| Autor: |
Eduardo Nieto-Ortega, Alejandro Maldonado Arenal, Lupita Escudero-Roque, Diana Ali Macedo-Falcon, Ana Elena Escorcia-Saucedo, Adalberto León Ángel, Alejandro Durán Méndez, Karla García-Callejas, Sergio Hernández-Islas, Gabriel Romero-López, Ángel Raúl Hernández-Romero, Daniela Pérez-Ortega, Estephany Rodríguez-Segura, Daniela Montaño‑Olmos, Jeffrey Hernández-Muñoz, Samuel Rodríguez-Peña, Montserrat Magos, María José Rueda-Medécigo, Yanira Lizeth Aco-Cuamani, Nazareth García-Chávez, Ana Lizeth García-Otero, Analiz Mejía-Rangel, Valeria Gutiérrez Losada, Miguel Cova-Bonilla, Alma Delia Aguilar-Arroyo, Araceli Sandoval-García, Eneyda Martínez-Francisco, Blanca Azucena Vázquez-García, Alberto Navarrete Peón |
| Rok vydání: |
2023 |
| DOI: |
10.21203/rs.3.rs-2347185/v1 |
| Popis: |
Prognostic scales may help to optimize the use of hospital resources, which may be of prime interest in the context of a fast spreading pandemics. Nonetheless, such tools are underdeveloped in the context of COVID-19. In the present article we asked whether accurate prognostic scales could be developed to optimize the use of hospital resources. We retrospectively studied 467 files of hospitalized patients after COVID-19. The odds ratios for 16 different biomarkers were calculated, and those that were significantly associated were screened by a Pearson’s correlation, and such index was used to establish the mathematical function for each marker. The scales to predict the need for hospitalization, intensive-care requirement and mortality had enhanced sensitivities (0.91 CI 0.87–0.94; 0.96 CI 0.94–0.98; 0.96 CI 0.94–0.98; all with p p |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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