Prognostic model for death from COVID-19
Introduction: Tools have been used to predict the risk of COVID-19, but none have evaluated their external validity. Objective: To evaluate the capacity of a model, based on prognostic factors, to predict the risk of dying from COVID-19. Material and Methods: A cohort analytical study was carried ou...
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Universidad de Ciencias Médicas de La Habana,
2024-03-01T00:00:00Z.
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LEADER | 00000 am a22000003u 4500 | ||
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001 | doaj_07f5636b1c6f4abb819dee265fa91f9c | ||
042 | |a dc | ||
100 | 1 | 0 | |a Alexis Álvarez Aliaga |e author |
700 | 1 | 0 | |a Julio César González Aguilera |e author |
700 | 1 | 0 | |a Alexis Suárez Quesada |e author |
700 | 1 | 0 | |a Andrés José Quesada Vázquez |e author |
700 | 1 | 0 | |a Liannys Lidia Naranjo Flores |e author |
245 | 0 | 0 | |a Prognostic model for death from COVID-19 |
260 | |b Universidad de Ciencias Médicas de La Habana, |c 2024-03-01T00:00:00Z. | ||
500 | |a 1729-519X | ||
520 | |a Introduction: Tools have been used to predict the risk of COVID-19, but none have evaluated their external validity. Objective: To evaluate the capacity of a model, based on prognostic factors, to predict the risk of dying from COVID-19. Material and Methods: A cohort analytical study was carried out on patients with COVID-19 at the "Carlos Manuel de Céspedes" provincial general hospital in the Bayamo municipality, province of Granma, from January 1st, 2020 to March 31st, 2023. Confirmed COVID-19 patients were selected. Death was defined as the dependent variable and sociodemographic variables were considered as independent variables for evaluation, including: toxic habits, comorbidity, biomarkers, phenotypes, and prognostic scales. Results: The Cox proportional regression model demonstrated that the factors associated with the prognosis of death were: classifying phenotype 5 (HR= 6.41; 95% CI= 1.49 to 13.44; p= 0.015); history of arterial hypertension (HR= 2.01; 95% CI= 1.34 to 2.98; p= 0.001); and the RALE scale at 4 or more points (HR= 1.94; 95% CI=1, 47 to 7.90; p= 0.047). The discriminative capacity of the model (C statistic = 0.891) and its calibration were adequate (X2 = 5.384; p = 0.637). Conclusions: The predictive capacity and calibration of the model were adequate. The model can be used as a clinical and epidemiological surveillance instrument, by staging the risk of dying in the most vulnerable subjects. | ||
546 | |a EN | ||
546 | |a ES | ||
690 | |a covid-19 | ||
690 | |a factores pronósticos | ||
690 | |a modelos pronósticos | ||
690 | |a mortalidad | ||
690 | |a Medicine (General) | ||
690 | |a R5-920 | ||
690 | |a Public aspects of medicine | ||
690 | |a RA1-1270 | ||
655 | 7 | |a article |2 local | |
786 | 0 | |n Revista Habanera de Ciencias Médicas, Vol 22, Iss 5, Pp e5614-e5614 (2024) | |
787 | 0 | |n https://revhabanera.sld.cu/index.php/rhab/article/view/5614 | |
787 | 0 | |n https://doaj.org/toc/1729-519X | |
856 | 4 | 1 | |u https://doaj.org/article/07f5636b1c6f4abb819dee265fa91f9c |z Connect to this object online. |