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.
Subject(s)
COVID-19 , Respiratory Distress Syndrome , Humans , Infant, Newborn , Hospital Mortality , Altitude , COVID-19/complications , ROC Curve , Oxygen , Prognosis , Retrospective StudiesABSTRACT
Introducción. La colonización por microorganismos patógenos de los dispositivos médicos usados en las unidades de cuidados intensivos es un factor de riesgo para el aumento de infecciones asociadas con la atención en salud y, por lo tanto, al de la morbilidad y la mortalidad de los pacientes intubados. En Colombia, no se ha descrito la colonización por hongos de los tubos endotraqueales, con lo cual se podrían considerar nuevas opciones terapéuticas para el beneficio de los pacientes. Objetivo. Describir los hongos que colonizan los tubos endotraqueales de los pacientes en unidades de cuidados intensivos, junto con su perfil de sensibilidad a los antifúngicos. Materiales y métodos. Se realizó un estudio observacional, descriptivo, en dos centros hospitalarios durante 12 meses. Se recolectaron tubos endotraqueales de pacientes de las unidades de cuidados intensivos. Estos fueron procesados para cultivar e identificar hongos, y para establecer su perfil de sensibilidad a los antifúngicos. Resultados. Se analizaron 121 tubos endotraqueales obtenidos de 113 pacientes. De estos, el 41,32 % se encontró colonizado por los hongos Candida albicans (64,61 %), C. no-albicans (30,77 %), Cryptococcus spp. (3,08 %) o mohos (1,54 %). Todos los hongos evaluados presentaron una gran sensibilidad a los antifúngicos, con un promedio del 91 %. Conclusión. Se encontró colonización fúngica en los tubos endotraqueales de pacientes con asistencia respiratoria mecánica. El perfil de sensibilidad en estos pacientes fue favorable. Se requiere un estudio clínico para correlacionar los microorganismos colonizadores y su capacidad de generar infección.
Introduction. Medical device colonization by pathogenic microorganisms is a risk factor for increasing infections associated with health care and, consequently, the morbidity and mortality of intubated patients. In Colombia, fungal colonization of endotracheal tubes has not been described, and this information could lead to new therapeutic options for the benefit of patients. Objective. To describe the colonizing fungi of the endotracheal tubes from patients in the intensive care unit, along with its antifungal sensitivity profile. Materials and methods. We conducted a descriptive, observational study in two health centers for 12 months. Endotracheal tubes were collected from patients in intensive care units. Samples were processed for culture, fungi identification, and antifungal sensitivity profile assessment. Results. A total of 121 endotracheal tubes, obtained from 113 patients, were analyzed: 41.32 % of the tubes were colonized by Candida albicans (64.62%), C. non-albicans (30.77%), Cryptococcus spp. (3.08%) or molds (1.54%). All fungi evaluated showed a high sensitivity to antifungals, with a mean of 91%. Conclusion. Fungal colonization was found in the endotracheal tubes of patients under invasive mechanical ventilation. The antifungal sensitivity profile in these patients was favorable. A clinical study is required to find possible correlations between the colonizing microorganisms and infectivity.
