scholarly journals A Simple-to-Use Web-Based Calculator for Survival Prediction in Acute Respiratory Distress Syndrome

2021 ◽  
Vol 8 ◽  
Author(s):  
Yong Liu ◽  
Jian Liu ◽  
Liang Huang
Keyword(s):  
Regression Analysis ◽  
Acute Respiratory Distress Syndrome ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Operating Characteristic ◽  
Distress Syndrome ◽  
Curve Analysis ◽  
Lasso Regression ◽  
Web Based ◽  
Decision Curve Analysis

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.

scholarly journals A Simple-To-Use Nomogram to Predict Survival After Acute Respiratory Distress Syndrome

2020 ◽  
Author(s):  
Yong Liu ◽  
Jiang Liu ◽  
Liang Huang
Keyword(s):  
Regression Analysis ◽  
Acute Respiratory Distress Syndrome ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Distress Syndrome ◽  
Curve Analysis ◽  
Lasso Regression ◽  
Decision Curve Analysis

Abstract Background: The aim of this study to construct and validate a simple-to-use nomogram 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 testing 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 nomogram was also assessed using decision curve analysis and Kaplan–Meier analysis.Results: Age, albumin, platelet count, Acute Physiology and Chronic Health Evaluation II score, PaO2/FiO2, lactate dehydrogenase, high-resolution computed tomography score, and syndrome etiology were identified as independent prognostic factors 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).Conclusions: We satisfactorily constructed a simple-to-use nomogram based on eight relevant factors to predict survival and prognosis of patients with acute respiratory distress syndrome. This model can aid personalized treatment and clinical decision-making.

scholarly journals Association of high-resolution computed tomography score with ventilator weaning and 28-day mortality of patients with acute respiratory distress syndrome

2020 ◽  
Vol 48 (6) ◽  
pp. 030006052091296
Author(s):  
Kun Zhao ◽  
Shu-juan Bai ◽  
Zhi-tao Wang ◽  
Yu-he Zhang ◽  
Chao Liu ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Regression Analysis ◽  
Acute Respiratory Distress Syndrome ◽  
High Resolution ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Distress Syndrome ◽  
Ventilator Weaning ◽  
High Resolution Computed Tomography ◽  
Multifactor Regression

Objective This study was performed to explore the association of the high-resolution computed tomography (HRCT) score with ventilator weaning and 28-day mortality of patients with acute respiratory distress syndrome (ARDS). Method In total, 197 patients treated for ARDS from October 2004 to December 2015 were retrospectively analyzed. Univariate analysis and multifactor regression analysis were used to determine the relationship of the HRCT score with ventilator weaning and 28-day mortality. Curve-fitting analysis and threshold analysis were further used to explore the association of the HRCT score with ventilator weaning and 28-day mortality. Results The multifactor regression analysis showed that the HRCT score was significantly associated with a lower rate of ventilator weaning and a higher risk of 28-day mortality in patients with ARDS. HRCT scores of 257.0 and 243.2 were the thresholds for ventilator weaning and 28-day mortality, respectively. When the HRCT score was below the threshold, every 1-point increase in the HRCT score was associated with a 4.6% decrease in the ventilator weaning rate and a 4.6% increase in the 28-day mortality rate. Conclusion The HRCT score was associated with ventilator weaning and 28-day mortality with a threshold of 257.0 and 243.2 points, respectively.

scholarly journals Factors associated with delirium among survivors of acute respiratory distress syndrome: a nationwide cohort study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Tak Kyu Oh ◽  
Hye Youn Park ◽  
In-Ae Song
Keyword(s):  
Regression Analysis ◽  
Acute Respiratory Distress Syndrome ◽  
South Korea ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Distress Syndrome ◽  
Cox Regression ◽  
Multivariable Logistic Regression Analysis ◽  
Cox Regression Analysis ◽  
All Cause Mortality

Abstract Background The prevalence of delirium, its associated factors, and its impact on long-term mortality among survivors of acute respiratory distress syndrome (ARDS) is unclear. Methods Since this was a population-based study, data were extracted from the National Health Insurance database in South Korea. All adults who were admitted to intensive care units with a diagnosis of ARDS between January 1, 2010, and December 31, 2019, and who survived for ≥ 60 days were included. The International Statistical Classification of Diseases and Related Health Problems, tenth revision code of delirium (F05) was used to extract delirium cases during hospitalization. Results A total of 6809 ARDS survivors were included in the analysis, and 319 patients (4.7%) were diagnosed with delirium during hospitalization. In the multivariable logistic regression analysis after covariate adjustment, male sex (odds ratio [OR] 1.60, 95% confidence interval [CI] 1.23, 2.08; P < 0.001), longer duration of hospitalization (OR 1.02, 95% CI 1.01, 1.03; P < 0.001), neuromuscular blockade use (OR 1.50, 95% CI 1.12, 2.01; P = 0.006), benzodiazepine (OR 1.55, 95% CI 1.13, 2.13; P = 0.007) and propofol (OR 1.48, 95% CI 1.01, 2.17; P = 0.046) continuous infusion, and concurrent depression (OR 1.31, 95% CI 1.01, 1.71; P = 0.044) were associated with a higher prevalence of delirium among ARDS survivors. In the multivariable Cox regression analysis after adjustment for covariates, the occurrence of delirium was not significantly associated with 1-year all-cause mortality, when compared to the other survivors who did not develop delirium (hazard ratio: 0.85, 95% CI 1.01, 1.71; P = 0.044). Conclusions In South Korea, 4.7% of ARDS survivors were diagnosed with delirium during hospitalization in South Korea. Some factors were potential risk factors for the development of delirium, but the occurrence of delirium might not affect 1-year all-cause mortality among ARDS survivors.

COVID-19 – eine vaskuläre Systemerkrankung

2020 ◽  
Vol 49 (10) ◽  
pp. 418-421
Author(s):  
Christopher Werlein ◽  
Peter Braubach ◽  
Vincent Schmidt ◽  
Nicolas J. Dickgreber ◽  
Bruno Märkl ◽  
...  
Keyword(s):  
Acute Respiratory Distress Syndrome ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Distress Syndrome

ZUSAMMENFASSUNGDie aktuelle COVID-19-Pandemie verzeichnet mittlerweile über 18 Millionen Erkrankte und 680 000 Todesfälle weltweit. Für die hohe Variabilität sowohl der Schweregrade des klinischen Verlaufs als auch der Organmanifestationen fanden sich zunächst keine pathophysiologisch zufriedenstellenden Erklärungen. Bei schweren Krankheitsverläufen steht in der Regel eine pulmonale Symptomatik im Vordergrund, meist unter dem Bild eines „acute respiratory distress syndrome“ (ARDS). Darüber hinaus zeigen sich jedoch in unterschiedlicher Häufigkeit Organmanifestationen in Haut, Herz, Nieren, Gehirn und anderen viszeralen Organen, die v. a. durch eine Perfusionsstörung durch direkte oder indirekte Gefäßwandschädigung zu erklären sind. Daher wird COVID-19 als vaskuläre Multisystemerkrankung aufgefasst. Vor dem Hintergrund der multiplen Organmanifestationen sind klinisch-pathologische Obduktionen eine wichtige Grundlage der Entschlüsselung der Pathomechanismen von COVID-19 und auch ein Instrument zur Generierung und Hinterfragung innovativer Therapieansätze.

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