Development and validation of a scoring system to predict mortality in patients hospitalized with COVID-19: A retrospective cohort study in two large hospitals in Ecuador

Iván Dueñas-Espín, María Echeverría-Mora, Camila Montenegro-Fárez, Manuel Baldeón, Luis Chantong Villacres, Hugo Espejo Cárdenas, Marco Fornasini, Miguel Ochoa Andrade, Carlos Solís

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Objective To develop and validate a scoring system to predict mortality among hospitalized patients with COVID-19. Methods Retrospective cohort study. We analyzed 5,062 analyzed hospitalized patients with COVID-19 treated at two hospitals; one each in Quito and Guayaquil, from February to July 2020. We assessed predictors of mortality using survival analyses and Cox models. We randomly divided the database into two sets: (i) the derivation cohort (n = 2497) to identify predictors of mortality, and (ii) the validation cohort (n = 2565) to test the discriminative ability of a scoring system. After multivariate analyses, we used the final model’s β-coefficients to build the score. Statistical analyses involved the development of a Cox proportional hazards regression model, assessment of goodness of fit, discrimination, and calibration. Results There was a higher mortality risk for these factors: male sex [(hazard ratio (HR) = 1.32, 95% confidence interval (95% CI): 1.03–1.69], per each increase in a quartile of ages (HR = 1.44, 95% CI: 1.24–1.67) considering the younger group (17–44 years old) as the reference, presence of hypoxemia (HR = 1.40, 95% CI: 1.01–1.95), hypoglycemia and hospital hyperglycemia (HR = 1.99, 95% CI: 1.01–3.91, and HR = 1.27, 95% CI: 0.99–1.62, respectively) when compared with normoglycemia, an AST–ALT ratio >1 (HR = 1.55, 95% CI: 1.25–1.92), C-reactive protein level (CRP) of >10 mg/dL (HR = 1.49, 95% CI: 1.07–2.08), arterial pH <7.35 (HR = 1.39, 95% CI: 1.08–1.80) when compared with normal pH (7.35–7.45), and a white blood cell count >10 × 103 per μL (HR = 1.76, 95% CI: 1.35–2.29). We found a strong discriminative ability in the proposed score in the validation cohort [AUC of 0.876 (95% CI: 0.822–0.930)], moreover, a cutoff score ≥39 points demonstrates superior performance with a sensitivity of 93.10%, a specificity of 70.28%, and a correct classification rate of 72.66%. The LR+ (3.1328) and LR- (0.0981) values further support its efficacy in identifying high-risk patients. Conclusion Male sex, increasing age, hypoxemia, hypoglycemia or hospital hyperglycemia, AST–ALT ratio >1, elevated CRP, altered arterial pH, and leucocytosis were factors significantly associated with higher mortality in hospitalized patients with COVID-19. A statistically significant Cox regression model with strong discriminatory power and good calibration was developed to predict mortality in hospitalized patients with COVID-19, highlighting its potential clinical utility.

Idioma originalInglés
Número de artículoe0288106
PublicaciónPLoS ONE
N.º7 July
EstadoPublicada - jul. 2023

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Copyright: © 2023 Dueñas-Espín et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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