Laboratory biomarkers associated with COVID-19 mortality among inpatients in a Peruvian referral hospital

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Aim To evaluate the biochemical and hematological markers associated with the risk of death due to COVID-19 in a clinical cohort with a severe clinical profile. Methods A retrospective study was conducted among 215 anonymized inpatient records from the Hospital Nacional Almanzor Aguinaga Asenjo, Per...

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Detalles Bibliográficos
Autores: Montero, Stephanie, Maguiña, Jorge L., Soto-Becerra, Percy, Failoc-Rojas, Virgilio E., Chira-Sosa, Jorge, Apolaya-Segura, Moisés, Díaz-Vélez, Cristian, Tello-Vera, Stalin
Formato: artículo
Fecha de Publicación:2024
Institución:Seguro Social de Salud
Repositorio:ESSALUD-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.essalud.gob.pe:20.500.12959/5153
Enlace del recurso:https://hdl.handle.net/20.500.12959/5153
https://doi.org/10.1016/j.heliyon.2024.e27251
Nivel de acceso:acceso abierto
Materia:Covid-19
SARS-CoV-2
Biochemical
Hematological
Biomarkers
https://purl.org/pe-repo/ocde/ford#3.03.08
https://purl.org/pe-repo/ocde/ford#3.03.09
Descripción
Sumario:Aim To evaluate the biochemical and hematological markers associated with the risk of death due to COVID-19 in a clinical cohort with a severe clinical profile. Methods A retrospective study was conducted among 215 anonymized inpatient records from the Hospital Nacional Almanzor Aguinaga Asenjo, Peru, between April and June 2020. The association between biomarkers and death due to COVID-19 was assessed using Cox regression, with a multivariable modeling of 1) biochemical and 2) hematological markers. Kaplan-Meier analyses and time-dependent receiver operating characteristic curves were calculated for each associated biomarker (p < 0.05). Results Data analysis of 215 inpatient records revealed an overall mortality rate of 51.30% (95% CI 44.70–58.50), a mean age of 63.90 ± 14.10 years, and a median oxygen saturation of 88% (interquartile range 82–92%). The best-fitted biochemical model included higher levels of C-reactive protein (CRP), D-dimer, fibrinogen, urea, and lactate dehydrogenase. Similarly, the best-fitted hematological model included higher absolute neutrophil and prothrombin time, and lower absolute platelet counts. The best area under the curve values in both models were found to be CRP and D-dimer values (>0.74) and the absolute neutrophil count (0.63). Conclusions Some specific biochemical markers outperformed hematological markers. Evaluated hematological counts analyzed in multivariable models proved to be better markers and could be useful to discriminate COVID-19 patients at high risk of death.
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