| Autor: |
González-Escamilla, Moisés, Pérez-Ibave, Diana Cristina, Burciaga-Flores, Carlos Horacio, Ortiz-Murillo, Vanessa Natali, Ramírez-Correa, Genaro A., Rodríguez-Niño, Patricia, Piñeiro-Retif, Rafael, Rodríguez-Gutiérrez, Hazyadee Frecia, Alcorta-Nuñez, Fernando, González-Guerrero, Juan Francisco, Vidal-Gutiérrez, Oscar, Garza-Rodríguez, María Lourdes |
| Předmět: |
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| Zdroj: |
Healthcare (2227-9032); Mar2022, Vol. 10 Issue 3, p462-N.PAG, 12p |
| Abstrakt: |
An early detection tool for latent COVID-19 infections in oncology staff and patients is essential to prevent outbreaks in a cancer center. (1) Background: In this study, we developed and implemented two early detection tools for the radiotherapy area to identify COVID-19 cases opportunely. (2) Methods: Staff and patients answered a questionnaire (electronic and paper surveys, respectively) with clinical and epidemiological information. The data were collected through two online survey tools: Real-Time Tracking (R-Track) and Summary of Factors (S-Facts). Cut-off values were established according to the algorithm models. SARS-CoV-2 qRT-PCR tests confirmed the positive algorithms individuals. (3) Results: Oncology staff members (n = 142) were tested, and 14% (n = 20) were positives for the R-Track algorithm; 75% (n = 15) were qRT-PCR positive. The S-Facts Algorithm identified 7.75% (n = 11) positive oncology staff members, and 81.82% (n = 9) were qRT-PCR positive. Oncology patients (n = 369) were evaluated, and 1.36% (n = 5) were positive for the Algorithm used. The five patients (100%) were confirmed by qRT-PCR. (4) Conclusions: The proposed early detection tools have proved to be a low-cost and efficient tool in a country where qRT-PCR tests and vaccines are insufficient for the population. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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