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Review

Respiratory Subsets in Patients with Moderate to Severe Acute Respiratory Distress Syndrome for Early Prediction of Death †

by
Jesús Villar
1,2,3,*,
Cristina Fernández
2,
Jesús M. González-Martín
1,2,
Carlos Ferrando
1,4,
José M. Añón
1,5,
Ana M. del Saz-Ortíz
6,
Ana Díaz-Lamas
7,
Ana Bueno-González
8,
Lorena Fernández
9,
Ana M. Domínguez-Berrot
10,
Eduardo Peinado
11,
David Andaluz-Ojeda
12,
Elena González-Higueras
13,
Anxela Vidal
14,
M. Mar Fernández
15,
Juan M. Mora-Ordoñez
16,
Isabel Murcia
17,
Concepción Tarancón
18,
Eleuterio Merayo
19,
Alba Pérez
20,
Miguel A. Romera
21,
Francisco Alba
22,
David Pestaña
23,
Pedro Rodríguez-Suárez
1,24,
Rosa L. Fernández
1,2,
Ewout W. Steyerberg
25,
Lorenzo Berra
26,‡,
Arthur S. Slutsky
3,27,‡ and
The Spanish Initiative for Epidemiology, Stratification and Therapies of ARDS (SIESTA) Network
§
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1
CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, 28029 Madrid, Spain
2
Research Unit, Hospital Universitario Dr. Negrín, 35019 Las Palmas de Gran Canaria, Spain
3
Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON M5B 1W8, Canada
4
Surgical Intensive Care Unit, Dept. of Anesthesia, Hospital Clinic, IDIBAPS, 08036 Barcelona, Spain
5
Intensive Care Unit, Hospital Universitario La Paz, IdiPaz, 28046 Madrid, Spain
6
Intensive Care Unit, Hospital Universitario Virgen de Arrixaca, 30120 Murcia, Spain
7
Intensive Care Unit, Hospital Universitario de A Coruña, 15006 La Coruña, Spain
8
Intensive Care Unit, Hospital General Universitario de Ciudad Real, 13005 Ciudad Real, Spain
9
Intensive Care Unit, Hospital Universitario Río Hortega, 47012 Valladolid, Spain
10
Intensive Care Unit, Complejo Asistencial Universitario de León, 24001 León, Spain
11
Intensive Care Unit, Hospital Universitario NS de Candelaria, 38010 Santa Cruz de Tenerife, Spain
12
Intensive Care Unit, Hospital Clínico Universitario, 47003 Valladolid, Spain
13
Intensive Care Unit, Hospital Universitario Virgen de La Luz, 16002 Cuenca, Spain
14
Intensive Care Unit, Hospital Universitario Fundación Jiménez Díaz, 28040 Madrid, Spain
15
Intensive Care Unit, Hospital Universitario Mutua Terrassa, Terrassa, 08221 Barcelona, Spain
16
Intensive Care Unit, Hospital Universitario Regional Carlos Haya, 29010 Málaga, Spain
17
Intensive Care Unit, Complejo Hospitalario Universitario de Albacete, 02006 Albacete, Spain
18
Intensive Care Unit, Complejo Público Hospitalario de Zamora, 49022 Zamora, Spain
19
Intensive Care Unit, Hospital El Bierzo, Ponferrada, 24404 León, Spain
20
Department of Anesthesia, Hospital Universitario Río Hortega, 47012 Valladolid, Spain
21
Intensive Care Unit, Hospital Universitario Puerta de Hierro, Majadahonda, 28222 Madrid, Spain
22
Intensive Care Unit, Hospital General N.S. del Prado, 45600 Talavera de la Reina, Spain
23
Department of Anesthesia, Hospital Universitario Ramón y Cajal, 28034 Madrid, Spain
24
Department of Thoracic Surgery, Hospital Universitario Dr. Negrín, 35019 Las Palmas de Gran Canaria, Spain
25
Department of Biomedical Data Sciences, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
26
Department of Anesthesia, Critical Care & Pain Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
27
Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON M5T3A1, Canada
*
Author to whom correspondence should be addressed.
To the memory of Robert M. Kacmarek.
These authors contributed equally to this work.
§
Members of the SIESTA network are listed in the Appendix A.
J. Clin. Med. 2022, 11(19), 5724; https://doi.org/10.3390/jcm11195724
Submission received: 10 August 2022 / Revised: 19 September 2022 / Accepted: 24 September 2022 / Published: 27 September 2022
(This article belongs to the Special Issue New Insights into Acute Respiratory Distress Syndrome)

Abstract

:
Introduction: In patients with acute respiratory distress syndrome (ARDS), the PaO2/FiO2 ratio at the time of ARDS diagnosis is weakly associated with mortality. We hypothesized that setting a PaO2/FiO2 threshold in 150 mm Hg at 24 h from moderate/severe ARDS diagnosis would improve predictions of death in the intensive care unit (ICU). Methods: We conducted an ancillary study in 1303 patients with moderate to severe ARDS managed with lung-protective ventilation enrolled consecutively in four prospective multicenter cohorts in a network of ICUs. The first three cohorts were pooled (n = 1000) as a testing cohort; the fourth cohort (n = 303) served as a confirmatory cohort. Based on the thresholds for PaO2/FiO2 (150 mm Hg) and positive end-expiratory pressure (PEEP) (10 cm H2O), the patients were classified into four possible subsets at baseline and at 24 h using a standardized PEEP-FiO2 approach: (I) PaO2/FiO2 ≥ 150 at PEEP < 10, (II) PaO2/FiO2 ≥ 150 at PEEP ≥ 10, (III) PaO2/FiO2 < 150 at PEEP < 10, and (IV) PaO2/FiO2 < 150 at PEEP ≥ 10. Primary outcome was death in the ICU. Results: ICU mortalities were similar in the testing and confirmatory cohorts (375/1000, 37.5% vs. 112/303, 37.0%, respectively). At baseline, most patients from the testing cohort (n = 792/1000, 79.2%) had a PaO2/FiO2 < 150, with similar mortality among the four subsets (p = 0.23). When assessed at 24 h, ICU mortality increased with an advance in the subset: 17.9%, 22.8%, 40.0%, and 49.3% (p < 0.0001). The findings were replicated in the confirmatory cohort (p < 0.0001). However, independent of the PEEP levels, patients with PaO2/FiO2 < 150 at 24 h followed a distinct 30-day ICU survival compared with patients with PaO2/FiO2 ≥ 150 (hazard ratio 2.8, 95% CI 2.2–3.5, p < 0.0001). Conclusions: Subsets based on PaO2/FiO2 thresholds of 150 mm Hg assessed after 24 h of moderate/severe ARDS diagnosis are clinically relevant for establishing prognosis, and are helpful for selecting adjunctive therapies for hypoxemia and for enrolling patients into therapeutic trials.

1. Introduction

Acute respiratory distress syndrome (ARDS) is a clinical-pathological entity [1] that is currently diagnosed using clinical and radiologic criteria [2,3] with poor accuracy and the low inter-rater reliability of clinicians [4,5]. Patients sharing the ARDS label differ in relation to the degree of lung injury and in their response to mechanical ventilation (MV) and adjunctive therapies [6]. The current definition of ARDS [2] accounts for the ratio of the partial pressure of arterial oxygen (PaO2) to the fraction of inspired oxygen (FiO2), or PaO2/FiO2, as a measure of hypoxemia at a positive end-expiratory pressure (PEEP) ≥ 5 cm H2O, regardless of the FiO2. In addition, the empirical cutoffs of baseline PaO2/FiO2 based on severity at 100, 200, and 300 mm Hg are somewhat arbitrary and have been inadequately validated [7,8,9,10,11].
The assessment of severity and prognosis in ARDS remains a challenge. The degree of hypoxemia in ARDS is a major determinant of the outcome [7,12], but the relationship between oxygenation and prognosis varies among published reports [7,8,9,10,13]. In ARDS, PEEP is applied to increase the lungs’ volume, keep the alveoli open, and improve oxygenation [14]. When PEEP recruits collapsed alveoli, the compliance of the respiratory system improves and increases the PaO2, although hypoxemia may coexist with minimally impaired lung compliance [15]. There is wide variation in the practice of choosing PEEP, but most patients with moderate to severe ARDS are managed with PEEP at ≥10 cm H2O in the first days of MV [9,16]. The progression of lung severity and the prognosis of ARDS has been reported to be related to changes in the PaO2/FiO2 in response to PEEP ≥ 10 [9,12]. Early identification of ARDS patients at a high risk of death after diagnosis would allow prompt escalation of therapeutic interventions, individualization of care, and precision in designing randomized clinical trials (RCTs). The challenges of the current definition of ARDS, which includes patients with different degrees of severity, make it difficult to successfully perform RCTs with positive findings that are highly generalizable [17].
In patients with ARDS, the PaO2/FiO2 ratio at ARDS onset/diagnosis is weakly associated with mortality. We hypothesized that setting a PaO2/FiO2 threshold of 150 mm Hg at 24 h from diagnosis of moderate/severe ARDS would improve predictions of the outcome in the intensive care unit (ICU). A PaO2/FiO2 threshold of 150 mm Hg has been used to identify patients for various interventions [18,19,20,21,22,23,24]. We previously reported a clinical classification system in a small population of 300 patients with moderate to severe ARDS to investigate whether the cutoff values of PaO2/FiO2 and PEEP would predict hospital mortality [25]. Boss et al. [26] validated the stratification model for hospital mortality in 519 ARDS patients, although the patients were not assessed with standardized ventilator settings. In this ancillary study, we have used a large population of moderate to severe ARDS patients to test and confirm whether the intersection of PaO2/FiO2 thresholds of 150 mm Hg and PEEP at 10 cm H2O could be useful for predicting ICU mortality and potential clinical translation.

2. Methods

This was an ancillary study using unrestricted data from our previously conducted and published studies [9,12,27,28] approved by the Ethics Committees of Hospital Universitario Dr. Negrín (Las Palmas de Gran Canaria, Spain), Hospital Virgen de la Luz (Cuenca, Spain), Hospital Clínico Universitario (Valladolid, Spain), and Hospital Universitario La Paz (Madrid, Spain), which have been adopted by all the participating centers, as required by Spanish legislation (see Supplementary File). The study was considered an audit, with waived informed consent (see the Supplementary File). The study followed the “Strengthening the Reporting of Observational Studies in Epidemiology” (STROBE) guidelines [29].

2.1. Patient Population, Study Design, and Oversight

We performed an ancillary analysis of the data derived from 1303 patients with moderate to severe ARDS treated with lung-protective MV included in our previously conducted and published studies [9,12,27,28]. The study was conducted in two steps (see the Supplementary File). First, we tested the classification model based on PaO2/FiO2 and PEEP cutoffs in 1000 patients admitted to a network of ICUs within the Spanish Initiative for Epidemiology, Stratification, and Therapies of ARDS (SIESTA) Program (see the Supplementary File). Data were pooled from three prospective observational multicenter cohorts (n = 300 patients in the ALIEN cohort, n = 300 patients in the STANDARDS cohort, and n = 400 patients in the STANDARDS-2 cohort) [9,12,27], enrolling consecutive patients managed with lung-protective MV (see the details in the Supplementary File) and who met the current criteria for moderate to severe ARDS [2], which included: (i) having an initiating clinical condition; (ii) symptoms developing within one week of a known clinical insult, or new or worsening respiratory symptoms; (iii) bilateral pulmonary infiltrates revealed by chest imaging (a chest radiograph or a computed tomography scan); (iv) the absence of left atrial hypertension or no clinical signs of left heart failure; and (v) hypoxemia, as defined by PaO2/FiO2 ≤ 200 mm Hg at PEEP ≥ 5 cm H2O regardless of the FiO2. Second, we confirmed the validity of the classification model in an independent cohort of 303 patients with moderate to severe ARDS managed with lung-protective MV who were included in a recent prospective observational multicenter study [28]. Each dataset had an adequate number of events (ICU deaths), as recommended [30].
All patients had arterial blood gases at study inclusion. We did not use SpO2 as a surrogate for PaO2 for enrolling patients. For identification of moderate/severe ARDS patients, the clinicians only considered qualifying blood gases while patients were clinically stable and did not consider transient falls in PaO2 resulting from acute events unrelated to the disease process (such as obstruction of the endotracheal tube by secretions, endotracheal suctioning, ventilator disconnection, or sudden pneumothorax, among others). No ICU patients meeting these criteria were excluded. We excluded patients younger than 18 years old; those with severe chronic pulmonary disease, acute cardiac failure, or brain death; patients with “do not resuscitate” orders; and postoperative patients receiving MV for <24 h (see the Supplementary File).

2.2. Data Collection and Outcomes

Day 0 was defined as the day and time when the patient first met the criteria for moderate to severe ARDS (see the Supplementary File). We collected information on the demographics, ARDS etiology, the Acute Physiology and Chronic Health Evaluation II (APACHE II) score [31], arterial blood gases, MV data, laboratory results, organ dysfunction (sequential organ failure assessment (SOFA) score) [32] at the onset of ARDS and after 24 h of treatment, and reported the primary cause of death in the ICU. We also recorded the duration of MV and calculated the number of ventilator-free days (VFDs) from the day of diagnosis of moderate/severe ARDS until Day 28 (see the Supplementary File).
The attending clinicians followed the current guidelines for general critical care management, which included the following: (i) in case of sepsis, physicians were urged to ensure early identification of the causative microorganism, to start intravenous administration of antibiotics as soon as sepsis was suspected or recognized, and to optimize antibiotic selection and timely administration on the basis of antibiograms; (ii) fluid resuscitation and vasopressor use were individualized, with the goal of maintaining a systolic blood pressure ≥ 90 mm Hg or a mean arterial pressure ≥ 65 mm Hg; (iii) to maintain the hemoglobin between 7 to 10 g/dL (see the Supplementary File). For ventilatory management, the clinicians followed the current recommendations for lung-protective MV [33,34], with a tidal volume (VT) of 4–8 mL per kg of predicted body weight (PBW), a ventilatory rate to maintain PaCO2 at 35 to 50 mm Hg (permissive hypercapnia was allowed to target VT), a plateau pressure of <30 cm H2O, and PEEP and FiO2 combinations to maintain PaO2 > 60 mm Hg or SpO2 > 90% (see the details in the Supplementary File).
At the time of ARDS diagnosis, all patients were ventilated with PEEP ≥ 5 cm H2O, as mandated by the current ARDS definition [2]. For the purpose of this study, PaO2/FiO2 and Pplat at 24 h of enrollment were assessed using a standardized ventilatory setting with PEEP = 10 cm H2O and FiO2 = 0.5 [9,12]. When patients required PEEP > 10 or FiO2 > 0.5, a set of rules for setting PEEP and FiO2 were applied only during the standardized assessment, as described and validated previously by our group [9,12]. We did not exclude any patient ventilated with PEEP < 10 cm H2O at 24 h due to the absence of the site investigator or because the clinician determined that it was not in the best interest of the patient to apply these settings (see the Supplementary File). At baseline and at 24 h, patients were classified into four possible groups or subsets, based on the intersection of the PaO2/FiO2 and PEEP values: Subset I, patients with PaO2/FiO2 ≥ 150 mm Hg at PEEP < 10 cm H2O; Subset II, PaO2/FiO2 ≥ 150 at PEEP ≥ 10; Subset III, PaO2/FiO2 < 150 at PEEP < 10; and Subset IV, PaO2/FiO2 < 150 at PEEP ≥ 10.
Patients were followed until ICU and hospital discharge. The primary outcome was all-cause ICU mortality. Secondary outcomes included the duration of MV, the number of VFDs up to Day 28 after moderate to severe ARDS diagnosis, and 30-day cumulative survival (see the Supplementary File).

2.3. Statistical Analysis

The plan of statistical analysis is provided in the Supplementary File. For the purpose of this study, we specified rules and expectations in advance [35] before the final statistical analyses were conducted (see the details in the Supplementary File). Quantitative variables are expressed as the means ± standard deviation (SD), and the median and 25th–75th percentiles (P25–P75). We used the Kolmogorov–Smirnov test to check for normal distribution of the data. We used Student’s t test or the Mann–Whitney test to compare two numerical variables, and ANOVA test to compare more than two numerical variables. We used Fisher’s exact test or Pearson’s Chi-squared test to check the relationships between categorical variables. We analyzed the probability of ICU survival to Day 30 for the initial four subsets and for the global subsets of patients with PaO2/FiO2 < 150 and ≥150 mm Hg at 24 h after moderate/severe ARDS diagnosis using the Kaplan–Meier method with the log-rank test. Patients discharged alive from the ICU before Day 30 of study inclusion were censored. No assumptions were made for missing data. We calculated the differences between the means, the risk ratio (RR), the odds ratio (OR), the hazard ratio (HR), and the 95% confidence intervals (CI).
We used dot-plots to present the distributions of PaO2/FiO2 versus PEEP at ARDS diagnosis and at 24 h. We used a multivariable logistic regression analysis for adjusting the performance of PaO2/FiO2 < 150 mm Hg for predicting severity and ICU mortality in relation to each patient’s age and SOFA score. Patients’ age and SOFA scores are strong, well-known predictors of outcome in critically ill patients [36]. We performed a sensitivity analysis testing two combinations of assumptions by using two thresholds of PaO2/FiO2 (100 and 120 mm Hg). For all comparisons, a two-sided p-value < 0.005 was considered to keep the false discovery rate below 5%, as recently recommended [37]. Analyses were performed using R Core Team 2022 software, version 4.2 (R Foundation for Statistical Computing, Vienna, Austria).

3. Results

All-cause ICU mortality rates were similar in the testing and confirmatory cohorts (375/1000, 37.5% vs. 112/303, 37.0%, respectively) (p = 0.920). Pneumonia, sepsis, aspiration, and trauma were the most common risk factors associated with the development of moderate/severe ARDS (Table 1). At baseline, most patients from the testing and confirmatory cohorts met the Berlin criteria for moderate ARDS (590/1000, 59% vs. 196/303, 64.7%, respectively), and their overall ICU mortality rates were similar (203/590, 34.4% vs. 64/196, 32.6%, respectively; RR 1.05, 95% CI 0.0.84–1.33, p = 0.665). The ICU mortality of patients meeting the criteria for severe ARDS were not different between the cohorts (172/410, 42% vs. 48/107, 44.9%, respectively; RR 1.10, 95% CI 0.78–1.54, p = 0.661).

3.1. ARDS Subsets at Baseline

At study entry, 792 patients (79.2%) from the testing cohort and 223 patients (73.6%) from the confirmatory cohort had PaO2/FiO2 < 150 mm Hg (Table 1). Their ICU mortality rate was not higher than that of patients with PaO2/FiO2 ≥ 150 mm Hg (testing cohort: 309/792 (39.0%) vs. 66/208 (31.7%); RR 1.22, 95% CI 0.0.99–1.53, p = 0.064; confirmatory cohort: 85/223 (38.1%) vs. 27/80 (33.8%); RR 1.13, 95% CI 0.80–1.60, p = 0.503).
Almost one-third of the patients (423/1303, 32.5%) were on PEEP < 10 cm H2O (313/1000 (31.3%) in the testing cohort and 110/303 (36.3%) in the confirmatory cohort), and their ICU mortality rates were not different from those of patients at PEEP ≥ 10 cm H2O (testing cohort: 122/313 (39.0%) vs. 253/687 (36.8%); RR 1.06, 95% CI 0.89–1.1.25, p = 0.527; confirmatory cohort: 43/110 (39.1%) vs. 69/193 (35.8%); RR 1.09, 95% CI 0.81–1.48, p = 0.647). The ICU mortality rates were not different among the four subsets (p = 0.229 for the testing cohort and p = 0.432 for the confirmatory cohort) (Table 2, Figure S1A).

3.2. ARDS Subsets at 24 h after Moderate/Severe ARDS Diagnosis

Only five patients (four in the testing and one in the confirmatory cohorts) died before 24 h after enrollment. Since these five patients had PaO2/FiO2 ≤ 100 mm Hg at PEEP ≥ 10 cm H2O and FiO2 > 0.5, they were included in the 24-h analysis. The distribution of the patients in each subset changed markedly at 24 h (Table 2, Figure 1 and Figure S1B). In total, 569 patients (56.9%) in the testing cohort and 136 patients (44.9%) in the confirmatory cohort still had a PaO2/FiO2 < 150 mm Hg, and their ICU mortality rate was much higher than that of patients with PaO2/FiO2 ≥ 150 (278/569 (48.9%) vs. 97/431 (22%); RR 2.17, 95% CI 1.79–2.64, p < 0.0001 in the testing cohort; and 80/136 (58.8%) vs. 32/167 (19.2%); RR 3.07, 95% CI 2.18–4.32, p < 0.0001 in the confirmatory cohort). The classification into four subsets at 24 h of ARDS diagnosis showed a strong association with ICU mortality (p < 0.001) (Figure 1B and Figure S1B). Cross-validation of the pooled data of the testing cohort confirmed that each individual study validated the subset model (Table S1).
At 24 h, patients in Subset IV showed higher mean SOFA scores than patients in the other subsets (Table 3 and Table S2). In Subset I, only five patients (17.9 %) from the testing cohort and five patients (14.3%) from the confirmatory cohort died in the ICU. The causes of death for each subset are listed in Table S3.

3.3. Probability of ICU Survival to Day 30

When considering the combined population of 1303 patients, patients with PaO2/FiO2 ≥ 150 mm Hg (Subsets I and II) had higher 30-day cumulative ICU survival compared with patients with PaO2/FiO2 < 150 mm Hg (Subsets III and IV) (Figure S2). Since Subsets I and III at 24 h of ARDS diagnosis had small sample sizes (n = 56 and n = 39, respectively), and a low number of ICU deaths (n = 9 and n = 17, respectively), they were of little interest in this study for predicting ICU mortality and did not influence the outcome or a clinical understanding. As a result, we aggregated patients with PaO2/FiO2 ≥ 150 mm Hg (Subsets I and II) and patients with PaO2/FiO2 < 150 mm Hg (Subsets III and IV) for examining the overall 30-day ICU cumulative survival in the two categories.
Patients with PaO2/FiO2 ≥ 150 mm Hg at 24 h had 30-day higher survival compared with patients with PaO2/FiO2 < 150 mm Hg (HR 2.8, 95% CI 2.2–3.5, p < 0.0001) (Table S4, Figure 2). In general, patients with PaO2/FiO2 < 150 mm Hg at 24 h had a higher mean plateau pressure, required higher levels of FiO2, had a higher SOFA score, and had fewer ventilator-free days (Table S4).
When the impact of PaO2/FiO2 < 150 mm Hg on ICU mortality was adjusted by the patients’ age and SOFA scores, PaO2/FiO2 < 150 at 24 h remained the major determinant of ICU death (OR 3.1 (95% CI 2.4–4.0) (Table S5).

3.4. Additional Analysis with Different PaO2/FiO2 Cutoff Values

PaO2/FiO2 cutoff values of 100 or 120 mm Hg did not provide more reliable outcome predictions at ARDS diagnosis or at 24 h after diagnosis (Tables S6 and S7).

4. Discussion

The major findings of this study are as follows. First stratification of moderate to severe ARDS patients at onset/diagnosis based on PaO2/FiO2 ratio greater than vs. less than 150 mm Hg did not predict ICU mortality. Second, the two major categories of patients based on PaO2/FiO2 at 24 h had markedly different ICU outcomes: for PaO2/FiO2 ≥ 150 mm Hg, the ICU mortality rate was about 20% and for PaO2/FiO2 < 150 mm Hg, the ICU mortality rate was greater than 45%.
The baseline gas exchange criteria for the definition of ARDS captured a highly heterogeneous group of patients with a spectrum of severity that represented fundamental differences in their pathophysiology and responses to specific therapies [38]. By changing the time of reassessment of the oxygenation defect to 24 h, and by using standardized ventilator settings, we identified subsets of moderate/severe ARDS patients with markedly different levels of risk of ICU death. Since there is no typical ARDS patient [1], the most critical factor in managing ARDS is the initiation of lung-protective MV after intubation [6], although the optimal MV strategy remains uncertain. The history of interventional RCTs of ARDS is full of failures, with few successes in the last decade [39]. Most RCTs of ARDS have not tested whether the experimental management or therapy is beneficial after assessing the degree of hypoxemia after 24 h of routine intensive management prior to randomization [39,40]. We need an ARDS classification system that can serve as a prototype to help set individual therapeutic targets, as in other critical conditions [41]. Developing an ARDS-specific stratification or sub-phenotyping model for guiding therapy and predicting outcomes is clinically relevant, because this heterogeneous syndrome is complex and evolves rapidly, and more than one-third of patients with moderate to severe ARDS do not leave the hospital alive.
Although categorization of continuous predictors (such as below vs. above a certain cutoff) should be avoided in the development of a model, the exception is when a well-accepted threshold is used in clinical practice [42]. A PaO2/FiO2 cutoff of 150 mm Hg seems to be appropriate, not only to discriminate between patients with higher or lower mortality but also for guiding medical therapy [18,19,20,21,22,23,24,25,26,43]. In our study, almost one-third of patients (423/1303, 32.5%) were ventilated with PEEP < 10 cm H2O at the time of moderate/severe ARDS diagnosis, a finding that is in line with recent reports on most successful and unsuccessful RCTs conducted in ARDS patients and published since 2010, where many patients were ventilated with PEEP < 10 cm H2O on average at inclusion into the trial and on the first day of randomization [39,44]. The European Collaborative Study [19] performed an observational study from 1985 to 1987 and analyzed 583 patients with ARDS in which hypoxemia was defined as a PaO2 < 75 mm Hg with FiO2 ≥ 0.5 at PEEP ≥ 5 cm H2O for at least 24 h. In that study, the mortality rate of ARDS patients with PaO2/FiO2 < 150 at 24 h was almost double the mortality rate of patients with PaO2/FiO2 ≥ 150 mm Hg. Using a similar study design to the European Collaborative Study, Villar et al. [20] published a pilot study in 1999 in a small population of 56 patients meeting the American–European Consensus Conference definition for ARDS, and found that the responses of PaO2 to PEEP after 24 h of the meeting ARDS criteria allowed a clear separation of the patients into two different groups with markedly different mortality rates. Three recent RCTs used a value of PaO2/FiO2 < 150 mm Hg at PEEP ≥ 5 [21,22] or ≥8 cm H2O [24] to enroll patients during the first 24–48 h of ARDS diagnosis. It is plausible that in a substantial proportion of the patients in recent RCTs, the severity of lung injury was modest. If patients have a low risk of the condition to be prevented, any trial will not validate the value of the intervention in the study [45]. Optimizing the selection of ARDS patients is central to the likelihood of successful trial design.
Our classification system uses two variables, PaO2/FiO2 and PEEP, which are particularly relevant for the diagnosis and ventilatory management of ARDS. However, we think that the key feature in our study was the time (waiting for 24 h), while PEEP was relatively unimportant because very few patients had PEEP < 10 cm H2O at 24 h after a diagnosis of moderate/severe ARDS. These ARDS subsets could be relevant for establishing prognoses, for selecting individualized therapies, and for helping to identify patients in whom benefit from treatment may be limited or disproportional to the resources used. Clearly, selection of the therapy for an individual ARDS patient involves both an assessment of respiratory dysfunction, as measured by the PaO2/FiO2 after 24 h of routine care, and an evaluation of the PEEP response. Not all ARDS is created equal. Distinguishing the level of lung severity of ARDS is critical for successful treatment, since there are certain ventilator and oxygenation therapeutic modalities that are not required in all patients. Subset I represents the less severe ARDS patients. Although, ideally, one aim of ventilating ARDS patients is to recruit consolidated and atelectatic alveolar units and decrease ventilator-induced lung injury [6], less than 50% of patients in our study achieved a PaO2/FiO2 ≥ 150 mm Hg with PEEP ≥ 10 at 24 h. It is plausible that the mortality rates in Subsets I and II are so low that it may have reached a lower limit that was dictated more by the underlying disease than by the syndrome itself [46]. Although a diagnosis of ARDS does not suggest any specific pharmacologic treatment, the underlying conditions or etiological diseases that cause ARDS are important root causes of mortality in ARDS [27]. The enrollment of mechanically ventilated ARDS patients with rapidly improving ARDS, such as those in Subsets I and II, may contribute to the failure of therapeutic RCTs [47]. Some patients from Subset III may have had a PaO2/FiO2 < 150 mm Hg as a result of insufficient PEEP, although in some patients, the best PEEP, according to lung compliance, could be <10 cm H2O [15,48]. Patients in Subset IV represent the most critical category and appear to be very resistant to therapy, suggesting that these patients should be the target for aggressive and innovative therapies. Further validations and evaluations of interventions for each subset are necessary.
Our study has several strengths. First, we have studied a large population of patients with moderate to severe ARDS managed with lung-protective MV admitted to a multidisciplinary network of ICUs. Since this was an observational study with practically no exclusion criteria, we believe that our patient population represents unselected patients under the wide syndromic umbrella of moderate to severe ARDS. We do not think that there was a relevant effect of time on our findings, since this type of combined analysis of several hundreds of patients from independent cohorts has been used extensively by other authors using heterogeneous populations from previous published clinical trials [49,50,51] (see the Supplementary File). Our model applies only to patients with moderate/severe ARDS while they are intubated and mechanically ventilated in line with a lung-protective ventilation approach. Second, our classification system is in line with recent recommendations [52] stating that better identification of patient populations is the key for appropriate characterization of the patients’ status. Third, PaO2/FiO2 was examined in line with a standardized ventilatory approach at 24 h, although five severe ARDS patients died before 24 h, and 20 patients with PaO2/FiO2 < 150 mm Hg were not assessed at PEEP ≥ 10 cm H2O for several reasons (see the Supplementary File).
We also acknowledge that our study has potential limitations. First, we did not enroll ARDS patients with persistent PaO2/FiO2 > 200 mm Hg during the ICU stay (see the Supplementary File). However, we do not believe that the exclusion of “mild” ARDS weakens our findings, since patients with mild ARDS represent a case-mix of patients in which many patients may not require invasive MV. Second, the classification at the time of moderate/severe ARDS onset/diagnosis, as mandated by the current ARDS definition, was not assessed using standardized ventilator settings, such as we applied at 24 h. However, a previous report examining the baseline PaO2/FiO2 values under standardized ventilatory settings showed that the baseline PaO2/FiO2 was not helpful for predicting the outcome compared with PaO2/FiO2 at 24 h [7,9]. Third, regarding the limitation of waiting 24 h for enrolling patients into RCTs, we need other studies to examine whether these ARDS subsets could be established at 12 or 18 h after ARDS diagnosis. Although most RCTs in ARDS since 1990 have considered enrolling patients within 24–48 h after ARDS diagnosis [44], in some trials, patients were enrolled at a median or mean time of 7.6 h [24], 22 h [21], or 33 h [22], although others included patients enrolled at <72 h from ARDS diagnosis [53]. Fourth, similar to most clinical investigators, we did not assess the compliance of physicians with our recommended guidelines for many therapies. Finally, we could address the impact that the Spanish healthcare system may have had on the generalizability of our results to other healthcare systems.
In conclusion, two clinical variables, namely PaO2/FiO2 (<150 mm Hg vs. ≥150 mm Hg) and PEEP (<10 cm H2O vs. ≥10 cm H2O) at 24 h after moderate/severe ARDS onset, seem to be essential for identifying ARDS subsets that could be used to guide medical therapy, to predict ICU outcomes, and to enroll patients in RCTs. Further confirmation and impact studies should evaluate whether the implementation of this classification and prediction model in clinical practice improves patient outcomes by informing therapeutic decisions.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jcm11195724/s1.

Author Contributions

J.V., C.F. (Carlos Ferrando), E.W.S., L.B. and A.S.S. contributed to the initial study concept and design. J.V., J.M.A., C.F. (Carlos Ferrando) and P.R.-S. obtained funding for the study. All authors contributed to the final study design, participated in its coordination, or participated in drafting the original manuscript. C.F. (Carlos Ferrando), J.M.A., A.M.d.S.-O., A.D.-L., A.B.-G., L.F., A.M.D.-B., E.P., D.A.-O., E.G.-H., A.V., M.M.F., J.M.M.-O., I.M., C.T., E.M., A.P., M.A.R., F.A. and D.P. enrolled patients into the study and participated in data collection, data analysis, and writing and editing the final draft of the manuscript. J.V., R.L.F., C.F. (Cristina Fernández), J.M.G.-M., E.W.S., L.B. and A.S.S. are responsible for data analysis and/or interpretation of the data. J.V., R.L.F., C.F. (Cristina Fernández) and J.M.G.-M. had full access to all data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Members of the SIESTA network participated in the enrollment of patients into the study and/or in the study design. All authors have read and agreed to the published version of the manuscript.

Funding

There was no specific funding source for this study. J.V. received grants from Instituto de Salud Carlos III, Madrid, Spain (PI16/00049, PI19/00141); The European Regional Development Funds; and the Asociación Científica Pulmón y Ventilación Mecánica, Las Palmas de Gran Canaria, Spain. J.V., J.M.A., and C. Ferrando received grant support from the Instituto de Salud Carlos III, Madrid, Spain (CB06/06/1088). L.B. receives salary support from K23 HL128882/NHLBI NIH, receives research funds from the Reginald Jenney Endowment Chair at Harvard Medical School, sundry funds from the Massachusetts General Hospital, and research grants from iNO Therapeutics LLC. A.S.S. is funded by the Canadian Institutes of Health Research (grants #137772 and FDN143285). The authors would like to thank Yasser and Lily B. of LP Bahrain for their support in loving memory of Lily Bendahan.

Institutional Review Board Statement

The study was approved by the Ethics Committees for Clinical Research of Hospital Universitario Negrín (Las Palmas de Gran Canaria, Spain, #2008-0915-EPI), Hospital Virgen de la Luz (Cuenca, Spain, #2014/PI-1114), Hospital Clínico Universitario (Valladolid, Spain, #PI17-594), and Hospital Universitario La Paz (Madrid, Spain, #PI-2694), which were adopted by all participating centers, as required by Spanish legislation. This study followed current Spanish legislation for biomedical research, fulfilling the standards indicated by the Declaration of Helsinki. The study was considered an audit, and informed consent was waived, although two local sites required informed consent as per the institution’s policies (see the details in the Supplementary File).

Informed Consent Statement

Not applicable.

Data Availability Statement

All data needed to evaluate the conclusions in this article are presented and tabulated in the main text or the Supplementary File. Data are available from the corresponding author on reasonable request.

Conflicts of Interest

All authors declare no competing interest. None of the clinical investigators received any honorarium for participating in the study.

Abbreviations

APACHE II: Acute Physiology and Chronic Health Evaluation II score; ARDS: acute respiratory distress syndrome; CI: confidence intervals; FiO2: fraction of inspired oxygen; HR: hazard ratio; ICU: intensive care unit; MV: mechanical ventilation; OR: odds ratio; PaCO2: partial pressure of carbon dioxide in arterial blood; PaO2: partial pressure of arterial oxygen; PaO2/FiO2: partial pressure of oxygen in arterial blood/inspired oxygen fraction ratio; PBW: predicted body weight; PEEP: positive end-expiratory pressure; P25–P75: 25th–75th percentiles; RCT: randomized controlled trial; RR: risk ratio; SD: standard deviation; SIESTA: Spanish Initiative for Epidemiology, Stratification, and Therapies of ARDS; SOFA: Sequential Organ Failure Assessment; SpO2: oxygen saturation; STROBE: Strengthening the Reporting of Observational Studies in Epidemiology; VFD: ventilator-free days; VT: tidal volume.

Appendix A. Members of the SIESTA Network Are Listed below

  • Jesús Villar, Rosa L. Fernández, Cristina Fernández, Jesús M. González-Martin, Pedro Rodríguez-Suárez (Hospital Universitario Dr. Negrín, Las Palmas de Gran Canaria, Spain);
  • Alfonso Ambrós, Rafael del Campo, Carmen Martín-Rodríguez, Ana Bueno-González, Carmen Hornos-López (Hospital General Universitario, Ciudad Real, Spain);
  • Fernando Mosteiro, Ana M. Díaz-Lamas, Regina Arrojo, Lidia Pita-García (Complejo Hospitalario Universitario de La Coruña, La Coruña, Spain);
  • Lorena Fernández, Jesús Sánchez-Ballesteros, Jesús Blanco, Arturo Muriel, Pablo Blanco-Schweizer, José Ángel de Ayala, César Aldecoa, Jesús Rico-Feijoo, Alba Pérez, Silvia Martín-Alfonso (Hospital Universitario Río Hortega, Valladolid, Spain);
  • Domingo Martínez, Juan A. Soler, Ana M. del Saz-Ortiz, Luís A. Conesa-Cayuela (Hospital Universitario Virgen de Arrixaca, Murcia, Spain);
  • Demetrio Carriedo, Ana M. Domínguez-Berrot, Francisco J. Díaz-Domínguez, Raúl I. González-Luengo (Complejo Hospitalario Universitario de León, León, Spain);
  • Lucia Capilla (Hospital General Universitario Rafael Méndez, Lorca, Murcia, Spain);
  • David Andaluz, Leonor Nogales, Laura Parra (Hospital Clínico Universitario, Valladolid, Spain);
  • Elena González-Higueras, Rosario Solano, María J. Bruscas (Hospital Virgen de la Luz, Cuenca, Spain);
  • Blanca Arocas, Marina Soro, Javier Belda, Andrea Gutiérrez, Ernesto Pastor, Gerardo Aguilar (Hospital Clínico Universitario, Valencia, Spain);
  • Carlos Ferrando (Hospital Clinic, Barcelona, Spain);
  • José M. Añón, Belén Civantos, Mónica Hernández (Hospital Universitario La Paz, Madrid, Spain);
  • Raquel Montiel, Dácil Parrilla, Eduardo Peinado, Lina Pérez-Méndez (Hospital Universitario NS de Candelaria, Tenerife, Spain);
  • Anxela Vidal, Denis Robaglia, César Pérez (Hospital Universitario Fundación Jiménez Díaz, Madrid, Spain);
  • María del Mar Fernández (Hospital Universitario Mutua Terrassa, Terrassa, Barcelona, Spain);
  • Eleuterio Merayo, Chanel Martínez-Jiménez, Ángeles de Celis-Álvarez (Hospital del Bierzo, Ponferrada, León, Spain);
  • Juan M. Mora-Ordoñez, J. Francisco Martínez-Carmona, Álvaro Valverde-Monto, Victoria Olea-Jiménez (Hospital Regional Universitario de Málaga, Málaga, Spain);
  • Concepción Tarancón, Silvia Cortés-Díaz (Hospital Virgen de la Concha, Zamora, Spain);
  • Carmen Martín-Delgado (Hospital La Mancha Centro, Alcázar de San Juan, Ciudad Real, Spain);
  • Francisca Prieto (Hospital Santa Bárbara, Puertollano, Ciudad Real, Spain);
  • Isidro Prieto, Mario Chico, Darío Toral (Hospital Universitario 12 de Octubre, Madrid, Spain);
  • Miguel A. Romera, Carlos Chamorro-Jambrina (Hospital Universitario Puerta de Hierro, Majadahonda, Madrid, Spain);
  • Alec Tallet, Santiago Macías, Noelia Lázaro (Hospital General de Segovia, Segovia, Spain);
  • Isabel Murcia, Ángel E. Pereyra (Hospital General Universitario de Albacete, Albacete, Spain);
  • Francisco Alba, Ruth Corpas (Hospital NS del Prado, Talavera de la Reina, Toledo, Spain);
  • David Pestaña, Pilar Cobeta, Adrián Mira (Hospital Universitario Ramón y Cajal, Madrid, Spain);
  • Francisca Prieto (Hospital Santa Barbara, Puertollano, Ciudad Real, Spain);
  • Lluis Blanch, Gemma Gomá, Gisela Pili (Corporació Sanitaria Parc Taulí, Sabadell, Barcelona, Spain);
  • Antonio Santos-Bouza, Cristina Domínguez (Complejo Hospitalario Universitario de Santiago, Santiago de Compostela, La Coruña, Spain);
  • Javier Collado, José I. Alonso (Hospital Río Carrión, Palencia, Spain);
  • Alberto Indarte, María E. Perea (Hospital General Yagüe, Burgos, Spain);
  • Ricardo Fernández, José I. Lozano (Hospital de Hellín, Albacete, Spain)
  • Ewout W. Steyerberg (Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands);
  • Robert M. Kacmarek (deceased), Lorenzo Berra (Massachussets General Hospital, Boston, Massachusetts, USA);
  • Arthur S. Slutsky (Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Ontario, Canada).

References

  1. Villar, J. What is the acute respiratory distress syndrome? Respir. Care 2011, 56, 1539–1545. [Google Scholar] [CrossRef] [PubMed]
  2. Ranieri, V.M.; Rubenfeld, G.D.; Thompson, B.T.; Ferguson, N.D.; Caldwell, E.; Fan, E.; Camporota, L.; Slutsky, A.S. Acute respiratory distress syndrome: The Berlin definition. JAMA 2012, 307, 2526–2533. [Google Scholar] [PubMed]
  3. Villar, J.; Pérez-Méndez, L.; Kacmarek, R.M. The Berlin definition met our needs: No. Intensive Care Med. 2016, 42, 648–650. [Google Scholar] [CrossRef]
  4. Peng, J.M.; Qian, C.Y.; Yu, X.Y.; Zhao, M.Y.; Li, S.S.; Ma, X.C.; Kang, Y.; Zhou, F.C.; He, Z.H.; Qin, T.H.; et al. Does training improve diagnostic accuracy and inter-rater agreement in applying the Berlin radiographic definition of acute respiratory distress syndrome? A multicenter prospective study. Crit. Care 2017, 21, 12. [Google Scholar] [CrossRef] [PubMed]
  5. Fountain, S.; Assar, S.; Heise, C.; Curry, S.; Raschke, R.A. What’s in a chest radiograph? Inter-rater variability in determining acute respiratory distress syndrome. Am. J. Resp. Crit. Care Med. 2018, 197, A5063. [Google Scholar]
  6. Villar, J.; Slutsky, A.S. GOLDEN anniversary of the acute respiratory distress syndrome: Still much work to do! Curr. Opin. Crit. Care 2017, 23, 4–9. [Google Scholar] [CrossRef] [PubMed]
  7. Villar, J.; Blanco, J.; del Campo, R.; Andaluz-Ojeda, D.; Díaz-Domínguez, F.J.; Muriel, A.; Córcoles, V.; Suárez-Sipmann, F.; Tarancón, C.; González-Higueras, E.; et al. Assessment of PaO2/FiO2 for stratification of patients with moderate and severe acute respiratory distress syndrome. BMJ Open 2015, 5, 1006812. [Google Scholar] [CrossRef]
  8. Hernu, R.; Wallet, F.; Thiolliére, F.; Martin, O.; Richard, J.C.; Schmitt, Z.; Wallon, G.; Delannoy, B.; Rimmelé, T.; Démeret, C.; et al. An attempt to validate the modification of the American-European consensus definition of acute lung injury/acute respiratory distress syndrome by the Berlin definition in a university hospital. Intensive Care Med. 2013, 39, 2161–2170. [Google Scholar] [CrossRef]
  9. Villar, J.; Pérez-Méndez, L.; Blanco, J.; Añón, J.M.; Blanch, L.; Belda, J.; Santos-Souza, A.; Fernández, R.L.; Kacmarek, R.M.; Spanish Initiative for Epidemiology, Stratification, and Therapies for ARDS (SIESTA) Network. A universal definition of ARDS: The PaO2/FiO2 ratio under a standard ventilatory setting—A prospective, multicenter validation study. Intensive Care Med. 2013, 39, 583–592. [Google Scholar] [CrossRef]
  10. Huber, W.; Findeissen, M.; Lahmer, T.; Herner, A.; Rasch, S.; Mayr, U.; Hoppmann, P.; Jaitner, J.; Okrojek, R.; Brettner, F.; et al. Prediction of outcome in patients with ARDS: A prospective cohort study comparing ARDS-definitions and other ARDS-associated parameters, ratios and scores at intubation and over time. PLoS ONE 2020, 15, e0232720. [Google Scholar] [CrossRef]
  11. Phillips, C.R. The Berlin definition: Real change or the emperor’s new clothes? Crit. Care 2013, 17, 174. [Google Scholar] [CrossRef] [Green Version]
  12. Villar, J.; Pérez-Méndez, L.; López, J.; Belda, J.; Blanco, J.; Saralegui, I.; Suárez-Sipmann, F.; López, J.; Lubillo, S.; Kacmarek, R.M.; et al. An early PEEP/FiO2 trial identifies different degrees of lung injury in patients with acute respiratory distress syndrome. Am. J. Respir. Crit. Care Med. 2007, 176, 795–804. [Google Scholar] [CrossRef] [PubMed]
  13. Kamo, T.; Tasaka, S.; Susuki, T.; Asakura, T.; Susuki, S.; Yagi, K.; Namkoong, H.; Ishii, M.; Morisaki, H.; Betsuyaku, T. Prognostic values of the Berlin definition criteria, blood lactate levels, and fibroproliferative changes on high-resolution computed tomography in ARDS patients. BMC Pulm. Med. 2019, 19, 37. [Google Scholar] [CrossRef]
  14. Shapiro, B.A.; Cane, R.D.; Harrison, R.A. Positive end-expiratory pressure therapy in adults with special reference to acute lung injury: A review of the literature and suggested clinical correlations. Crit. Care Med. 1984, 12, 127–141. [Google Scholar] [CrossRef]
  15. Cove, M.E.; Pinsky, M.R.; Marini, J.J. Are we ready to think differently about setting PEEP? Crit. Care 2022, 26, 222. [Google Scholar] [CrossRef]
  16. Briel, M.; Meade, M.; Mercat, A.; Brower, R.G.; Talmor, D.; Walter, S.D.; Slutsky, A.S.; Pullenayegum, E.; Zhou, Q.; Cook, D.; et al. Higher vs lower positive end-expiratory pressure in patients with acute lung injury and acute respiratory distress syndrome: Systematic review and meta-analysis. JAMA 2010, 303, 865–873. [Google Scholar] [CrossRef]
  17. Kang, M.; Kempker, J.A. Definitions, epidemiology, clinical risk factors, and health disparities in acute respiratory distress syndrome. Sem. Respir. Crit. Care Med. 2019, 40, 3–11. [Google Scholar] [CrossRef]
  18. Bone, R.C.; Maunder, R.; Slotman, G.; Silverman, H.; Hyers, T.M.; Kerstein, M.D.; Ursprung, J.J. Prostaglandin E1 Study Group. An early test of survival in patients with the adult respiratory distress syndrome. The PaO2/FiO2 ratio and its differential response to conventional therapy. Chest 1989, 96, 849–851. [Google Scholar] [CrossRef] [PubMed]
  19. Artigas, A.; Carlet, J.; LeGall, J.R.; Chastang, C.; Blanch, L.; Fernández, R. Clinical presentation, prognostic factors and outcome of ARDS in the European Collaborative Study (1985–1987). In Adult Respiratory Distress Syndrom; Zapol, W.M., Lemaire, F., Eds.; A preliminary report; Dekker: New York, NY, USA, 1991; pp. 37–64. [Google Scholar]
  20. Villar, J.; Pérez-Méndez, L.; Kacmarek, R.M. Current definitions of acute lung injury and the acute respiratory distress syndrome do not reflect their true severity and outcome. Intensive Care Med. 1999, 25, 930–935. [Google Scholar] [CrossRef] [PubMed]
  21. Papazian, L.; Forel, J.M.; Gacouin, A.; Penot-Ragon, C.; Perrin, G.; Loundou, A.; Jaber, S.; Arnal, J.M.; Perez, D.; Seghboyan, J.M.; et al. Neuromuscular blockers in early acute respiratory distress syndrome. N. Engl. J. Med. 2010, 363, 1107–1116. [Google Scholar] [CrossRef] [PubMed]
  22. Guérin, C.; Reignier, J.; Richard, J.C.; Beuret, P.; Gacouin, A.; Boulain, T.; Clavel, M.; Chatellier, D.; Jaber, S.; Rosselli, S.; et al. Prone positioning in severe acute respiratory distress syndrome. N. Engl. J. Med. 2013, 368, 2159–2168. [Google Scholar] [CrossRef] [PubMed]
  23. Maiolo, G.; Collino, F.; Vasques, F.; Rapetti, F.; Tonetti, T.; Romitti, F.; Cressoni, M.; Chiumello, D.; Moerer, O.; Herrmann, P.; et al. Reclassifying acute respiratory distress syndrome. Am. J. Respir. Crit. Care Med. 2018, 197, 1586–1595. [Google Scholar] [CrossRef] [PubMed]
  24. The National Heart, Lung, and Blood Institute Petal Clinical Trials Network; Moss, M.; Huang, D.; Brower, R.G.; Ferguson, N.D.; Ginde, A.A.; Gong, M.N.; Grissom, C.K.; Gundel, S.; Hayden, D.; et al. Early neuromuscular blockade in the acute respiratpry distress syndrome. N. Engl. J. Med. 2019, 380, 1997–2008. [Google Scholar] [PubMed]
  25. Villar, J.; Fernández, R.L.; Ambrós, A.; Parra, L.; Blanco, J.; Domínguez-Berrot, A.M.; Gutiérrez, J.M.; Blanch, L.; Añón, J.M.; Martín, C.; et al. A clinical classification of the acute respiratory distress syndrome for predicting outcome and guiding therapy. Crit. Care Med. 2015, 43, 346–353. [Google Scholar] [CrossRef] [PubMed]
  26. Bos, L.D.; Cremer, O.L.; Ong, D.S.Y.; Caser, E.B.; Barbas, C.S.V.; Villar, J.; Kacmarek, R.M.; Schultz, M.J.; MARS Consortium. External validation confirms the legitimacy of a new clinical classification of ARDS for predicting outcome. Intensive Care Med. 2015, 41, 2004–2005. [Google Scholar] [CrossRef] [PubMed]
  27. Villar, J.; Martínez, D.; Mosteiro, F.; Ambrós, A.; Añón, J.M.; Ferrando, C.; Soler, J.A.; Montiel, R.; Vidal, A.; Conesa-Cayuela, L.A.; et al. Stratification and Outcome of Acute Respiratory Distress Syndrome (STANDARDS) Network. Is overall mortality the right composite endpoint in clinical trials of acute respiratory distress syndrome? Crit. Care Med. 2018, 46, 892–899. [Google Scholar] [CrossRef]
  28. Villar, J.; Mora-Ordoñez, J.M.; Soler, J.A.; Mosteiro, F.; Vidal, A.; Ambrós, A.; Fernández, L.; Murcia, I.; Civantos, B.; Romera, M.A.; et al. The PANDORA study: Prevalence and outcome of acute hypoxemic respiratory failure in the pre-COVID era. Crit. Care Explor. 2022, 4, e0684. [Google Scholar] [CrossRef] [PubMed]
  29. Von Elm, E.; Altman, D.G.; Egger, M.; Pocock, S.J.; Gøtzsche, P.C.; Vandenbroucke, J.P.; for the STROBE Initiative. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. PLoS Med. 2007, 4(e296). [Google Scholar] [CrossRef]
  30. Vergouwe, Y.; Steyerberg, E.W.; Eijkemans, M.J.C.; Habbema, J.D.F. Substantial effective sample sizes were required for external validation studies of predictive logistic regression models. J. Clin. Epidemiol. 2005, 58, 475–483. [Google Scholar] [CrossRef]
  31. Knaus, W.A.; Draper, E.A.; Wagner, D.P.; Zimmerman, J.E. APACHE II: A severity of disease classification system. Crit. Care Med. 1985, 13, 818–829. [Google Scholar] [CrossRef]
  32. Vincent, J.L.; de Mendonça, A.; Cantraine, F.; Moreno, R.; Takala, J.; Suter, P.M.; Sprung, C.L.; Colardyn, F.; Blecher, S. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: Results of a multicenter, prospective study. Working group on “sepsis-related problems” of the European Society of Intensive Care Medicine. Cri. Care Med. 1998, 26, 1793–1800. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Acute Respiratory Distress Syndrome Network. Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. N. Engl. J. Med. 2000, 342, 1301–1308. [Google Scholar] [CrossRef]
  34. Fan, E.; Del Sorbo, L.; Goligher, E.C.; Hodgson, C.L.; Munshi, L.; Walkey, A.J.; Adhikari, N.K.J.; Amato, M.B.P.; Branson, R.; Brower, R.G.; et al. American Thoracic Society, European Society of Intensive Care Medicine, and Society of Critical Care Medicine. An official American Thoracic Society/European Society of Intensive Care Medicine/Society of Critical Care Medicine Clinical Practice Guideline: Mechanical ventilation in adult patients with acute respiratory distress syndrome. Am. J. Respir. Crit. Care Med. 2017, 195, 1253–1263. [Google Scholar] [CrossRef]
  35. Ioannidis, J.P.A. The importance of predefined rules and prespecified statistical analyses. Do not abandon significance. JAMA 2019, 321, 2067–2068. [Google Scholar] [CrossRef]
  36. Villar, J.; Ambrós, A.; Mosteiro, F.; Martínez, D.; Fernández, L.; Ferrando, C.; Carriedo, D.; Soler, J.A.; Parrilla, D.; Hernández, M.; et al. A prognostic enrichment strategy for selection of patients with acute respiratory distress syndrome in clinical trials. Crit. Care Med. 2019, 47, 377–385. [Google Scholar] [CrossRef] [PubMed]
  37. Ioannidis, J.P.A. The proposal to lower p value thresholds to 0.005. JAMA 2018, 319, 1429–1430. [Google Scholar] [CrossRef] [PubMed]
  38. Matthay, M.A.; McAuley, D.F.; Ware, L.B. Clinical trials in acute respiratory distress syndrome: Challenges and opportunities. Lancet Respir. Med. 2017, 5, 524–534. [Google Scholar] [CrossRef]
  39. Villar, J.; Ferrando, C.; Tusman, G.; Berra, L.; Rodríguez-Suárez, P.; Suárez-Sipmann, F. Unsuccessful and successful clinical trials in acute respiratory distress syndrome: Addressing physiology-based gaps. Front. Physiol 2021, 12, 774025. [Google Scholar] [CrossRef]
  40. Juschten, J.; Tuinman, P.R.; Guo, T.; Juffermans, N.P.; Schultz, M.J.; Loer, S.A.; Girbes, A.R.J.; de Grooth, H.J. Between-trial heterogeneity in ARDS research. Intensive Care Med. 2021, 47, 422–434. [Google Scholar] [CrossRef]
  41. Forrester, J.S.; Diamond, G.A.; Swan, H.J.C. Correlative classification of clinical and hemodynamic function after acute myocardial infarction. Am. J. Cardiol. 1977, 39, 137–145. [Google Scholar] [CrossRef]
  42. Steyerberg, E.W.; Vergouwe, Y. Towards better clinical prediction models: Seven steps for development and an ABCD for validation. Eur. Heart J. 2014, 35, 1925–1931. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Qadir, N.; Bartz, R.R.; Cooter, M.L.; Hough, C.L.; Lanspa, M.J.; Banner-Goodspeed, V.M.; Chen, J.T.; Giovanni, S.; Gomaa, D.; Sjoding, M.W.; et al. Variation in early management practices in moderate-to-severe ADS in the United States. The Severe ARDS-generating evidence study. Chest 2021, 160, 1304–1315. [Google Scholar] [CrossRef] [PubMed]
  44. Villar, J.; Suárez-Sipmann, F.; Kacmarek, R.M. Should the ART trial change our practice? J. Thorac. Dis. 2017, 9, 4871–4877. [Google Scholar] [CrossRef] [PubMed]
  45. Villar, J.; Pérez-Méndez, L.; Aguirre-Jaime, A.; Kacmarek, R.M. Why are physicians so skeptical about positive randomized controlled trials in critical care medicine? Intensive Care Med. 2005, 31, 196–204. [Google Scholar] [CrossRef] [PubMed]
  46. Bernard, G. Acute lung failure—our evolving understanding of ARDS. N. Engl. J. Med. 2017, 377, 507–509. [Google Scholar] [CrossRef] [PubMed]
  47. Schenck, E.J.; Oromendia, C.; Torres, L.K.; Berlin, D.A.; Choi, A.M.K.; Siempos, I.I. Rapidly improving ARDS in therapeutic randomized controlled trials. Chest 2019, 155, 474–482. [Google Scholar] [CrossRef] [PubMed]
  48. Rezoagli, E.; Bellani, G. How I set up positive end-expiratory pressure: Evidence- and physiology-based. Crit. Care 2019, 23, 412. [Google Scholar] [CrossRef]
  49. Amato, M.B.; Meade, M.O.; Slutsky, A.S.; Brochard, L.; Costa, E.L.; Schoenfeld, D.A.; Stewerst, T.E.; Briel, M.; Talmor, D.; Mercat, A.; et al. Driving pressure and survival in the acute respiratory distress syndrome. N. Engl. J. Med. 2015, 372, 747–755. [Google Scholar] [CrossRef]
  50. Metkus, T.S.; Guallar, E.; Sokoll, L.; Morrow, D.; Tomaselli, G.; Brower, R.; Schulman, S.; Korley, F.K. Prevalence and prognostic association of circulating troponin in acute respiratory distress syndrome. Crit. Care Med. 2017, 45, 1709–1717. [Google Scholar] [CrossRef]
  51. Zhang, R.; Wang, Z.; Tejera, P.; Frank, A.J.; Wei, Y.; Su, L.; Zhu, Z.; Guo, Y.; Chen, F.; Bajwa, E.K.; et al. Late-onset moderate to severe acute respiratory distress syndrome is associated with shorter survival and higher mortality: A two-stage association study. Intensive Care Med. 2017, 43, 399–407. [Google Scholar] [CrossRef] [PubMed]
  52. Vincent, J.L.; Hall, J.B.; Slutsky, A.S. Ten big mistakes in intensive care medicine. Intensive Care Med. 2015, 41, 505–507. [Google Scholar] [CrossRef] [PubMed]
  53. Writing Group for the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART) Investigators; Cavalcanti, A.B.; Suzumura, E.A.; Laranjeira, L.N.; Paisani, D.M.; Damiani, L.P.; Guimarães, H.P.; Romano, E.R.; Regenga, M.M.; Taniguchi, L.N.T.; et al. Effect of lung recruitment and titrated positive end-expiratory pressure (PEEP) vs low PEEP on mortality in patients with acute respiratory distress syndrome: A randomized clinical trial. JAMA 2017, 318, 1335–1345. [Google Scholar] [PubMed]
Figure 1. Distribution of 1000 patients (testing cohort) with moderate to severe acute respiratory distress syndrome (ARDS), based on cutoff values for the PaO2/FiO2 ratio (150 mm Hg) and the positive end-expiratory pressure level (10 cm H2O) for each individual patient: (A) at the time of moderate/severe ARDS diagnosis (baseline); (B) after 24 h of standard critical care with protective mechanical ventilation. The dotted lines are placed at a PaO2/FiO2 ratio of 150 mm Hg and at PEEP 10 cm H2O. Mortality increased as lung function deteriorated (from Subset I to Subset IV) at 24 h. Subset I: PaO2/FiO2 ≥ 150 at PEEP < 10; Subset II: PaO2/FiO2 ≥ 150 at PEEP ≥ 10; Subset III: PaO2/FiO2 < 150 at PEEP < 10; Subset IV: PaO2/FiO2 < 150 at PEEP ≥ 10.
Figure 1. Distribution of 1000 patients (testing cohort) with moderate to severe acute respiratory distress syndrome (ARDS), based on cutoff values for the PaO2/FiO2 ratio (150 mm Hg) and the positive end-expiratory pressure level (10 cm H2O) for each individual patient: (A) at the time of moderate/severe ARDS diagnosis (baseline); (B) after 24 h of standard critical care with protective mechanical ventilation. The dotted lines are placed at a PaO2/FiO2 ratio of 150 mm Hg and at PEEP 10 cm H2O. Mortality increased as lung function deteriorated (from Subset I to Subset IV) at 24 h. Subset I: PaO2/FiO2 ≥ 150 at PEEP < 10; Subset II: PaO2/FiO2 ≥ 150 at PEEP ≥ 10; Subset III: PaO2/FiO2 < 150 at PEEP < 10; Subset IV: PaO2/FiO2 < 150 at PEEP ≥ 10.
Jcm 11 05724 g001
Figure 2. Probability of cumulative ICU survival to Day 30 in 1303 patients with moderate to severe acute respiratory distress syndrome (ARDS). Patients were stratified into two large categories based on cutoff values of 150 mm Hg for PaO2/FiO2 (<150 and ≥150) at 24 h of study entry.
Figure 2. Probability of cumulative ICU survival to Day 30 in 1303 patients with moderate to severe acute respiratory distress syndrome (ARDS). Patients were stratified into two large categories based on cutoff values of 150 mm Hg for PaO2/FiO2 (<150 and ≥150) at 24 h of study entry.
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Table 1. Baseline characteristics and outcome data of 1303 patients with moderate to severe acute respiratory distress syndrome (ARDS).
Table 1. Baseline characteristics and outcome data of 1303 patients with moderate to severe acute respiratory distress syndrome (ARDS).
VariablesTesting Cohort (n = 1000)Confirmatory Cohort (n = 303)
Age, years, mean (SD)57 ± 1658 ± 15
Sexn (%)n (%)
Male 680 (68.0)223 (73.6)
Female 320 (32.0)80 (26.4)
Etiologyn (%)n (%)
Pneumonia480 (48.0)110 (36.3)
Sepsis286 (28.6)78 (25.7)
Aspiration94 (9.4)47 (15.5)
Trauma74 (7.4)38 (12.5)
Acute pancreatitis32 (3.2)13 (4.3)
Multiple transfusions10 (1.0)3 (1.0)
Others24 (2.4)14 (4.6)
Degree of ARDS severityn (%)n (%)
Severe410 (41.0)107 (35.3)
Moderate590 (59.0)196 (64.7)
APACHE II score, mean ± SD20.8 ± 6.721.3 ± 7.8
SOFA score, mean ± SD9.1 ± 3.59.8 ± 3.5
PaO2/FiO2, mm Hg, mean ± SD114.3 ± 38.4120.4 ± 41.0
FiO2, mean ± SD0.79 ± 0.190.76 ± 0.20
PaO2, mm Hg, mean ± SD85.9 ± 26.386.3 ± 24.9
PaCO2, mm Hg, mean ± SD49.0 ±12.550.6 ± 13.8
pH, mean ± SD7.30 ± 0.117.29 ± 0.11
VT, mL/kg PBW, mean ± SD6.8 ± 1.06.7 ± 1.1
Respiratory rate, resp/min, mean ± SD21.3 ± 4.922.3 ± 4.6
Minute ventilation, L/min, mean ± SD9.1 ± 2.29.5 ± 2.0
PEEP, cm H2O, mean ± SD12 ± 311 ± 3
Plateau pressure, cm H2O, mean ± SD26.5 ± 4.8 §25.2 ± 4.9
Driving pressure, cm H2O, mean ± SD14.5 ± 4.8 §14.3 ± 4.8
No. extrapulmonary OF, mean ± SD1.7 ± 1.11.8 ± 1.1
Length of ICU stay, d, median (P25–P75)19 (11–31)16 (9–27)
Duration of MV from ARDS diagnosis, d, mean ± SD17.6 ± 17.014.0 ± 16.6
VFDs, d, mean ± SD7.9 ± 9.19.2 ± 9.7
Days from ICU admission to ARDS onset, median (P25–P75)1 (0–3)1 (0–2)
Days from ARDS onset to ICU discharge, median (P25–P75)16 (9–28)14 (7–23)
All-cause ICU mortality, n (%)375 (37.5)112 (37.0)
All-cause hospital mortality, n (%)415 (41.5)124 (40.9)
APACHE: Acute Physiology and Chronic Health Evaluation; d: days; FiO2: fraction of inspired oxygen concentration; ICU: intensive care unit; MV: mechanical ventilation; OF: organ failure; PBW: predicted body weight; PEEP: positive end-expiratory pressure; SD: standard deviation; SOFA: sequential organ failure assessment scale; VFDs: ventilator-free days from the diagnosis of moderate/severe ARDS until Day 28; VT: tidal volume. The APACHE II score was not reported at baseline in 19 patients. § Plateau pressure was not reported at baseline in 15 patients.
Table 2. Distribution and mortality in the intensive care unit (ICU) of each subset of patients with moderate to severe acute respiratory distress syndrome (ARDS) in the testing (n = 1000) and confirmatory (n = 303) cohorts.
Table 2. Distribution and mortality in the intensive care unit (ICU) of each subset of patients with moderate to severe acute respiratory distress syndrome (ARDS) in the testing (n = 1000) and confirmatory (n = 303) cohorts.
CohortTimingSubset I
PaO2/FiO2 ≥ 150 at PEEP < 10
Subset II
PaO2/FiO2 ≥ 150 at PEEP ≥ 10
Subset III
PaO2/FiO2 < 150 at PEEP < 10
Subset IV
PaO2/FiO2 < 150 at PEEP ≥ 10
p-Value
Testing CohortAt moderate/severe ARDS diagnosis
No. of subjects73135240552
No. events (ICU deaths)25 41 97 212
Event rate (95% CI)34.3(23.4–45.1)30.4(22.6–38.1)40.4(34.2–46.6)38.4(34.4–42.5)0.184
Risk ratio (95% CI)1 (Ref)0.9 (0.6–1.3)1.2 (0.8–1.7)1.1 (0.8–1.6)0.229
At 24 h after onset
No. of subjects2840325544
No. events (ICU deaths)5 92 10268
Event rate (95% CI)17.9 (3.7–32.0)22.8(18.7–26.9)40.0(20.8–59.2)49.3(45.0–53.6)<0.001
Risk ratio (95% CI) 1 (Ref)1.6 (0.6–2.9)2.2 (0.9–5.7)2.8 (1.2–6.1)<0.001
Confirmatory CohortAt moderate/severe ARDS diagnosis
No. of subjects324878145
No. events (ICU deaths)9183451
Event rate (95% CI)28.1(12.6–43.7)37.5(24.0–52.7)43.6(32.4–55.3)35.2(27.4–42.9)0.745
Risk ratio (95% CI) 1 (Ref)1.3 (0.7–2.6)1.6 (0.8–2.8)1.3 (0.7–2.3)0.434
At 24 h after onset
No. of subjects2813914122
No. events (ICU deaths)428 7 73
Event rate (95% CI)14.3 (1.3–27.3)20.1(13.5–26.8)50.0(23.8–76.2)59.8(51.1–68.5)<0.001
Risk ratio (95% CI)1 (Ref)1.4 (0.5–3.7)3.5 (1.2–10.0)4.2 (1.7–10.5)<0.001
ARDS: acute respiratory distress syndrome; ICU: intensive care unit; PEEP: positive end-expiratory pressure.
Table 3. Main characteristics of 1000 patients with moderate to severe acute respiratory distress syndrome (ARDS). The classification was made at 24 h after diagnosis of moderate/severe ARDS as Subsets I, II, III, and IV based on cutoff values of 150 mm Hg for PaO2/FiO2 and 10 cm H2O for PEEP *.
Table 3. Main characteristics of 1000 patients with moderate to severe acute respiratory distress syndrome (ARDS). The classification was made at 24 h after diagnosis of moderate/severe ARDS as Subsets I, II, III, and IV based on cutoff values of 150 mm Hg for PaO2/FiO2 and 10 cm H2O for PEEP *.
VariablesValues
Subset I
n = 28
Subset II
n = 403
Subset III
n = 25
Subset IV
n = 544
p-Value
APACHE II
Mean ± SD 16.4 ± 4.217.5 ± 7.220.1 ± 6.420.4 ± 7.0<0.001
Mean difference (95% CI)0 (Ref)1.1 (−1.6 to 3.8)3.7 (0.7 to 6.7)4.0 (1.4 to 6.6)<0.001
Age, mean ± SD66 ± 1356 ± 1660 ± 1957 ± 160.011
Sex, No. (%) 0.046
Men15 (53.6)263 (65.3)21 (84.0)381 (70.0)
Women13 (46.4)140 (34.7)4 (16.0)163 (30.0)
VT, mL/kg PBW
Mean ± SD6.8 ± 0.96.7 ± 0.96.7 ± 0.86.6 ± 0.90.285
Mean difference (95% CI)0 (Ref)−0.1 (−0.4 to 0.2)−0.1 (−0.6 to 0.4)−0.2 (−0.5 to 0.1)0.252
Plateau pressure, cm H2O
Mean ± SD24.4 ± 5.025.2 ± 4.626.2 ± 4.628.0 ± 4.3<0.001
Mean difference (95% CI)0 (Ref)0.8 (−1.0 to 2.6)1.8 (−0.9 to 4.5)3.6 (2.0 to 5.3)<0.001
PEEP, cm H2O
Mean ± SD7.6 ± 1.712.5 ± 2.87.4 ± 2.113.0 ± 2.8<0.001
Mean difference (95% CI)0 (Ref)4.9 (3.8 to 6.0)−0.2 (−1.2 to 0.8)5.4 (4.4 to 6.5)<0.001
Driving pressure, cm H2O
Mean ± SD16 ± 512 ± 418 ± 515 ± 4<0.001
Mean difference (95% CI)0 (Ref)−4 (−6 to −3)2 (−1 to 5)−1 (−2 to 1)<0.001
FiO2
Mean ± SD0.53 ± 0.110.55 ± 0.110.77 ± 0.160.75 ± 0.18<0.001
Mean difference (95% CI)0 (Ref)0.02(−0.1 to 0.1)0.24 (0.2 to 0.7)0.22 (0.1 to 0.3)<0.001
PaO2/FiO2, mm Hg
Mean ± SD228 ± 45200 ± 46110 ± 30107 ± 27<0.001
Mean difference (95% CI)0 (Ref)−28 (−46 to −10)−118(−139 to −97)−121(−132 to −110)<0.001
SOFA score
Mean ± SD7.3 ± 3.58.1 ± 3.38.2 ± 3.39.9 ±3.8<0.001
Mean difference (95% CI)0 (Ref)0.8 (−0.5 to 2.1)0.9 (−1.0 to 2.8)2.6 (1.2 to 4.0)<0.001
Days on MV from ARDS diagnosis
Mean ± SD12.3 ± 13.116.2 ± 14.916.3 ± 14.319.0 ± 18.50.025
Mean difference (95% CI)0 (Ref)3.9 (−1.8 to 9.6)4.0(−3.6 to 11.6)6.7(−0.3 to 13.7)0.059
VFDs, d
Mean ± SD13.7 ± 11.11.1 ± 9.56.8 ± 8.85.2 ± 7.8<0.001
Mean difference (95% CI)0 (Ref)−2.6 (−6.3 to 1.1)−6.9(−12.4 to −1.4)−8.5(−11.5 to −5.5)<0.001
ICU deaths
No. events59210268
Event rate (95% CI)17.9 (3.7–32.0)22.8 (18.7–26.9)40.0 (20.8–59.2)49.3 (45.1–53.5)<0.001
Risk ratio (95% CI)1 (Ref)1.3 (0.6–2.9)2.2 (0.9–5.7)2.8 (1.2–6.1)<0.001
APACHE: Acute Physiology and Chronic Health Evaluation; ARDS: acute respiratory distress syndrome; ICU: intensive care unit; MV: mechanical ventilation; PBW: predicted body weight; PEEP: positive end-expiratory pressure; SD: standard deviation; SOFA: sequential organ failure assessment; VFDs: ventilator-free days from diagnosis of moderate/severe ARDS until Day 28; VT: tidal volume. The APACHE II score was not reported at 24 h in 33 patients (10 patients in Subset II, 2 patients in Subset III, and 21 in Subset IV). * Subset I, PaO2/FiO2 ≥ 150 at PEEP < 10; Subset II, PaO2/FiO2 ≥ 150 at PEEP ≥ 10; Subset III, PaO2/FiO2 < 150 at PEEP < 10; Subset IV, PaO2/FiO2 < 150 at PEEP ≥ 10.
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Villar, J.; Fernández, C.; González-Martín, J.M.; Ferrando, C.; Añón, J.M.; del Saz-Ortíz, A.M.; Díaz-Lamas, A.; Bueno-González, A.; Fernández, L.; Domínguez-Berrot, A.M.; et al. Respiratory Subsets in Patients with Moderate to Severe Acute Respiratory Distress Syndrome for Early Prediction of Death. J. Clin. Med. 2022, 11, 5724. https://doi.org/10.3390/jcm11195724

AMA Style

Villar J, Fernández C, González-Martín JM, Ferrando C, Añón JM, del Saz-Ortíz AM, Díaz-Lamas A, Bueno-González A, Fernández L, Domínguez-Berrot AM, et al. Respiratory Subsets in Patients with Moderate to Severe Acute Respiratory Distress Syndrome for Early Prediction of Death. Journal of Clinical Medicine. 2022; 11(19):5724. https://doi.org/10.3390/jcm11195724

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Villar, Jesús, Cristina Fernández, Jesús M. González-Martín, Carlos Ferrando, José M. Añón, Ana M. del Saz-Ortíz, Ana Díaz-Lamas, Ana Bueno-González, Lorena Fernández, Ana M. Domínguez-Berrot, and et al. 2022. "Respiratory Subsets in Patients with Moderate to Severe Acute Respiratory Distress Syndrome for Early Prediction of Death" Journal of Clinical Medicine 11, no. 19: 5724. https://doi.org/10.3390/jcm11195724

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