Analysis of the predictive factors for critical illness of COVID-19 during treatment - Relationship between serum zinc level and critical illness of COVID-19
Objectives: Because most severely ill patients with COVID-19 in our hospital showed zinc deficiency, we aimed to examine the relationship between the patient’s serum zinc level and severe cases of COVID-19. Methods: Serum zinc <70 µg/dL was defined as the criterion for hypozincemia, and patients...
- Autores:
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2020
- Institución:
- Universidad de Bogotá Jorge Tadeo Lozano
- Repositorio:
- Expeditio: repositorio UTadeo
- Idioma:
- eng
- OAI Identifier:
- oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/13599
- Acceso en línea:
- https://doi.org/10.1016/j.ijid.2020.09.008
http://hdl.handle.net/20.500.12010/13599
- Palabra clave:
- COVID-19
Serum Zinc
Predictive Factors
Logistic Regression Analysis
Critical Illness
Japan
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
- Rights
- License
- Abierto (Texto Completo)
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oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/13599 |
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|
dc.title.spa.fl_str_mv |
Analysis of the predictive factors for critical illness of COVID-19 during treatment - Relationship between serum zinc level and critical illness of COVID-19 |
title |
Analysis of the predictive factors for critical illness of COVID-19 during treatment - Relationship between serum zinc level and critical illness of COVID-19 |
spellingShingle |
Analysis of the predictive factors for critical illness of COVID-19 during treatment - Relationship between serum zinc level and critical illness of COVID-19 COVID-19 Serum Zinc Predictive Factors Logistic Regression Analysis Critical Illness Japan Síndrome respiratorio agudo grave COVID-19 SARS-CoV-2 Coronavirus |
title_short |
Analysis of the predictive factors for critical illness of COVID-19 during treatment - Relationship between serum zinc level and critical illness of COVID-19 |
title_full |
Analysis of the predictive factors for critical illness of COVID-19 during treatment - Relationship between serum zinc level and critical illness of COVID-19 |
title_fullStr |
Analysis of the predictive factors for critical illness of COVID-19 during treatment - Relationship between serum zinc level and critical illness of COVID-19 |
title_full_unstemmed |
Analysis of the predictive factors for critical illness of COVID-19 during treatment - Relationship between serum zinc level and critical illness of COVID-19 |
title_sort |
Analysis of the predictive factors for critical illness of COVID-19 during treatment - Relationship between serum zinc level and critical illness of COVID-19 |
dc.subject.spa.fl_str_mv |
COVID-19 Serum Zinc Predictive Factors Logistic Regression Analysis Critical Illness Japan |
topic |
COVID-19 Serum Zinc Predictive Factors Logistic Regression Analysis Critical Illness Japan Síndrome respiratorio agudo grave COVID-19 SARS-CoV-2 Coronavirus |
dc.subject.lemb.spa.fl_str_mv |
Síndrome respiratorio agudo grave COVID-19 SARS-CoV-2 Coronavirus |
description |
Objectives: Because most severely ill patients with COVID-19 in our hospital showed zinc deficiency, we aimed to examine the relationship between the patient’s serum zinc level and severe cases of COVID-19. Methods: Serum zinc <70 µg/dL was defined as the criterion for hypozincemia, and patients continuously with serum zinc <70 µg/dL were classified in the hypozincemia cohort. To evaluate whether hypozincemia could be a predictive factor for critical illness of COVID-19, we performed the multivariate analysis by employing logistic regression analysis. Results: Prolonged hypozincemia was found to be a risk factor for a severe case of COVID-19. In evaluating the relationship between the serum zinc level and severity of patients with COVID-19 by multivariate logistic regression analysis, critical illness can be predicted through the sensitivity and false specificity of an ROC curve with an error rate of 10.3% and AUC of 94.2% by only two factors: serum zinc value (P=0.020) and LDH value (P=0.026). Conclusions: Proper management of the prediction results in this study can contribute to the establishment and maintenance of a safe medical system, taking the arrival of the second wave and spread of COVID Journal Pre-proof -19 in the future into consideration. |
publishDate |
2020 |
dc.date.accessioned.none.fl_str_mv |
2020-09-22T19:41:00Z |
dc.date.available.none.fl_str_mv |
2020-09-22T19:41:00Z |
dc.date.created.none.fl_str_mv |
2020 |
dc.type.local.spa.fl_str_mv |
Artículo |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
format |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.identifier.issn.spa.fl_str_mv |
1201-9712 |
dc.identifier.other.spa.fl_str_mv |
https://doi.org/10.1016/j.ijid.2020.09.008 |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/20.500.12010/13599 |
dc.identifier.doi.spa.fl_str_mv |
https://doi.org/10.1016/j.ijid.2020.09.008 |
identifier_str_mv |
1201-9712 |
url |
https://doi.org/10.1016/j.ijid.2020.09.008 http://hdl.handle.net/20.500.12010/13599 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.local.spa.fl_str_mv |
Abierto (Texto Completo) |
rights_invalid_str_mv |
Abierto (Texto Completo) http://purl.org/coar/access_right/c_abf2 |
dc.format.extent.spa.fl_str_mv |
42 páginas |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
International Journal of Infectious Diseases |
dc.source.spa.fl_str_mv |
reponame:Expeditio Repositorio Institucional UJTL instname:Universidad de Bogotá Jorge Tadeo Lozano |
instname_str |
Universidad de Bogotá Jorge Tadeo Lozano |
institution |
Universidad de Bogotá Jorge Tadeo Lozano |
reponame_str |
Expeditio Repositorio Institucional UJTL |
collection |
Expeditio Repositorio Institucional UJTL |
bitstream.url.fl_str_mv |
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spelling |
2020-09-22T19:41:00Z2020-09-22T19:41:00Z20201201-9712https://doi.org/10.1016/j.ijid.2020.09.008http://hdl.handle.net/20.500.12010/13599https://doi.org/10.1016/j.ijid.2020.09.008Objectives: Because most severely ill patients with COVID-19 in our hospital showed zinc deficiency, we aimed to examine the relationship between the patient’s serum zinc level and severe cases of COVID-19. Methods: Serum zinc <70 µg/dL was defined as the criterion for hypozincemia, and patients continuously with serum zinc <70 µg/dL were classified in the hypozincemia cohort. To evaluate whether hypozincemia could be a predictive factor for critical illness of COVID-19, we performed the multivariate analysis by employing logistic regression analysis. Results: Prolonged hypozincemia was found to be a risk factor for a severe case of COVID-19. In evaluating the relationship between the serum zinc level and severity of patients with COVID-19 by multivariate logistic regression analysis, critical illness can be predicted through the sensitivity and false specificity of an ROC curve with an error rate of 10.3% and AUC of 94.2% by only two factors: serum zinc value (P=0.020) and LDH value (P=0.026). Conclusions: Proper management of the prediction results in this study can contribute to the establishment and maintenance of a safe medical system, taking the arrival of the second wave and spread of COVID Journal Pre-proof -19 in the future into consideration.42 páginasapplication/pdfengInternational Journal of Infectious Diseasesreponame:Expeditio Repositorio Institucional UJTLinstname:Universidad de Bogotá Jorge Tadeo LozanoCOVID-19Serum ZincPredictive FactorsLogistic Regression AnalysisCritical IllnessJapanSíndrome respiratorio agudo graveCOVID-19SARS-CoV-2CoronavirusAnalysis of the predictive factors for critical illness of COVID-19 during treatment - Relationship between serum zinc level and critical illness of COVID-19Artículohttp://purl.org/coar/resource_type/c_2df8fbb1Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2Yasui, YukakoYasui, HiroyukiSuzuki, KumikoSaitou, TakakoYamamoto, YoshikiIshizaka, ToshihikoNishida, KoujiYoshihara, ShingoGohma, IwaoOgawa, YoshihikoLICENSElicense.txtlicense.txttext/plain; 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