metricas
covid
Buscar en
Annals of Hepatology
Toda la web
Inicio Annals of Hepatology Aspartate aminotransferase as predictor of severity in SARSCoV-2 infection: line...
Información de la revista
Vol. 19. Núm. S1.
Abstracts of the 2020 Annual meeting of the Mexican Association of Hepatology (AMH) – XV Congreso Nacional de Hepatología (23-25 de julio)
Páginas 22 (septiembre 2020)
Compartir
Compartir
Descargar PDF
Más opciones de artículo
Vol. 19. Núm. S1.
Abstracts of the 2020 Annual meeting of the Mexican Association of Hepatology (AMH) – XV Congreso Nacional de Hepatología (23-25 de julio)
Páginas 22 (septiembre 2020)
46
Open Access
Aspartate aminotransferase as predictor of severity in SARSCoV-2 infection: linear regression model
Visitas
867
A. Servín-Caamaño, D. Reyes-Herrera, A. Flores-López, E.J.A. Robiou-Vivero, F. Martínez-Rivera, V. Galindo-Hernández, C. Casillas-Suárez, O. Chapa-Azuela, A. Chávez-Morales, V.H. Rosales-Salyano, B. Jiménez-Bobadilla, M.L. Hernández-Medel, B. Orozco-Zúñiga, J.R. Zacarías-Ezzat, S. Camacho-Hernández, J.L. Pérez-Hernández, F. Higuera-de la Tijera
Hospital General de México “Dr. Eduardo Liceaga”, México
Este artículo ha recibido

Under a Creative Commons license
Información del artículo
Texto completo
Descargar PDF
Estadísticas
Figuras (1)
Tablas (1)
Texto completo

Background and aim: Some patients with SARSCov-2 infection develop severe disease (SARS); however, the factors associated with severity are not yet fully understood. Some reports indicate that liver injury may be a poor prognostic factor. AIM: To identify the biochemical factors related to the development of SARS with mechanical ventilation (MV) requirement in patients with SARSCov-2 and COVID-19.

Methods. Type of study: Observational. Cohort study. Procedure: Data from COVID-19 patients were collected at admission time to a tertiary care center. Differential factors were identified between seriously ill SARS+MV patients versus stable patients without MV. Transformation to the natural logarithm of significant variables was performed and multiple linear regression was applied, then a predictive model of severity called AAD (Age-AST-D dimer) was constructed.

Results: 166 patients were included, 114(68.7%) men, mean age 50.6±13.3 years-old, 27(16.3%) developed SARS+MV. In the comparative analysis between those with SARS+MV versus stable patients without MV we found significant raises of ALT (225.4±341.2 vs. 41.3±41.1; P=0.003), AST 325.3±382.4 vs. 52.8±47.1; P=0.001), LDH (764.6±401.9 vs. 461.0±185.6; P=0.001), D dimer (7765±9109 vs. 1871±4146; P=0.003), age (58.6±12.7 vs. 49.1±12.8; P=0-001). The results of the regression are shown in the Table, where model 3 was the one that best explained the development of SARS+MV; with these variables was constructed the model called AAD, where: [AAD=3.896+ln(age)x-0.218+ln(AST)x-0.185+ln(DD)x0.070], where a value ≤ 2.75 had sensitivity=0.797 and 1-specificity=0.391, AUROC=0.74 (95%CI: 0.62-0.86; P<0.0001), to predict the risk of developing SARS+MV (OR=5.8, 95%CI: 2.2-15.4; P=0.001).

Conclusions: Elevation of AST (probable marker of liver damage) is an important predictor of progression to SARS, together with elevation of D-dimer and age early (at admission) and efficiently predict which patients will potentially require MV.

Conflicts of interest: The authors have no conflicts of interest to declare.

Multiple linear regression models predictive of SARS development in patients with COVID-19 and requirement for intubation
ModelNon-standarized Coeficients  Standarized CoeficientsP  95% Confidence Interval for BColinearity statistics
  Error Desv.  Beta      Inferior limit  Superior limit  Tolerance  VIF 
2.721  .131    .000  2.462  2.980     
  AST  −.229  .033  −.512  .000  −.293  −.164  1.000  1.000 
3.161  .198    .000  2.770  3.551     
  AST  −.194  .034  −.435  .000  −.261  −.127  .878  1.139 
  DD  −.081  .028  −.221  .004  −.135  −.026  .878  1.139 
3.896  .414    .000  3.077  4.714     
  AST  −.185  .034  −.413  .000  −.252  −.118  .860  1.163 
  DD  −.070  .028  −.190  .014  −.125  −.014  .844  1.185 
  Age  −.218  .108  −.148  .046  −.433  −.004  .915  1.093 

AST, aspartate aminotransferase; C, constant; DD, D dimer; VIF, variance inflation factors.

Resume of the model:

R=0.512, r2=0.262, r2 adjusted=0.256, standard error=0.331.

R=0.552, r2=0.305, r2 adjusted=0.294, standard error=0.322.

R=0.570, r2=0.325, r2 adjusted=0.310, standard error=0.318. Durbin-Watson=1.53.

AAD MODEL TO PREDICT SEVERE FORM (SARS)+INTUBATION

Descargar PDF
Opciones de artículo
es en pt

¿Es usted profesional sanitario apto para prescribir o dispensar medicamentos?

Are you a health professional able to prescribe or dispense drugs?

Você é um profissional de saúde habilitado a prescrever ou dispensar medicamentos

Quizás le interese:
10.1016/j.aohep.2020.08.044
No mostrar más