| Abstract|| |
OBJECTIVE: Outcome of acute respiratory distress syndrome (ARDS) in relation to age, gender, race, pre-Intensive Care Unit (ICU) location, and type of ICU.
METHODS: Retrospective cohort study of patients enrolled in the ARDS network randomized controlled trials.
RESULTS: A total of 2914 patients were included in these trials. Outcomes were adjusted to baseline covariates including APACHE III score, vasopressor use, cause of lung injury, lung injury score, diabetes, cancer status, body mass index, and study ID. Older patients had significantly higher mortality at both 28- and 60-day (odds ratio [OR] 2.59 [95% confidence interval [CI]: 2.12-3.18] P < 0.001 and 2.79, 95% CI: 2.29-3.39, P < 0.001, respectively); less ICU and ventilator free days (relative risk [RR] 0.92, 95% CI: 0.87-0.96, P < 0.001 and 0.92, 95% CI: 0.88-0.96, P < 0.001, respectively). For preadmission location, the 28- and 60-day mortality were lower if the patient was admitted from the operating room (OR)/recovery room (OR 0.65, 95% CI: 0.44-0.95, P = 0.026; and OR = 0.66, 95% CI: 0.46-0.95, P = 0.025, respectively) or emergency department (OR = 0.78, 95% CI: 0.61-0.99, P = 0.039; and OR = 0.71, 95% CI: 0.56-0.89, P = 0.004, respectively), but no statistical differences in ICU and ventilator free days between different preadmission locations. Races other than white and black had a statistically higher mortality (28- and 60-day mortality: OR = 1.47, 95% CI: 1.09-1.98, P = 0.011; and OR 1.53, 95% CI: 1.15-2.04, P = 0.004, respectively). Between whites and blacks, females and males there were no statistically significant differences in all outcomes.
CONCLUSION: Older patients and races other than blacks and whites have higher mortality associated with ARDS. Mortality is affected by patients preadmission location. There are no differences in outcome in relation to the type of ICU, gender, or between blacks and whites.
Keywords: Acute respiratory distress syndrome, demographics, outcome
|How to cite this article:|
El-Haddad H, Jang H, Chen W, Haider S, Soubani AO. The effect of demographics and patient location on the outcome of patients with acute respiratory distress syndrome. Ann Thorac Med 2017;12:17-24
|How to cite this URL:|
El-Haddad H, Jang H, Chen W, Haider S, Soubani AO. The effect of demographics and patient location on the outcome of patients with acute respiratory distress syndrome. Ann Thorac Med [serial online] 2017 [cited 2017 Apr 28];12:17-24. Available from: http://www.thoracicmedicine.org/text.asp?2017/12/1/17/197767
Acute respiratory distress syndrome (ARDS) is a serious complication associated with critical illness affecting an estimated 150,000 annually in the US and at least 20% of mechanically ventilated patients. , The outcome of ARDS varies significantly between patients and is influenced by several factors. There are conflicting results in the literature about the predictors of outcome in patients with ARDS. The ARDS network randomized controlled trials provide a unique opportunity to study the different variables affecting outcome of these patients. We have shown that the outcome is affected by cancer status and not influenced by body mass index (BMI) or presence or absence of diabetes mellitus. , The aim of this study was to analyze the effect of demographic data such as age, race, gender, pre-Intensive Care Unit (ICU) patient location, and type of ICU on outcome of patients with ARDS.
| Methods|| |
The ARDS network has conducted several randomized controlled trials to evaluate therapeutic interventions for the management of acute lung injury. These trials have been previously published. ,,,,, [Table 1] summarizes the relevant features of these trials. Briefly, all patients fulfilled diagnostic criteria for acute lung injury and were mechanically ventilated. Similar inclusion and exclusion criteria were used in all of the trials. The National Institute of Health and the local Institutional Review Boards of each of the sites approved all studies.
We had authorized access to the original data for each of these studies. This manuscript was prepared using Ketoconazole and Respiratory Management in ALI/ARDS (KARMA), Late Steroid Rescue Study (LASRS), Lisofylline and Respiratory Management in ALI/ARDS (LARMA), Assessment of Low tidal Volume and elevated End-expiratory volume to Obviate Lung Injury (ALVEOLI), Fluids And Catheters Treatment Trial (FACTT), and Albuterol for the Treatment of Acute lung injury (ALTA) research materials obtained from the National Heart, Lung, and Blood Institute (NHLBI) Biologic Specimen and Data Repository Information Coordinating Center. The findings of this study do not necessarily reflect the opinions or views of the KARMA, LASRS, LARMA, ALVEOLI, FACTT, and ALTA investigators or the NHLBI.
For the purpose of this analysis, we included only patients who had P/F ratio < 300 to fulfill the Berlin definition of ARDS.  The data were stratified in relation to demographics (age, race, and gender), pre-ICU patient location, and the type of ICU. Other data points extracted included vasopressor use, etiology of ARDS, lung injury score as well as APACHE score. We also included cancer status since it was found important in our previous analysis of the data. 
For age, patients were divided into two groups 16-59 years and 60-89 years. Regarding race patients were divided into white (reference), black and others. The race was self-identified by the patients or relatives. Pre-ICU patient locations were classified into floor/stepdown unit (reference), emergency department (ED), operating room (OR)/recovery room, and others. The ICU locations were classified into mobile ICU (MICU)/critical care unit (CCU) (reference), surgical ICU (SICU)/cardiac SICU, neuro ICU, burn, trauma, and mixed ICU.
The primary outcome for our analysis was mortality at 28-day after enrollment in the study in relation to age, gender, race, pre-ICU, and type of ICU. The secondary outcomes were 60-day mortality, ventilator-free days, and ICU-free days. The ventilator-free days were defined as the number of days of at least 48-h unassisted breathing during the first 28 days after enrollment.
Patient's baseline characteristics across six studies were reported descriptively. Continuous data are presented as medians with ranges. Categorical data are reported as frequencies and percentages. In an effort to minimize the false positives due to multiple testing, all variables were specified a priori to be clinically sound. These variables included age (<60 and ≥60), gender, ethnic (white, black, and other), pre-ICU location, type of ICU, APACHE III, vasopressor use, cause of lung injury (pneumonia, severe sepsis, aspiration, trauma, and others), lung injury score, cancer status, BMI, diabetes mellitus, and study ID.
The univariate analysis of association between age (<60 and ≥60), gender, ethnic (white, black, and other), pre-ICU location, and type of ICU and clinical outcomes including 28-day mortality, 60-day mortality, categorized ventilation free days in weeks, categorized ICU-free days in weeks, were tested for significance using a Chi-square test or Fisher's exact test where appropriate.
Purposeful multivariable logistic regression model and multivariable zero-inflated negative binomial regression model were then used to evaluate the effect of above-mentioned patient baseline characteristics on clinical outcomes including 28- or 60-day mortality and ventilation free days or ICU-free days, respectively.
Because of missing values in our set of covariates, all the multivariable models were carried out after 15 multiple imputations using the R package mice. All P values are 2-sided with a significance level of 0.05. The results of these analyses should be regarded only as descriptive findings, and multiple testing were not adjusted. All calculations were performed with R version 3.0.2.
| Results|| |
A total of 2914 patients were included in these trials. Five patients with P/F >300 were excluded from analysis. [Table 2] describes the baseline characteristics of these patients.
On univariate analysis, there was significant statistical difference in the mortality rate, with 28-day mortality being higher among older age group (39.44% vs. 18.49%, P < 0.001, Chi-square test). The 60-day mortality for old age group was 45% and for younger age group 21% (P < 0.001, Chi-square test) [Figure 1]. The older age group had less ICU free days [Figure 2] and less ventilator-free days [Figure 3] (both P < 0.001, Chi-square test). The multivariable logistic regression results showed a statistically significant higher mortality at both 28 days and 60 days for older age group (OR for 28-day mortality = 2.59, 95% confidence interval [CI]: 2.12-3.18, P < 0.001; OR for 60-day mortality = 2.79, 95% CI: 2.29-3.39, P < 0.001) [Table 3]. The multivariable negative binomial regression showed there were statistically significant more ICU-free days and ventilator-free days for younger age group (older age group; relative risk [RR] for ICU-free days = 0.92, 95% CI: 0.87-0.96, P < 0.001; RR for ventilator-free days = 0.92, 95% CI: 0.88-0.96, P < 0.001) [Table 3].
|Figure 1: Mortality rate by age group (a), gender (b), race (c), location before admission to Intensive Care Unit (d), and patient location (e); Chi-squared test was used to calculate P values. The bar plots represent mortality rate (%) ± standard error from groups defined by each variable|
Click here to view
|Figure 2: Percentage of patients with 0, 1-7, 8-14, 15-21, and 22-28 Intensive Care Unit-free days during the first 28 days after enrollment by age group (a), gender (b), race (c), location prior to admission to Intensive Care Unit (d), and patient location (e); either Chi-squared test or Fisher's exact test was used to calculate P values|
Click here to view
|Figure 3: Percentage of patients with 0, 1-7, 8-14, 15-21, 22-28 ventilator-free days during the first 28 days after enrollment by age group (a), gender (b), race (c), location before admission to Intensive Care Unit (d), and patient location (e); either Chi-squared test or Fisher's exact test was used to calculate P values|
Click here to view
|Table 3: Results of multivariable regression models after multiple imputations |
Click here to view
On univariate analysis, there was no significant statistical difference between males and females mortality at 28 days (25.77% versus 23.72%, P = 0.219, Chi-square test) but there was a statistically significant higher mortality for males at 60 days (30.16% vs. 26.36%, P = 0.027, Chi-square test) [Figure 1]. There was no statistically significant difference in the categorized ICU free days [Figure 2] or ventilator-free days [Figure 3] in relation to gender. The multivariable logistic regression results did not show a statistically significant difference for 28 days (OR = 0.94, 95% CI: 0.78-1.14, P = 0.538) as well as 60 days mortality (OR = 0.85, 95% CI: 0.7-1.02, P = 0.083). There were statistically significant more ICU-free days for females (RR = 1.04, 95% CI: 1.00-1.08, P = 0.046) but not for ventilator-free days [Table 3] from multivariable negative binomial model.
On univariate analysis, there mortality at 28 days was least for whites (23.51%) followed by blacks (26.87%) followed by others (30.18%) (P = 0.017, Chi-square test). For 60-day mortality, it was least among whites (26.81%) followed by blacks (31.29%) followed by others (34.45%) (P = 0.005, Chi-square test) [Figure 1]. The group others had the least categorized ICU and ventilator-free days followed by blacks than whites [Figure 2] and [Figure 3]. The multivariable logistic regression model resulted no statistically significant differences between white and blacks in 28-day mortality (OR = 1.1, 95% CI: 0.85-1.41, P = 0.479) and 60-day mortality (OR = 1.16, 95% CI: 0.91-1.47, P = 0.242). However, there was a statistically significant mortality in the group of other races for both 28-day mortality (OR = 1.47, 95% CI: 1.09-1.98, P = 0.011) and 60-day mortality (OR = 1.53, 95% CI: 1.15-2.04, P = 0.004). There were no statistically significant differences in ICU-free days and ventilator-free days between different groups [Table 3] from multivariable negative binomial model.
Pre-Intensive Care Unit patient location
On univariate analysis, the least 28-day mortality was in patients admitted from the operating room/recovery room (17%) followed by ED (23.57%) and then the floor/stepdown (32.19%) (P ≤ 0.001, Chi-square test) [Figure 1]. The 60-day mortality was least for the patients admitted from the operating room/recovery room (20.75%) followed by ED (26.16%) and then the floor/stepdown (36.87%) (P < 0.001, Chi-square test) [Figure 1]. The least ICU-free days were for patients admitted from the floor/stepdown unit and the most ICU-free days and ventilator-free days were for patients admitted from the ED or from the operating room/recovery room [Figure 2] and [Figure 3]. The multivariable logistic regression showed there was a statistically significant lower 28-day mortality if the patient was admitted from the operating room/recovery room (OR = 0.65, 95% CI: 0.44-0.95, P = 0.026) followed by the ED (OR = 0.78, 95% CI: 0.61-0.99, P = 0.039). The same trend was seen in 60-day mortality (operating room/recovery room: OR = 0.66, 95% CI: 0.46-0.95, P = 0.025 followed by ED: OR = 0.71, 95% CI: 0.56-0.89, P = 0.004) [Table 3]. There were no statistically significant differences in ICU-free days and ventilator-free days between different groups from multivariable negative binomial regression model [Table 3].
Type of Intensive Care Unit
On univariate analysis, the least 28-day mortality was in the trauma units 16.02% followed neuro ICU 19.05%, followed by SICU/cardiac SICU 21.31%, burn units 23.4%, and MICU/CCU 28.17% (P < 0.001). The 60-day mortality was lowest in trauma units 18.2% followed by SICU/cardiac SICU 25.3%, burn units 25.5%, neuro ICU 26.2%, and MICU/CCU 31.9% (P < 0.001) [Figure 1]. The categorized ICU-free days and ventilator-free days were mixed and inconsistent between the groups [Figure 2] and [Figure 3]. The multivariable logistic regression model and negative binomial regression model showed no statistically significant difference between the different types of ICU in relation to 28 days mortality, 60-day mortality, ICU-free days, and ventilator-free days [Table 3].
| Discussion|| |
This analysis shows that certain demographic factors affect the outcome of patients with ARDS with higher mortality in older patients and races other than blacks and whites. On the other hand, there were no differences in outcome in relation to gender or between blacks and whites. In addition, this analysis demonstrates that the pre-ICU patient location impacts outcome with least mortality in those admitted from operating room/recovery, followed by those admitted from ED, and is worst in those who were admitted from floor/step down units. There were no differences in outcomes in relation to the type of ICU the patients with ARDS were treated in.
ARDS is a clinical condition characterized by severe respiratory distress, hypoxemic respiratory failure with bilateral pulmonary infiltrates in the absence of congestive heart failure or fluid overload. The most common risk factor for developing ARDS is severe sepsis; other known risk factors include aspiration of gastric contents, severe trauma, massive blood products, drug overdose, pancreatitis, near-drowning, and inhalation injury. , The pathogenesis involves diffuse alveolar and capillary endothelial injury that allows proteinaceous interstitial fluid accumulation, loss of functional surfactant resulting in alveolar collapse resulting in impaired gas exchange.  Although mortality has improved significantly in the last two decades, it is still as high as 46% for those with severe ARDS. 
There are different factors the affect the outcome of patients with ARDS. Several studies have addressed these factors with variable results. ,,,,,,,,,,,,,, The aims of this study were to determine the role of demographic data such as age, gender, and race on the outcome and also to study other variables that have not been previously addressed such as pre-ICU patient location and type of ICU.
Age has been shown to be a critical determinant in the incidence of ARDS (16/100,000 person-years in young (15-19 years of age) and 306/100,000 person-years (75-84 years of age), and has been reported to be a risk factor for death among patients with this syndrome. ,,,, A study of 256 patients done by Suchyta et al. identified age over 55 years as a cutoff above which mortality is significantly increased (P = 0.002).  Mortality rates among patients between the age 15-19 years has been reported to be 24% which increases above 60% among patients 85 years of age or older. , The current analysis confirms previous findings about worse outcomes with older age including 28- and 60-day mortality and fewer ventilator and ICU-free days. However, it shows at the same time that the mortality for older patients is better than previous reports (28-day mortality 39% for those older than 60 years). Factors associated with age that may explain worse outcomes include a reduction in respiratory function due to decline in chest wall compliance forced expiratory volume in 1 s, respiratory muscle strength, and diminished response to hypoxia and hypercapnia. Other factors include comorbid illnesses, increased risk of pulmonary infections and delayed tissue repair following an inflammatory injury. ,
The role of race and gender on the development and outcome of ARDS has been previously studied with conflicting results. In a study of the National Center for Health Statistics of 333,004 patients who died from ARDS, the rates of death for men were almost double those for women (8.6/100,000 men as compared to 4.7/100,000 for women, P < 0.05).  The mortality in blacks was significantly higher than whites and other races. The findings were true for men and women (the mean rate for black men was 12.8/100,000, compared with 9.1/100,000 in white men and for black women was 7.4/100,000, compared with 5.4/100,000 in white women (P < 0.05). 
The authors of that study hypothesized the higher mortality in men and blacks to be due to factors related to higher risk in these groups for diagnoses that lead to ARDS such as sepsis and trauma, higher risk of developing ARDS during critical illness, and dying from ARDS once they develop the disease. The differences in outcome could also reflect socioeconomic status, the severity of illness or other confounding factors. 
In another recent study, men were more likely than women to develop acute lung injury (6.9% vs. 4.7%, P < 0.001) and experienced a longer ICU (P = 0.002) but not hospital (P = 0.10) length of stay. Men who developed acute lung injury had a nonsignificant increase in in-hospital mortality (27.6% vs. 18.5%; P = 0.08; 95% CI, 0.94%-2.99%). Whites, compared with blacks, were more likely to develop acute lung injury (6.5% vs. 4.5%, P = 0.014); however, there was no difference in acute lung injury associated mortality (24.8% vs. 21.6%, P = 0.63). Hispanic ethnicity was associated with neither acute lung injury development (5.6% in Hispanics and 6.6% in non-Hispanics, P = 0.43), nor mortality (P = 0.84).  In an analysis of part of the ARDS network studies and after adjusting for severity of illness, there was no difference in mortality between black and white patients; however Hispanics had higher 60 days mortality (OR = 2.00; 95% CI, 1.37-2.90) and fewer ventilator-free days. 
The current analysis of only patients who fulfilled the revised criteria for ARDS shows that there were no differences in outcomes between men and women. Furthermore, there were no differences between blacks and whites in all outcomes; however, races other than blacks and whites had significantly higher 28- and 60-day mortality. The races other than blacks and whites include not only primary Hispanics but also other minorities. It is not clear why this group had higher mortality, but factors may include language barriers affecting seeking medical attention or the care during critical illness. In addition, it is possible that this group may have a higher burden of comorbid illnesses. Further studies are needed to determine whether other races have higher risk for developing or dying from ARDS and the reasons behind these differences.
There are very few studies that analyze the outcome of ARDS in relation to pre-ICU location or type of ICU. A prospective observational study of 296 patients with ARDS reported a significantly lower ICU mortality rate among patients with community-acquired ARDS (diagnosed within 48 h of hospital or ICU admission) as compared to hospital acquired ARDS.  Patients in the community acquired ARDS also had higher number of ventilator-free days as well has a higher number of ICU-free days. Our study shows that the mortality outcomes were significantly better in patients admitted to ICU from ED or operating room/recovery room as compared to those admitted from floor/step down units. This has similar implication to the above study in that patients admitted to ICU from the community did better than those who developed ARDS while in hospital for other illnesses. This difference in outcome may be related to slow progression of respiratory failure, trial of other therapies for hypoxia, hospital-acquired complications, or delayed diagnosis among patients on the floor/step down.
The current study also significantly shows that there were no differences in all outcomes in relation to the type of ICU the patients with ARDS were treated in. The type of ICU is likely to correlate with the etiology of ARDS. Some studies have suggested that there is the difference in outcome of ARDS in relation to the precipitating factors. For example, the risk of death from ARDS associated with sepsis and burn were higher than with trauma or neurological complications. ,,
The lack of differences in outcome between the different ICUs may reflect standardized care of ARDS (lung protective strategies, pronning, and supportive care) in the modern units.
The strengths of the study are the large number of patients with similar distribution among baseline characteristics. In addition, the original studies were high quality multicenter, randomized, controlled double-blinded prospective studies with robust design, inclusion criteria and data collection, which provides stronger conclusions. Only patients that fulfilled the current definition of ARDS were included in the analysis. The outcomes included mortality (28 and 60 days) and other indicators of utilization of health-care resources such as ventilator and ICU-free days. There are limitations to this study including the retrospective analysis of published data with the lack of specific data about confounding factors related to our analysis. Also, there is no correlation between the pre-ICU location and type of ICU and etiology of ARDS.
| Conclusion|| |
This study provides further insight about predictors of outcome in patients with ARDS. Higher mortality is associated with older patients and races other than blacks and white. Older patients also have fewer ventilator and ICU-free days. Mortality is also impacted by the patient location before ICU admission. On the other hand, there are no differences in outcome in relation to gender or between blacks and white or the type of ICU the patient is treated in.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Rubenfeld GD, Caldwell E, Peabody E, Weaver J, Martin DP, Neff M, et al.
Incidence and outcomes of acute lung injury. N Engl J Med 2005;353:1685-93.
Zaccardelli DS, Pattishall EN. Clinical diagnostic criteria of the adult respiratory distress syndrome in the Intensive Care Unit. Crit Care Med 1996;24:247-51.
Soubani AO, Chen W, Jang H. The outcome of acute respiratory distress syndrome in relation to body mass index and diabetes mellitus. Heart Lung 2015;44:441-7.
Soubani AO, Shehada E, Chen W, Smith D. The outcome of cancer patients with acute respiratory distress syndrome. J Crit Care 2014;29:183.e7-12.
Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. The acute respiratory distress syndrome network. N Engl J Med 2000;342:1301-8.
National Heart, Lung, and Blood Institute Acute Respiratory Distress Syndrome (ARDS) Clinical Trials Network, Wheeler AP, Bernard GR, Thompson BT, et al.
Pulmonary-artery versus central venous catheter to guide treatment of acute lung injury. N Engl J Med 2006;354:2213-24.
National Heart, Lung, and Blood Institute Acute Respiratory Distress Syndrome (ARDS) Clinical Trials Network, Wiedemann HP, Wheeler AP, Bernard GR, et al.
Comparison of two fluid-management strategies in acute lung injury. N Engl J Med 2006;354:2564-75.
Steinberg KP, Hudson LD, Goodman RB, Hough CL, Lanken PN, Hyzy R, et al.
Efficacy and safety of corticosteroids for persistent acute respiratory distress syndrome. N Engl J Med 2006;354:1671-84.
Brower RG, Lanken PN, MacIntyre N, Matthay MA, Morris A, Ancukiewicz M, et al.
Higher versus lower positive end-expiratory pressures in patients with the acute respiratory distress syndrome. N Engl J Med 2004;351:327-36.
National Heart, Lung, and Blood Institute Acute Respiratory Distress Syndrome (ARDS) Clinical Trials Network, Matthay MA, Brower RG, Carson S, et al.
Randomized, placebo-controlled clinical trial of an aerosolized ß 2
-agonist for treatment of acute lung injury. Am J Respir Crit Care Med 2011;184:561-8.
ARDS Definition Task Force, Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, et al.
Acute respiratory distress syndrome: The Berlin definition. JAMA 2012;307:2526-33.
Jia X, Malhotra A, Saeed M, Mark RG, Talmor D. Risk factors for ARDS in patients receiving mechanical ventilation for >48 h. Chest 2008;133:853-61.
Fanelli V, Ranieri VM. Mechanisms and clinical consequences of acute lung injury. Ann Am Thorac Soc 2015;12 Suppl 1:S3-8.
Bellani G, Laffey JG, Pham T, Fan E, Brochard L, Esteban A, et al.
Epidemiology, patterns of care, and mortality for patients with acute respiratory distress syndrome in Intensive Care Units in 50 countries. JAMA 2016;315:788-800.
Suchyta MR, Clemmer TP, Elliott CG, Orme JF Jr., Morris AH, Jacobson J, et al.
Increased mortality of older patients with acute respiratory distress syndrome. Chest 1997;111:1334-9.
Azevedo LC, Park M, Salluh JI, Rea-Neto A, Souza-Dantas VC, Varaschin P, et al.
Clinical outcomes of patients requiring ventilatory support in Brazilian Intensive Care Units: A multicenter, prospective, cohort study. Crit Care 2013;17:R63.
Brun-Buisson C, Minelli C, Bertolini G, Brazzi L, Pimentel J, Lewandowski K, et al.
Epidemiology and outcome of acute lung injury in European Intensive Care Units. Results from the ALIVE study. Intensive Care Med 2004;30:51-61.
Zilberberg MD, Epstein SK. Acute lung injury in the medical ICU: Comorbid conditions, age, etiology, and hospital outcome. Am J Respir Crit Care Med 1998;157(4 Pt 1):1159-64.
Linge HM, Lee JY, Ochani K, Koga K, Kohn N, Ojamaa K, et al.
Age influences inflammatory responses, hemodynamics, and cardiac proteasome activation during acute lung injury. Exp Lung Res 2015;41:216-27.
Sharma G, Goodwin J. Effect of aging on respiratory system physiology and immunology. Clin Interv Aging 2006;1:253-60.
Moss M, Mannino DM. Race and gender differences in acute respiratory distress syndrome deaths in the United States: An analysis of multiple-cause mortality data (1979-1996). Crit Care Med 2002;30:1679-85.
Lemos-Filho LB, Mikkelsen ME, Martin GS, Dabbagh O, Adesanya A, Gentile N, et al.
Sex, race, and the development of acute lung injury. Chest 2013;143:901-9.
Erickson SE, Shlipak MG, Martin GS, Wheeler AP, Ancukiewicz M, Matthay MA, et al.
Racial and ethnic disparities in mortality from acute lung injury. Crit Care Med 2009;37:1-6.
Kao KC, Hu HC, Hsieh MJ, Tsai YH, Huang CC. Comparison of community-acquired, hospital-acquired, and intensive care unit-acquired acute respiratory distress syndrome: A prospective observational cohort study. Crit Care 2015;19:384.
Bordes J, Lacroix G, Esnault P, Goutorbe P, Cotte J, Dantzer E, et al.
Comparison of the Berlin definition with the American European consensus definition for acute respiratory distress syndrome in burn patients. Burns 2014;40:562-7.
Fowler AA, Hamman RF, Good JT, Benson KN, Baird M, Eberle DJ, et al.
Adult respiratory distress syndrome: Risk with common predispositions. Ann Intern Med 1983;98 (5 Pt 1):593-7.
Rincon F, Maltenfort M, Dey S, Ghosh S, Vibbert M, Urtecho J, et al.
The prevalence and impact of mortality of the acute respiratory distress syndrome on admissions of patients with ischemic stroke in the United States. J Intensive Care Med 2014;29:357-64.
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3]