Verificación secundaria del protocolo Charité-Berlín de SARS-CoV-2 en la UPTC: Integrando la IA en las consideraciones Epidemiológicas

Autores:: Buitrago, Sindy P.
Hernández-Zambrano, Laura J.
Herrera-Martínez, Yimy
Garzón-Ospina, Diego

Tipo de recurso:: Article of journal

Fecha de publicación:: 2025

Institución:: Universidad Pedagógica y Tecnológica de Colombia

Repositorio:: RiUPTC: Repositorio Institucional UPTC

Idioma:

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network_acronym_str	REPOUPTC2
network_name_str	RiUPTC: Repositorio Institucional UPTC
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dc.title.es-ES.fl_str_mv	Verificación secundaria del protocolo Charité-Berlín de SARS-CoV-2 en la UPTC: Integrando la IA en las consideraciones Epidemiológicas
title	Verificación secundaria del protocolo Charité-Berlín de SARS-CoV-2 en la UPTC: Integrando la IA en las consideraciones Epidemiológicas
spellingShingle	Verificación secundaria del protocolo Charité-Berlín de SARS-CoV-2 en la UPTC: Integrando la IA en las consideraciones Epidemiológicas SARS-CoV-2, COVID-19, RT-PCR, Curva ROC, Universidades SARS-CoV-2, COVID-19, RT-PCR, ROC Curve, Universities
title_short	Verificación secundaria del protocolo Charité-Berlín de SARS-CoV-2 en la UPTC: Integrando la IA en las consideraciones Epidemiológicas
title_full	Verificación secundaria del protocolo Charité-Berlín de SARS-CoV-2 en la UPTC: Integrando la IA en las consideraciones Epidemiológicas
title_fullStr	Verificación secundaria del protocolo Charité-Berlín de SARS-CoV-2 en la UPTC: Integrando la IA en las consideraciones Epidemiológicas
title_full_unstemmed	Verificación secundaria del protocolo Charité-Berlín de SARS-CoV-2 en la UPTC: Integrando la IA en las consideraciones Epidemiológicas
title_sort	Verificación secundaria del protocolo Charité-Berlín de SARS-CoV-2 en la UPTC: Integrando la IA en las consideraciones Epidemiológicas
dc.creator.fl_str_mv	Buitrago, Sindy P. Hernández-Zambrano, Laura J. Herrera-Martínez, Yimy Garzón-Ospina, Diego
dc.contributor.author.spa.fl_str_mv	Buitrago, Sindy P. Hernández-Zambrano, Laura J. Herrera-Martínez, Yimy Garzón-Ospina, Diego
dc.subject.none.fl_str_mv	SARS-CoV-2, COVID-19, RT-PCR, Curva ROC, Universidades SARS-CoV-2, COVID-19, RT-PCR, ROC Curve, Universities
topic	SARS-CoV-2, COVID-19, RT-PCR, Curva ROC, Universidades SARS-CoV-2, COVID-19, RT-PCR, ROC Curve, Universities
publishDate	2025
dc.date.accessioned.none.fl_str_mv	2025-07-11 14:41:34 2026-04-16T17:13:11Z
dc.date.available.none.fl_str_mv	2025-07-11 14:41:34
dc.date.issued.none.fl_str_mv	2025-07-11
dc.type.spa.fl_str_mv	Artículo de revista
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dc.identifier.issn.none.fl_str_mv	0121-7488
dc.identifier.uri.none.fl_str_mv	https://repositorio.uptc.edu.co/handle/001/18824
dc.identifier.doi.none.fl_str_mv	10.19053/uptc.01217488.v16.nE.2025.19783
dc.identifier.eissn.none.fl_str_mv	2462-7658
dc.identifier.url.none.fl_str_mv	https://doi.org/10.19053/uptc.01217488.v16.nE.2025.19783
identifier_str_mv	0121-7488 10.19053/uptc.01217488.v16.nE.2025.19783 2462-7658
url	https://repositorio.uptc.edu.co/handle/001/18824 https://doi.org/10.19053/uptc.01217488.v16.nE.2025.19783
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dc.relation.references.none.fl_str_mv	Veugen, J.M.J., et al., Advancing COVID-19 diagnostics: rapid detection of intact SARS-CoV-2 using viability RT-PCR assay. 2024. 12(9): p. e00160-24. Peeling, R.W., et al., Diagnostics for COVID-19: moving from pandemic response to control. Lancet, 2022. 399(10326): p. 757-768. Corman, V.M., etal., Detectionof2019novelcoronavirus (2019-nCoV) by real-time RT-PCR. Euro Surveill, 2020. 25(3). Hirotsu, Y., H. Mochizuki, and M. Omata, Doublequencher probes improve detection sensitivity toward Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in a reverse-transcription polymerase chain reaction (RT-PCR) assay. Journal of Virological Methods, 2020. 284: p. 113926. CDC, CDC 2019-Novel Coronavirus (2019-nCoV) RealTime RT-PCR Diagnostic Panel. 2020. Pan American Health, O. and O. Pan American Health, Laboratory Guidelines for Detection and Diagnosis of the Novel Coronavirus (2019-nCoV) Infection. 2020, PAHO: Washington, D.C. Palacio Rua, K., et al., Validation of a duplex PCR technique using the gen E and RNase P for the diagnosis of SARS-CoV-2. Enferm Infecc Microbiol Clin (Engl Ed), 2021. 40(8): p. 428-35. Park, H., et al., One-Step RT-qPCR for Viral RNA Detection Using Digital Analysis. Front Bioeng Biotechnol, 2022. 10: p. 837838. Kim, M.Y., et al., Highly sensitive and multiplexed one-step RT-qPCR for profiling genes involved in the circadian rhythm using microparticles. Scientific Reports, 2021. 11(1): p. 6463. Hurtado, K.J., Capacidad diagnóstica de laboratorio en Colombia durante el primer año de la pandemia. 2021. INS, Protocolo de verificación (validación secundaria) para pruebas moleculares de PCR en tiempo real (RTqPCR) para la detección del SARS-CoV-2. 2020. Cabrera Perez, R., Fonseca Mendoza, D., Restrepo Fernandez, C. M., Verificación del desempeño (validación secundaria) de la prueba molecular de PCR en tiempo real (RT-qPCR) en la plataforma Vivalytic One®* (Vivalytic SARS-CoV-2) para la detección de SARS-CoV-2 en el punto de atención (POC). 2024. Contreras, H., Gastelbondo-Pastrana, B, Torres, K, Contreras, V, Echeverri De la Hoz, D, Flórez, L, Garay, E y Mattar, S. , Publicación: Resultados del aprendizaje del IIBT durante la pandemia: detección molécular de SARS-CoV-2. 2023. Landis, J.R. and G.G. Koch, The measurement of observer agreement for categorical data. Biometrics, 1977. 33(1): p. 159-74. Oba, J., et al., SARS-CoV-2 RT-qPCR testing of pooled saliva samples: A case study of 824 asymptomatic individuals and a questionnaire survey in Japan. PLOS ONE, 2022. 17(5): p. e0263700. Serrano-Cumplido, A., et al., Aplicación del valor umbral del número de ciclos (Ct) de PCR en la COVID-19. Medicina de Familia. SEMERGEN, 2021. 47(5): p. 337- 341. Reusken, C., et al., Laboratory readiness and response fornovel coronavirus (2019-nCoV)inexpert laboratories in 30 EU/EEA countries, January 2020. Euro Surveill, 2020. 25(6). Leite, J.A., et al., COVID-19 laboratory preparedness and response in the Americas Region: Lessons learned. PLOS ONE, 2021. 16(6): p. e0253334. Castellar-Mendoza, C., et al., Development and Optimization of a Multiplex Real-Time RT-PCR to Detect SARS-CoV-2 in Human Samples. Int J Microbiol, 2024. 2024: p. 4894004. Reina, J. and L. Suarez, [Evaluation of different genes in the RT-PCR detection of SARS-CoV-2 in respiratory samples and its evolution in infection]. Rev Esp Quimioter, 2020. 33(4): p. 292-293. Kostoulas, P., P. Eusebi, and S. Hartnack, Diagnostic Accuracy Estimates for COVID-19 Real-Time Polymerase Chain Reaction and Lateral Flow Immunoassay Tests With Bayesian Latent-Class Models. Am J Epidemiol, 2021. 190(8): p. 1689-1695. Monaghan, T.F., et al., Foundational Statistical Principles in Medical Research: Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value. Medicina (Kaunas), 2021. 57(5). Zou, L., et al., SARS-CoV-2 Viral Load in Upper Respiratory Specimens of Infected Patients. N Engl J Med, 2020. 382(12): p. 1177-1179. Chong, Y.P., et al., SARS-CoV-2 Testing Strategies in the Diagnosis and Management of COVID-19 Patients in Low-Income Countries: A Scoping Review. Mol Diagn Ther, 2023. 27(3): p. 303-320. Chung, Y.-S., et al., Validation of real-time RT-PCR for detection of SARS-CoV-2 in the early stages of the COVID-19 outbreak in the Republic of Korea. Scientific Reports, 2021. 11(1): p. 14817. Miranda, J.P., et al., Analytical and Clinical Validation for RT-qPCR Detection of SARS-CoV-2 Without RNA Extraction. Front Med (Lausanne), 2020. 7: p. 567572. Prado, T., et al., Wastewater-based epidemiology for preventing outbreaks and epidemics in Latin America Lessons from the past and a look to the future. Sci Total Environ, 2023. 865: p. 161210. Mei, X., et al., Artificial intelligence–enabled rapid diagnosis of patients with COVID-19. Nature Medicine, 2020. 26(8): p. 1224-1228. Wang, S., et al., A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19). Eur Radiol, 2021. 31(8): p. 6096-6104. Shariaty, F., et al., Application of Artificial Intelligence for Rapid Prevention of Epidemic Diseases (COVID-19). Research Square, 2022.
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dc.relation.citationvolume.spa.fl_str_mv	16
dc.relation.ispartofjournal.spa.fl_str_mv	Ciencia en Desarrollo
dc.relation.bitstream.none.fl_str_mv	https://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/download/19783/15872
dc.relation.citationedition.spa.fl_str_mv	Núm. 1E , Año 2025 : VII Encuentro Internacional de la Facultad de Ciencias (IMFaS 2024)
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dc.publisher.spa.fl_str_mv	Universidad Pedagógica y Tecnológica de Colombia
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institution	Universidad Pedagógica y Tecnológica de Colombia
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spelling	Buitrago, Sindy P.Hernández-Zambrano, Laura J.Herrera-Martínez, YimyGarzón-Ospina, Diego2025-07-11 14:41:342026-04-16T17:13:11Z2025-07-11 14:41:342025-07-110121-7488https://repositorio.uptc.edu.co/handle/001/1882410.19053/uptc.01217488.v16.nE.2025.197832462-7658https://doi.org/10.19053/uptc.01217488.v16.nE.2025.19783application/pdfUniversidad Pedagógica y Tecnológica de Colombiahttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.esinfo:eu-repo/semantics/openAccessEsta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.http://purl.org/coar/access_right/c_abf2https://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/view/19783SARS-CoV-2, COVID-19, RT-PCR, Curva ROC, UniversidadesSARS-CoV-2, COVID-19, RT-PCR, ROC Curve, UniversitiesVerificación secundaria del protocolo Charité-Berlín de SARS-CoV-2 en la UPTC: Integrando la IA en las consideraciones EpidemiológicasArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleJournal articleinfo:eu-repo/semantics/publishedVersionTexthttp://purl.org/coar/version/c_970fb48d4fbd8a85Veugen, J.M.J., et al., Advancing COVID-19 diagnostics: rapid detection of intact SARS-CoV-2 using viability RT-PCR assay. 2024. 12(9): p. e00160-24.Peeling, R.W., et al., Diagnostics for COVID-19: moving from pandemic response to control. Lancet, 2022. 399(10326): p. 757-768.Corman, V.M., etal., Detectionof2019novelcoronavirus (2019-nCoV) by real-time RT-PCR. Euro Surveill, 2020. 25(3).Hirotsu, Y., H. Mochizuki, and M. Omata, Doublequencher probes improve detection sensitivity toward Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in a reverse-transcription polymerase chain reaction (RT-PCR) assay. Journal of Virological Methods, 2020. 284: p. 113926.CDC, CDC 2019-Novel Coronavirus (2019-nCoV) RealTime RT-PCR Diagnostic Panel. 2020.Pan American Health, O. and O. Pan American Health, Laboratory Guidelines for Detection and Diagnosis of the Novel Coronavirus (2019-nCoV) Infection. 2020, PAHO: Washington, D.C.Palacio Rua, K., et al., Validation of a duplex PCR technique using the gen E and RNase P for the diagnosis of SARS-CoV-2. Enferm Infecc Microbiol Clin (Engl Ed), 2021. 40(8): p. 428-35.Park, H., et al., One-Step RT-qPCR for Viral RNA Detection Using Digital Analysis. Front Bioeng Biotechnol, 2022. 10: p. 837838.Kim, M.Y., et al., Highly sensitive and multiplexed one-step RT-qPCR for profiling genes involved in the circadian rhythm using microparticles. Scientific Reports, 2021. 11(1): p. 6463.Hurtado, K.J., Capacidad diagnóstica de laboratorio en Colombia durante el primer año de la pandemia. 2021.INS, Protocolo de verificación (validación secundaria) para pruebas moleculares de PCR en tiempo real (RTqPCR) para la detección del SARS-CoV-2. 2020.Cabrera Perez, R., Fonseca Mendoza, D., Restrepo Fernandez, C. M., Verificación del desempeño (validación secundaria) de la prueba molecular de PCR en tiempo real (RT-qPCR) en la plataforma Vivalytic One®* (Vivalytic SARS-CoV-2) para la detección de SARS-CoV-2 en el punto de atención (POC). 2024.Contreras, H., Gastelbondo-Pastrana, B, Torres, K, Contreras, V, Echeverri De la Hoz, D, Flórez, L, Garay, E y Mattar, S. , Publicación: Resultados del aprendizaje del IIBT durante la pandemia: detección molécular de SARS-CoV-2. 2023.Landis, J.R. and G.G. Koch, The measurement of observer agreement for categorical data. Biometrics, 1977. 33(1): p. 159-74.Oba, J., et al., SARS-CoV-2 RT-qPCR testing of pooled saliva samples: A case study of 824 asymptomatic individuals and a questionnaire survey in Japan. PLOS ONE, 2022. 17(5): p. e0263700.Serrano-Cumplido, A., et al., Aplicación del valor umbral del número de ciclos (Ct) de PCR en la COVID-19. Medicina de Familia. SEMERGEN, 2021. 47(5): p. 337- 341.Reusken, C., et al., Laboratory readiness and response fornovel coronavirus (2019-nCoV)inexpert laboratories in 30 EU/EEA countries, January 2020. Euro Surveill, 2020. 25(6).Leite, J.A., et al., COVID-19 laboratory preparedness and response in the Americas Region: Lessons learned. PLOS ONE, 2021. 16(6): p. e0253334.Castellar-Mendoza, C., et al., Development and Optimization of a Multiplex Real-Time RT-PCR to Detect SARS-CoV-2 in Human Samples. Int J Microbiol, 2024. 2024: p. 4894004.Reina, J. and L. Suarez, [Evaluation of different genes in the RT-PCR detection of SARS-CoV-2 in respiratory samples and its evolution in infection]. Rev Esp Quimioter, 2020. 33(4): p. 292-293.Kostoulas, P., P. Eusebi, and S. Hartnack, Diagnostic Accuracy Estimates for COVID-19 Real-Time Polymerase Chain Reaction and Lateral Flow Immunoassay Tests With Bayesian Latent-Class Models. Am J Epidemiol, 2021. 190(8): p. 1689-1695.Monaghan, T.F., et al., Foundational Statistical Principles in Medical Research: Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value. Medicina (Kaunas), 2021. 57(5).Zou, L., et al., SARS-CoV-2 Viral Load in Upper Respiratory Specimens of Infected Patients. N Engl J Med, 2020. 382(12): p. 1177-1179.Chong, Y.P., et al., SARS-CoV-2 Testing Strategies in the Diagnosis and Management of COVID-19 Patients in Low-Income Countries: A Scoping Review. Mol Diagn Ther, 2023. 27(3): p. 303-320.Chung, Y.-S., et al., Validation of real-time RT-PCR for detection of SARS-CoV-2 in the early stages of the COVID-19 outbreak in the Republic of Korea. Scientific Reports, 2021. 11(1): p. 14817.Miranda, J.P., et al., Analytical and Clinical Validation for RT-qPCR Detection of SARS-CoV-2 Without RNA Extraction. Front Med (Lausanne), 2020. 7: p. 567572.Prado, T., et al., Wastewater-based epidemiology for preventing outbreaks and epidemics in Latin America Lessons from the past and a look to the future. Sci Total Environ, 2023. 865: p. 161210.Mei, X., et al., Artificial intelligence–enabled rapid diagnosis of patients with COVID-19. Nature Medicine, 2020. 26(8): p. 1224-1228.Wang, S., et al., A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19). Eur Radiol, 2021. 31(8): p. 6096-6104.Shariaty, F., et al., Application of Artificial Intelligence for Rapid Prevention of Epidemic Diseases (COVID-19). Research Square, 2022.441E3916Ciencia en Desarrollohttps://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/download/19783/15872Núm. 1E , Año 2025 : VII Encuentro Internacional de la Facultad de Ciencias (IMFaS 2024)PublicationOREORE.xmltext/xml2878https://repositorio.uptc.edu.co/bitstreams/b948e4ef-3055-420a-a46f-1b15df756c88/download28145cd313c2053c5ae8db9c2b5f109aMD51falseAnonymousREAD001/18824oai:repositorio.uptc.edu.co:001/188242026-10-30 07:03:14.231https://creativecommons.org/licenses/by-nc-nd/4.0/deed.esmetadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCbdigital@metabiblioteca.com

Verificación secundaria del protocolo Charité-Berlín de SARS-CoV-2 en la UPTC: Integrando la IA en las consideraciones Epidemiológicas

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