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.

Pre-Existing Psychiatric Illness Is Associated With an Increased Risk of Delirium in Patients With Acute Respiratory Distress Syndrome

2021 ◽  
pp. 088506662110190
Author(s):  
Saminder Singh Kalra ◽  
Johnny Jaber ◽  
Bashar N. Alzghoul ◽  
Ryan Hyde ◽  
Sarina Parikh ◽  
...  
Keyword(s):  
Acute Respiratory Distress Syndrome ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Psychiatric Illness ◽  
Distress Syndrome ◽  
Multivariable Logistic Regression Analysis ◽  
Psychiatric Illnesses ◽  
Increased Risk ◽  
Icu Delirium ◽  
The Impact

Background: Patients with acute respiratory distress syndrome (ARDS) are highly susceptible to developing delirium for a multitude of reasons. Previous studies have linked pre-existing depression with an increased risk of postoperative delirium in patients undergoing cardiac and non-cardiac surgery. However, the evidence regarding the association between pre-existing psychiatric illnesses and delirium in ARDS patients is unknown. In this study, we aim to determine the relationship between pre-existing psychiatric illness and the risk of development of delirium amongst ARDS patients. Study Design and Methods: We performed a retrospective study of a mixed group of patients admitted to the intensive care unit (ICU) between January 2016 and December 2019 with a diagnosis of ARDS per the Berlin definition. The study group was divided into 2 cohorts: subjects with delirium and subjects without delirium. Comparison between the 2 groups was conducted to examine the impact of pre-existing psychiatric illnesses including major depressive disorder (MDD), generalized anxiety disorder (GAD), bipolar disorder, schizophrenia, or post-traumatic stress disorder. Multivariable logistic regression analysis was performed adjusting for benzodiazepine use, sedatives, analgesics, sequential organ failure assessment score, and corticosteroid use to determine the association between pre-existing psychiatric disorders and delirium. Results: 286 patients with ARDS were identified; 124 (43%) of whom were diagnosed with ICU delirium. In patients diagnosed with ICU delirium, 49.2% were found to have preexisting psychiatric illnesses, compared to 34.0% without any preexisting psychiatric illness (OR = 1.94, P = 0.01). In a subgroup analysis of individual psychiatric illnesses, GAD and MDD were associated with the development of delirium (OR = 1.88, P = 0.04 and OR = 1.76, P = 0.05 respectively). Interpretation: ARDS patients with preexisting psychiatric illnesses, particularly GAD and MDD are associated with an increased risk of developing ICU delirium. Clinicians should be aware of the effect of psychiatric co-morbidities on developing delirium in critically ill patients.

scholarly journals Comparisons of Outcomes between Patients with Direct and Indirect Acute Respiratory Distress Syndrome Receiving Extracorporeal Membrane Oxygenation

Membranes ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 644
Author(s):  
Li-Chung Chiu ◽  
Li-Pang Chuang ◽  
Shih-Wei Lin ◽  
Hsin-Hsien Li ◽  
Shaw-Woei Leu ◽  
...  
Keyword(s):  
Acute Respiratory Distress Syndrome ◽  
Extracorporeal Membrane Oxygenation ◽  
Hospital Mortality ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Clinical Outcomes ◽  
Sofa Score ◽  
Distress Syndrome ◽  
Cox Regression ◽  
Membrane Oxygenation

Acute respiratory distress syndrome (ARDS) is a heterogeneous syndrome caused by direct (local damage to lung parenchyma) or indirect lung injury (insults from extrapulmonary sites with acute systemic inflammatory response), the clinical and biological complexity can have a profound effect on clinical outcomes. We performed a retrospective analysis of 152 severe ARDS patients receiving extracorporeal membrane oxygenation (ECMO). Our objective was to assess the differences in clinical characteristics and outcomes of direct and indirect ARDS patients receiving ECMO. Overall hospital mortality was 53.3%. A total of 118 patients were assigned to the direct ARDS group, and 34 patients were assigned to the indirect ARDS group. The 28-, 60-, and 90-day hospital mortality rates were significantly higher among indirect ARDS patients (all p < 0.05). Cox regression models demonstrated that among direct ARDS patients, diabetes mellitus, immunocompromised status, ARDS duration before ECMO, and SOFA score during the first 3 days of ECMO were independently associated with mortality. In indirect ARDS patients, SOFA score and dynamic compliance during the first 3 days of ECMO were independently associated with mortality. Our findings revealed that among patients receiving ECMO, direct and indirect subphenotypes of ARDS have distinct clinical outcomes and different predictors for mortality.

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 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 Economic Status and Mortality in Patients with Acute Respiratory Distress Syndrome

2020 ◽  
Vol 17 (6) ◽  
pp. 1815
Author(s):  
Tak Kyu Oh ◽  
In-Ae Song ◽  
Jae Ho Lee
Keyword(s):  
Acute Respiratory Distress Syndrome ◽  
Health Insurance ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Distress Syndrome ◽  
Cox Regression ◽  
Economic Status ◽  
Health Insurance Data ◽  
The Impact ◽  
Insurance Data

The high cost of treatment for acute respiratory distress syndrome (ARDS) is a concern for healthcare systems, while the impact of patients’ socio-economic status on the risk of ARDS-associated mortality remains controversial. This study investigated associations between patients’ income at the time of ARDS diagnosis and ARDS-specific mortality rate after treatment initiation. Data from records provided by the National Health Insurance Service of South Korea were used. Adult patients admitted for ARDS treatment from 2013 to 2017 were included in the study. Patients’ income in the year of diagnosis was evaluated. A total of 14,600 ARDS cases were included in the analysis. The 30-day and 1-year mortality rates were 48.6% and 70.3%, respectively. In multivariable Cox regression model, we compared income quartiles, showing that compared to income strata Q1, the Q2 (p = 0.719), Q3 (p = 0.946), and Q4 (p = 0.542) groups of income level did not affect the risk of 30-day mortality, respectively. Additionally, compared to income strata Q1, the Q2 (p = 0.762), Q3 (p = 0.420), and Q4 (p = 0.189) strata did not affect the risk of 1-year mortality. Patient income at the time of ARDS diagnosis did not affect the risk of 30-day or 1-year mortality in the present study based on South Korea’s health insurance data.

scholarly journals Association of COVID-19 with Intracranial Hemorrhage during Extracorporeal Membrane Oxygenation for Acute Respiratory Distress Syndrome: A 10-Year Retrospective Observational Study

2021 ◽  
Vol 11 (1) ◽  
pp. 28
Author(s):  
Tobias Pantel ◽  
Kevin Roedl ◽  
Dominik Jarczak ◽  
Yuanyuan Yu ◽  
Daniel Peter Frings ◽  
...  
Keyword(s):  
Acute Respiratory Distress Syndrome ◽  
Extracorporeal Membrane Oxygenation ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Intracranial Hemorrhage ◽  
Distress Syndrome ◽  
Cranial Computed Tomography ◽  
Cox Regression Analysis ◽  
Membrane Oxygenation ◽  
Vv Ecmo

Extracorporeal membrane oxygenation (ECMO) is potentially lifesaving for patients with acute respiratory distress syndrome (ARDS) but may be accompanied by serious adverse events, including intracranial hemorrhage (ICRH). We hypothesized that ICRH occurs more frequently in patients with COVID-19 than in patients with ARDS of other etiologies. We performed a single-center retrospective analysis of adult patients treated with venovenous (vv-) ECMO for ARDS between January 2011 and April 2021. Patients were included if they had received a cranial computed tomography (cCT) scan during vv-ECMO support or within 72 h after ECMO removal. Cox regression analysis was used to identify factors associated with ICRH. During the study period, we identified 204 patients with vv-ECMO for ARDS, for whom a cCT scan was available. We observed ICRH in 35.4% (n = 17/48) of patients with COVID-19 and in 16.7% (n = 26/156) of patients with ARDS attributable to factors other than COVID-19. COVID-19 (HR: 2.945; 95%; CI: 1.079–8.038; p = 0.035) and carboxyhemoglobin (HR: 0.330; 95%; CI: 0.135–0.806; p = 0.015) were associated with ICRH during vv-ECMO. In patients receiving vv-ECMO, the incidence of ICRH is doubled in patients with COVID-19 compared to patients suffering from ARDS attributable to other causes. More studies on the association between COVID-19 and ICRH during vv-ECMO are urgently needed to identify risk patterns and targets for potential therapeutic interventions.

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 &lt; 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.

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