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Prediction model for in-hospital mortality in patients at high altitudes with ARDS due to COVID-19.
Rodriguez Lima, David Rene; Rubio Ramos, Cristhian; Yepes Velasco, Andrés Felipe; Gómez Cortes, Leonardo Andrés; Pinilla Rojas, Darío Isaías; Pinzón Rondón, Ángela María; Ruíz Sternberg, Ángela María.
Afiliação
  • Rodriguez Lima DR; Critical and Intensive Care Medicine, Hospital Universitario Mayor-Méderi, Bogotá, Colombia.
  • Rubio Ramos C; Grupo de Investigación Clínica, Escuela de Medicina y Ciencias de la Salud, Universidad del Rosario, Bogotá, Colombia.
  • Yepes Velasco AF; Critical and Intensive Care Medicine, Hospital Universitario Mayor-Méderi, Bogotá, Colombia.
  • Gómez Cortes LA; Critical and Intensive Care Medicine, Hospital Universitario Mayor-Méderi, Bogotá, Colombia.
  • Pinilla Rojas DI; Critical and Intensive Care Medicine, Hospital Universitario Mayor-Méderi, Bogotá, Colombia.
  • Pinzón Rondón ÁM; Critical and Intensive Care Medicine, Hospital Universitario Mayor-Méderi, Bogotá, Colombia.
  • Ruíz Sternberg ÁM; Grupo de Investigación Clínica, Escuela de Medicina y Ciencias de la Salud, Universidad del Rosario, Bogotá, Colombia.
PLoS One ; 18(10): e0293476, 2023.
Article em En | MEDLINE | ID: mdl-37883460
ABSTRACT

INTRODUCTION:

The diagnosis of acute respiratory distress syndrome (ARDS) includes the ratio of pressure arterial oxygen and inspired oxygen fraction (P/F) ≤ 300, which is often adjusted in locations more than 1,000 meters above sea level (masl) due to hypobaric hypoxemia. The main objective of this study was to develop a prediction model for in-hospital mortality among patients with ARDS due to coronavirus disease 2019 (COVID-19) (C-ARDS) at 2,600 masl with easily available variables at patient admission and to compare its discrimination capacity with a second model using the P/F adjusted for this high altitude.

METHODS:

This study was an analysis of data from patients with C-ARDS treated between March 2020 and July 2021 in a university hospital located in the city of Bogotá, Colombia, at 2,600 masl. Demographic and laboratory data were extracted from electronic records. For the prediction model, univariate analyses were performed to screen variables with p <0.25. Then, these variables were automatically selected with a backward stepwise approach with a significance level of 0.1. The interaction terms and fractional polynomials were also examined in the final model. Multiple imputation procedures and bootstraps were used to obtain the coefficients with the best external validation. In addition, total adjustment of the model and logistic regression diagnostics were performed. The same methodology was used to develop a second model with the P/F adjusted for altitude. Finally, the areas under the curve (AUCs) of the receiver operating characteristic (ROC) curves of the two models were compared.

RESULTS:

A total of 2,210 subjects were included in the final analysis. The final model included 11 variables without interaction terms or nonlinear functions. The coefficients are presented excluding influential observations. The final equation for the model fit was g(x) = age(0.04819)+weight(0.00653)+height(-0.01856)+haemoglobin(-0.0916)+platelet count(-0.003614)+ creatinine(0.0958)+lactate dehydrogenase(0.001589)+sodium(-0.02298)+potassium(0.1574)+systolic pressure(-0.00308)+if moderate ARDS(0.628)+if severe ARDS(1.379), and the probability of in-hospital death was p (x) = e g (x)/(1+ e g (x)). The AUC of the ROC curve was 0.7601 (95% confidence interval (CI) 0.74-0, 78). The second model with the adjusted P/F presented an AUC of 0.754 (95% CI 0.73-0.77). No statistically significant difference was found between the AUC curves (p value = 0.6795).

CONCLUSION:

This study presents a prediction model for patients with C-ARDS at 2,600 masl with easily available admission variables for early stratification of in-hospital mortality risk. Adjusting the P/F for 2,600 masl did not improve the predictive capacity of the model. We do not recommend adjusting the P/F for altitude.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Síndrome do Desconforto Respiratório / COVID-19 Limite: Humans / Newborn Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Colômbia

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Síndrome do Desconforto Respiratório / COVID-19 Limite: Humans / Newborn Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Colômbia