Abstract
Background: The aim of this study was to construct and validate a simple-to-use model to predict the survival of patients with acute respiratory distress syndrome.Methods: A total of 197 patients with acute respiratory distress syndrome were selected from the Dryad Digital Repository. All eligible individuals were randomly stratified into the training set (n=133) and the validation set (n=64) as 2: 1 ratio. LASSO regression analysis was used to select the optimal predictors, and receiver operating characteristic and calibration curves were used to evaluate accuracy and discrimination of the model. Clinical usefulness of the model was also assessed using decision curve analysis and Kaplan-Meier analysis.Results: Age, albumin, platelet count, PaO2/FiO2, lactate dehydrogenase, high-resolution computed tomography score, and etiology were identified as independent prognostic factors based on LASSO regression analysis; these factors were integrated for the construction of the nomogram. Results of calibration plots, decision curve analysis, and receiver operating characteristic analysis showed that this model has good predictive ability of patient survival in acute respiratory distress syndrome. Moreover, a significant difference in the 28-day survival was shown between the patients stratified into different risk groups (P < 0.001). For convenient application, we also established a web-based calculator (https://huangl.shinyapps.io/ARDSprognosis/).Conclusions: We satisfactorily constructed a simple-to-use model based on seven relevant factors to predict survival and prognosis of patients with acute respiratory distress syndrome. This model can aid personalized treatment and clinical decision-making.
Highlights
Acute respiratory distress syndrome (ARDS) is a clinically and pathophysiologically complex syndrome characterized by rapid progression and devastating hypoxemic respiratory failure [1]
197 eligible ARDS patients with integrated information were randomly stratified into two independent cohorts
To facilitate the clinical application of our findings, we developed a web-based calculator to predict prognosis of ARDS patients according to the nomogram (Figures 3A,B)
Summary
Acute respiratory distress syndrome (ARDS) is a clinically and pathophysiologically complex syndrome characterized by rapid progression and devastating hypoxemic respiratory failure [1]. Many risk factors, such as sepsis, pneumonia, pancreatitis, and major trauma, are associated with the development of ARDS [2]. There has been some progress in ARDS treatment in the last several decades, the prognosis of patients with ARDS are still not satisfactory. The treatment of ARDS predominantly includes mechanical ventilation therapy [4]. The aim of this study was to construct and validate a simple-to-use model to predict the survival of patients with acute respiratory distress syndrome
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