Objective
To analyse the accuracy of commonly used risk scores (PSI and CURB‐65) in predicting mortality and need for ICU admission in Covid‐19.
Material and methods
Prospective study of patients diagnosed with Covid‐19 pneumonia. Patients were followed until home discharge or death. PSI, CURB‐65, SMART‐COP and MuLBSTA severity scores were assessed on admission. Risk scores were related to mortality and ICU admission.
Results
About 249 patients, 143 males (57.4%) were included. The mean age was 65.6 + 16.1 years. Factors associates with mortality in the multivariate analysis were age > 80 years (OR: 13.9; 95% CI 3.8‐51.1) (P = .000), lymphocytes < 800 (OR: 2.9; CI 95% 1.1‐7‐9) (P = .040), confusion (OR: 6.3; 95% CI 1.6‐24.7) (P = .008) and NT‐proBNP > 500 pg/mL (OR: 10.1; 95% CI 1.1‐63.1) (P = .039). In predicting mortality, the PSI score: AUC 0.874 (95% CI 0.808‐0.939) and the CURB‐65 score: AUC 0.852 (95% CI 0.794‐0.909) were the ones that obtained the best results. In the need for ICU admission, the SMART‐COP score: AUC 0.749 (95% CI 0.695‐0.820) and the MuLBSTA score: AUC 0.777 (95% CI 0.713‐0.840) were the ones that obtained better results, with significant differences with PSI and CURB‐65. The scores with the lowest value for ICU admission prediction were PSI with AUC of 0.620 (95% CI 0.549‐0.690) and CURB‐65 with AUC of 0.604 (95% CI 0.528‐0.680).
Conclusions
Prognosis scores routinely used for CAP (PSI and CURB‐65) were good predictors for mortality in patients with Covid‐19 CAP but not for need of hospitalisation or ICU admission. In the evaluation of Covid‐19 pneumonia, we need scores that allow to decide the appropriate level of care.
RESUMENLa Cadena Datos-Información-Conocimiento (DIC), denominada "Jerarquía de la Información" o "Pirámide del Conocimiento", es uno de los modelos más importantes en la Gestión de la Información y la Gestión del Conocimiento. Por lo general, la estructuración de la cadena se ha ido definiendo como una arquitectura en la que cada elemento se levanta sobre el elemento inmediatamente inferior; sin embargo no existe un consenso en la definición de los elementos, ni acerca de los procesos que transforman un elemento de un nivel a uno del siguiente nivel. En este artículo se realiza una revisión de la Cadena Datos-Información-Conocimiento examinando las definiciones más relevantes sobre sus elementos y sobre su articulación en la literatura, para sintetizar las acepciones más comunes. Se analizan los elementos de la Cadena DIC desde la semiótica de Peirce; enfoque que nos permite aclarar los significados e identificar las diferencias, las relaciones y los roles que desempeñan en la cadena desde el punto de vista del pragmatismo. Finalmente se propone una definición de la Cadena DIC apoyada en las categorías triádicas de signos y la semiosis ilimitada de Peirce, los niveles de sistemas de signos de Stamper y las metáforas de Zeleny. Palabras clave: Cadena Datos-Información-Conocimiento, pragmatismo, semiótica, signo, semiosis.A Review of the Data-Information-Knowledge Chain from the Pragmatism of Peirce
ABSTRACTThe Data-Information-Knowledge (DIC) Chain, known as "Information Hierarchy" or "Knowledge Pyramid", is one of the most important models in Information Management and Knowledge Management. In general, the structure of the DIC Chain has been defined as an architecture in which each
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