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The Age-AST-D Dimer (AAD) Regression Model Predicts Severe COVID-19 Disease.
Higuera-de-la-Tijera, Fátima; Servín-Caamaño, Alfredo; Reyes-Herrera, Daniel; Flores-López, Argelia; Robiou-Vivero, Enrique J A; Martínez-Rivera, Felipe; Galindo-Hernández, Victor; Rosales-Salyano, Victor H; Casillas-Suárez, Catalina; Chapa-Azuela, Oscar; Chávez-Morales, Alfonso; Jiménez-Bobadilla, Billy; Hernández-Medel, María L; Orozco-Zúñiga, Benjamín; Zacarías-Ezzat, Jed R; Camacho, Santiago; Pérez-Hernández, José L.
  • Higuera-de-la-Tijera F; Multidisciplinary Team for the Attention and Care of Patients with COVID-19, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Servín-Caamaño A; Gastroenterology and Hepatology Department, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Reyes-Herrera D; Multidisciplinary Team for the Attention and Care of Patients with COVID-19, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Flores-López A; Internal Medicine Department, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Robiou-Vivero EJA; Multidisciplinary Team for the Attention and Care of Patients with COVID-19, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Martínez-Rivera F; Internal Medicine Department, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Galindo-Hernández V; Multidisciplinary Team for the Attention and Care of Patients with COVID-19, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Rosales-Salyano VH; Internal Medicine Department, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Casillas-Suárez C; Multidisciplinary Team for the Attention and Care of Patients with COVID-19, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Chapa-Azuela O; Internal Medicine Department, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Chávez-Morales A; Multidisciplinary Team for the Attention and Care of Patients with COVID-19, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Jiménez-Bobadilla B; Internal Medicine Department, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Hernández-Medel ML; Multidisciplinary Team for the Attention and Care of Patients with COVID-19, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Orozco-Zúñiga B; Internal Medicine Department, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Zacarías-Ezzat JR; Multidisciplinary Team for the Attention and Care of Patients with COVID-19, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Camacho S; Internal Medicine Department, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
  • Pérez-Hernández JL; Multidisciplinary Team for the Attention and Care of Patients with COVID-19, Hospital General de México ¨Dr. Eduardo Liceaga¨, Mexico City, Mexico.
Dis Markers ; 2021: 6658270, 2021.
Artículo en Inglés | MEDLINE | ID: covidwho-1159714
ABSTRACT

AIM:

Coronavirus disease (COVID-19) ranges from mild clinical phenotypes to life-threatening conditions like severe acute respiratory syndrome (SARS). It has been suggested that early liver injury in these patients could be a risk factor for poor outcome. We aimed to identify early biochemical predictive factors related to severe disease development with intensive care requirements in patients with COVID-19.

METHODS:

Data from COVID-19 patients were collected at admission time to our hospital. Differential biochemical factors were identified between seriously ill patients requiring intensive care unit (ICU) admission (ICU patients) versus stable patients without the need for ICU admission (non-ICU patients). Multiple linear regression was applied, then a predictive model of severity called Age-AST-D dimer (AAD) was constructed (n = 166) and validated (n = 170).

RESULTS:

Derivation cohort from 166 patients included, there were 27 (16.3%) ICU patients that showed higher levels of liver injury markers (P < 0.01) compared with non-ICU patients alanine aminotrasnferase (ALT) 225.4 ± 341.2 vs. 41.3 ± 41.1, aspartate aminotransferase (AST) 325.3 ± 382.4 vs. 52.8 ± 47.1, lactic dehydrogenase (LDH) 764.6 ± 401.9 vs. 461.0 ± 185.6, D-dimer (DD) 7765 ± 9109 vs. 1871 ± 4146, and age 58.6 ± 12.7 vs. 49.1 ± 12.8. With these finding, a model called Age-AST-DD (AAD), with a cut-point of <2.75 (sensitivity = 0.797 and specificity = 0.391, c - statistic = 0.74; 95%IC 0.62-0.86, P < 0.001), to predict the risk of need admission to ICU (OR = 5.8; 95% CI 2.2-15.4, P = 0.001), was constructed. Validation cohort in 170 different patients, the AAD model < 2.75 (c - statistic = 0.80 (95% CI 0.70-0.91, P < 0.001) adequately predicted the risk (OR = 8.8, 95% CI 3.4-22.6, P < 0.001) to be admitted in the ICU (27 patients, 15.95%).

CONCLUSIONS:

The elevation of AST (a possible marker of early liver injury) along with DD and age efficiently predict early (at admission time) probability of ICU admission during the clinical course of COVID-19. The AAD model can improve the comprehensive management of COVID-19 patients, and it could be useful as a triage tool to early classify patients with a high risk of developing a severe clinical course of the disease.
Asunto(s)

Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Aspartato Aminotransferasas / COVID-19 Tipo de estudio: Estudio de cohorte / Estudio observacional / Estudio pronóstico Límite: Adulto / Femenino / Humanos / Masculino / Middle aged Idioma: Inglés Revista: Dis Markers Asunto de la revista: Bioquímica Año: 2021 Tipo del documento: Artículo País de afiliación: 2021

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Aspartato Aminotransferasas / COVID-19 Tipo de estudio: Estudio de cohorte / Estudio observacional / Estudio pronóstico Límite: Adulto / Femenino / Humanos / Masculino / Middle aged Idioma: Inglés Revista: Dis Markers Asunto de la revista: Bioquímica Año: 2021 Tipo del documento: Artículo País de afiliación: 2021