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Risk Factors and Predictive Model for Mortality of Hospitalized COVID-19 Elderly Patients from a Tertiary Care
Mallika Chuansangeam1, Bunyarat Srithan1, Pattharawin Pattharanitima1
1Department of Internal Medicine, Faculty of Medicine, Thammasat University Hospital, Thammasat University, Pathum Thani 12120, Thailand.
Insights
A new risk score accurately identifies elderly COVID-19 patients at high risk of death. This tool aids early clinical decisions for hospitalized seniors with COVID-19, improving mortality prediction.
Area of Science:
- Gerontology
- Infectious Diseases
- Clinical Medicine
Background:
- Elderly patients with COVID-19 face a high mortality risk.
- Early identification of high-risk individuals is crucial for timely clinical intervention.
- This study focuses on predicting in-hospital mortality in this demographic.
Purpose of the Study:
- To identify risk factors for all-cause in-hospital mortality in elderly COVID-19 patients.
- To develop a predictive scoring system for mortality risk assessment.
- To validate the accuracy of the developed risk score.
Main Methods:
- Retrospective review of 138 hospitalized elderly COVID-19 patients (age > 60).
- Multivariate logistic regression to identify independent predictors of mortality.
- Development of a weighted integer risk score based on identified variables.
Main Results:
- Four key variables (age, respiratory rate, glomerular filtration rate, stroke history) were identified as predictors.
- The developed scoring system demonstrated high accuracy with an AUROC of 0.9415.
- A risk score exceeding 213 was established as a threshold for high mortality risk.
Conclusions:
- A simple predictive risk score can accurately assess mortality risk upon admission.
- This tool offers a valuable initial assessment for hospitalized elderly COVID-19 patients.
- The scoring system supports informed clinical decision-making for high-risk individuals.
Abstract:
Background: Early detection of elderly patients with COVID-19 who are at high risk of mortality is vital for appropriate clinical decisions. We aimed to evaluate the risk factors associated with all-cause in-hospital mortality among elderly patients with COVID-19. Methods: In this retrospective study, the medical records of elderly patients aged over 60 who were hospitalized with COVID-19 at Thammasat University Hospital from 1 July to 30 September 2021 were reviewed. Multivariate logistic regression was used to identify independent predictors of mortality. The sum of weighted integers was used as a total risk score for each patient. Results: In total, 138 medical records of patients were reviewed. Four identified variables based on the odds ratio (age, respiratory rate, glomerular filtration rate and history of stroke) were assigned a weighted integer and were developed to predict mortality risk in hospitalized elderly patients. The AUROC of the scoring system were 0.9415 (95% confidence interval, 0.9033-0.9716). The optimized scoring system was developed and a risk score over 213 was considered a cut-off point for high mortality risk. Conclusions: A simple predictive risk score provides an initial assessment of mortality risk at the time of admission with a high degree of accuracy among hospitalized elderly patients with COVID-19.
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