality risk; CCI ≥4 predicted mortality with 87.2% sensitivity.
Conclusions:
- The CCI is a simple, valid tool for assessing COVID-19 mortality risk.
- Managing comorbidities is crucial for improving outcomes in COVID-19 patients.
- Early identification and treatment of comorbidities can enhance patient prognosis.
Objective:
Comorbidities are diseases that coexist with a disease of interest or an index disease, which can directly affect the prognosis of the disease of interest or indirectly affect the choice of treatment. The Charlson comorbidity index (CCI) is the most widely used comorbidity index. In this study, it was aimed to examine the predictive role of the CCI score on the mortality of patients with COVID-19.
Methods:
We have retrospectively analyzed COVID-19 patients whose diagnosis was confirmed by PCR and who were hospitalized in two centers between April 2020 and December 2020. The severity of comorbidity of the patients was categorized into five groups according to the CCI score: CCI score 0, CCI score 1-2, CCI score 3-4, CCI score 5-6, and CCI score ≥7. Factors affecting mortality and differences between groups classified by CCI were determined by logistic regression analysis and one-way analysis of variance.
Results:
A total of 1,559 COVID-19 patients were included in the study and 70 (4.49%) patients had deceased. Half of the study population (n=793, 50.9%) had different comorbidities. The CCI score was 3.8±2.7 in deceased patients and 1.3±1.9 in surviving individuals. There was a positive correlation between CCI scores and mortality in COVID-19 patients, with each point increase in the CCI score increasing the risk of death by 2.5%. CCI score of 4 and above predicted mortality with 87.2% sensitivity and 97.9% negative predictive value. Five (0.6%) of 766 patients with CCI scores of 0, 16 (3.6%) of 439 patients with CCI scores of 1-2, 13 (6.9%) of 189 patients with CCI scores of 3-4, and a CCI score of 5, 13 (15.7%) of 83 patients with -6 and 23 (28.0%) of 82 patients with a CCI score of ≥7 died.
Conclusion:
CCI is a simple, easily applicable, and valid method for classifying comorbidities and estimating COVID-19 mortality. The close relationship between the CCI score and mortality reveals the reality of how important vaccination is, especially in this group of patients. Increasing awareness of potential comorbidities in COVID-19 patients can provide insight into the disease and to improve outcomes by identifying and treating patients earlier and more effectively.
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