American Journal of Respiratory and Critical Care Medicine

Rationale: Many patients with severe acute respiratory distress syndrome (ARDS) caused by influenza A(H1N1) infection receive extracorporeal membrane oxygenation (ECMO) as a rescue therapy.

Objectives: To analyze factors associated with death in ECMO-treated patients and the influence of ECMO on intensive care unit (ICU) mortality.

Methods: Data from patients admitted for H1N1-associated ARDS to French ICUs were prospectively collected from 2009 to 2011 through the national REVA registry. We analyzed factors associated with in-ICU death in ECMO recipients, and the potential benefit of ECMO using a propensity score–matched (1:1) cohort analysis.

Measurements and Main Results: A total of 123 patients received ECMO. By multivariate analysis, increasing values of age, lactate, and plateau pressure under ECMO were associated with death. Of 103 patients receiving ECMO during the first week of mechanical ventilation, 52 could be matched to non-ECMO patients of comparable severity, using a one-to-one matching and using control subjects only once. Mortality did not differ between the two matched cohorts (odds ratio, 1.48; 95% confidence interval, 0.68–3.23; P = 0.32). Interestingly, the 51 ECMO patients who could not be matched were younger, had lower Pao2/Fio2 ratio, had higher plateau pressure, but also had a lower ICU mortality rate than the 52 matched ECMO patients (22% vs. 50%; P < 0.01).

Conclusions: Under ECMO, an ultraprotective ventilation strategy minimizing plateau pressure may be required to improve outcome. When patients with severe influenza A(H1N1)–related ARDS treated with ECMO were compared with conventionally treated patients, no difference in mortality rates existed. The unmatched, severely hypoxemic, and younger ECMO-treated patients had, however, a lower mortality.

Scientific Knowledge on the Subject

Extracorporeal membrane oxygenation (ECMO) benefit for H1N1 severe acute respiratory distress syndrome is still debated because different countries have heterogeneous results.

What This Study Adds to the Field

We identified new factors associated with survival in ECMO patients. In a propensity score–matched analysis, ECMO-treated patients and conventionally treated patients have similar mortality rates.

Extracorporeal membrane oxygenation (ECMO) has been proposed early after its first description as a possible management of the most hypoxemic cases of acute respiratory distress syndrome (ARDS), but two randomized controlled trials (RCT) could not confirm the superiority of the technique over more conventional management (1, 2), and its use was long restricted to a few selected centers. Renewed interest in this therapy has been stimulated by technical improvements and by the positive results of a recent RCT (3). This technique was thus more widely used during the recent influenza A(H1N1) pandemic (pdm) as a rescue therapy for the most severe ARDS cases who could hardly be managed with conventional therapy (4, 5).

Analysis of patients with influenza A(H1N1)pdm pneumonia provides a unique opportunity to describe the results of ECMO in patients suffering from a relatively homogeneous form of ARDS. In a recent study from the United Kingdom, patients referred to ECMO centers had lower mortality than propensity score (PS)–matched nonreferred patients (6). Soon after the first cases occurred in France, the REVA/French Society of Intensive Care (SRLF) H1N1 registry was set up to prospectively collect the characteristics of patients infected with influenza A(H1N1)pdm hospitalized in participating intensive care units (ICUs), and included 123 patients treated with ECMO between July 2009 and May 2011 (7, 8). In this study, we describe the baseline characteristics, ICU management, and variables associated with ICU mortality in the largest cohort to date of patients with severe influenza A(H1N1)pdm–induced ARDS receiving ECMO; we also estimated the potential benefit of ECMO on survival of patients after PS matching of ECMO recipients with other patients from the same registry having severe ARDS managed without this technique. Some of the results of these studies have been previously reported in the form of abstracts in May 2012 during the American Thoracic Society International Conference (9, 10).

Database and Patient Selection

From July 2009 to March 2010, the baseline characteristics, ICU management, and outcome of all patients infected with influenza A(H1N1)pdm admitted to 114 participating French ICUs were prospectively collected in a web-based registry (REVA-SRLF H1N1 registry). During the subsequent wave of the epidemic (September 2010 to March 2011), only patients treated with ECMO were recorded in the database. The database thus contained patients infected with influenza A(H1N1)pdm with ARDS treated or not treated with ECMO.

All adult patients hospitalized with influenza A(H1N1)pdm–related ARDS and treated with ECMO were included in this ECMO cohort (Figure 1). Patients were followed-up until ICU discharge or death, or up to June 1, 2011.

Patients treated with ECMO in the first week of ARDS were matched to patients from the whole database having influenza A/H1N1–related severe ARDS and treated without ECMO using a PS exposed–nonexposed one-to-one matching approach. Severe ARDS was defined by the classical definition of ARDS (11) plus a modified Lung Injury Score (12) greater than 3 or any of the following three criteria: (1) an arterial pH less than 7.21, (2) a ratio of arterial partial pressure of oxygen to the fraction of inspired oxygen (Pao2/Fio2) less than 100 mm Hg, or (3) an arterial oxygen saturation (Sao2) less than 90%.

A confirmed case of influenza A(H1N1)pdm–associated ARDS was considered when a polymerase chain reaction was positive.

Data Collection

Baseline characteristics were collected on admission; ICU evolution and management were recorded daily (variables are detailed in the online supplement).

Statistical Analysis

Descriptive statistics included frequency (percentages) for categorical variables, mean and standard deviation, or median and interquartile ranges for continuous variables. Comparisons of proportions were made using chi-square test, Fisher exact test, or McNemar test for matched patients; continuous variables were compared using Student t test or Wilcoxon rank sum test and the corresponding paired tests for matched patients.

To determine variables associated with ICU mortality in the whole cohort of ECMO-treated patients, covariates assumed to be associated with death and those associated with ICU mortality at P less than 0.10 in univariate analyses were entered in a multivariate stepwise backward logistic regression model.

Propensity score.

Covariates presumed to be associated with the decision of ECMO treatment or with ICU death were included in a multivariable logistic regression analysis with ECMO treatment in the first week as the dependent variable to determine the PS of ECMO treatment for each patient (i.e., the probability of receiving ECMO treatment conditionally on the observed covariates). The independent covariates selected were age; sex; pregnancy status; body mass index (BMI); risk factors for influenza-related complications as defined by the Centers for Disease Control and Prevention (13) (including immunosuppression, chronic lung disease, diabetes, chronic renal failure, chronic heart failure, obesity, and pregnancy); SAPS3 score (14, 15), SOFA score (16), bacterial coinfection, and shock at the time of admission; and the use of corticosteroids or of a rescue therapy, worst arterial pH, Pao2/Fio2 ratio, and Lung Injury Score (12) before ECMO implantation or during the first week for non-ECMO patients with ARDS. Missing data were imputed to complete the PS. Therefore, we selected the model leading to a reduction of the imbalances (17) between the two matched cohorts for a maximal number of variables (plotted standardized differences before and after matching) (see Figure E1 in the online supplement).

Case-matching procedure.

For the matched cohort analysis, patients treated with ECMO were matched with patients with severe ARDS managed without ECMO according to the PS, using a 1:1 matching procedure without replacement (a matched control patient cannot be reused for matching another case) and a caliper width of 0.2 (i.e., 0.2 × standard deviation of the logit of the PS) resulting in a relatively narrow difference between matched variables, as recommended (18, 19). This PS matching method was rather conservative and these points as well as the results obtained with less stringent methods are explained in more details in the online supplement.

Sensitivity analyses.

Multivariate analyses of variables associated with ICU death in the ECMO cohort were performed with and without data imputation. Several models with covariates usually related with mortality were performed to limit confounding. To compare our results with those of the analysis conducted on the UK cohort (6), the PS-matched analysis was repeated allowing replacement for matching ECMO with non-ECMO patients (i.e., reusing control patients more than once when no other control subject could be found). We then performed the three analyses done by the UK group on our dataset (manual matching with replacement, PS matching analysis with replacement, GenMatch matching with replacement [2022]) (see online supplement).

All statistical tests were two-sided and were not adjusted for multiple comparisons. P values of 0.05 or less were considered statistically significant. Statistical analyses were performed with R 2.10.1 (http://www.R-project.org) software packages.

Quality Control Assessment

Data collected were directly downloaded as electronic files from the REVA web registry. The database was completed when needed after direct contact with the ICU physicians. Duplicate notifications were systematically checked, and patients transferred from one ICU to another were counted as a single admission. We followed the Strengthening the Reporting of Observational Studies in Epidemiology statement guidelines for observational cohort studies (23).

Ethical and Legal Aspects

The national committee for protection of patient’s rights and electronic data recording approved data collection in the national H1N1 registry. The SRLF Ethics Committee gave approval for the registry and this analysis. The authors had full access to the data and take responsibility for their integrity.

Patient Characteristics

Between July 29, 2009 and March 26, 2011, 127 patients infected by influenza A(H1N1)pdm and treated with ECMO were recorded into the REVA/SRLF H1N1 registry (Figure 1, Table 1). The inclusiveness for ECMO patients treated in French ICUs was cross-checked with mandatory notifications to the National Institute for Public Health Surveillance (InVS, St Maurice, France) and only two patients were missing from the REVA registry. Four of these 127 patients were excluded for not fulfilling the H1N1pdm-related ARDS criteria (Figure 1). Despite a lack of virologic confirmation, 16 patients considered as having a high probability of influenza A(H1N1)pdm–induced ARDS because of a typical clinical presentation and no other cause for ARDS were kept in the analysis (2 in the ECMO group, 14 in the ARDS group).

TABLE 1. BASELINE CHARACTERISTICS, MANAGEMENT, AND OUTCOME OF 123 PATIENTS TREATED WITH ECMO FOR INFLUENZA A/H1N1PDM–RELATED ACUTE RESPIRATORY DISTRESS SYNDROME

Mean (SD), Median (IQR), or N (%)
Baseline characteristics
 Age, yr42 (13)
 Male sex61 (50%)
 MacCabe 1*108 (88%)
 Risk factor for influenza complication93 (76%)
 Pregnancy or postpartum18 (15%)
 BMI, kg/m230.5 (8.5)
On admission
 SAPS358 (14)
 SOFA9.5 (4)
 Bacterial coinfection28 (23%)
Before ECMO
 Shock60 (49%)
 Corticosteroid therapy42 (34%)
 Rescue therapy91 (74%)
  Inhaled nitric oxide83 (72%)
  Prone positioning51 (45%)
  Almitrine7 (7%)
  HFOV3 (2%)
Time from MV to ECMO, d2 (1–5)
V-V ECMO107 (87%)
Pre-ECMOFirst Day on ECMO
Tidal volume, ml/kg PBW6.7 (1.6)3.9 (1.4)
Respiratory rate, min−127 (6)19 (8)
PEEP, cm H2O13 (4)13 (4)
Plateau pressure, cm H2O32 (5)26 (4)
Pao2/Fio2 ratio, mm Hg63 (21)109 (74)
Sao2, %84 (11)95 (5)
Arterial pH7.26 (0.12)7.39 (0.12)
Paco2, mm Hg57 (18)38 (9)
Arterial lactate, mM2.9 (3)4.2 (5.6)
Driving pressure, cm H2O19 (6)14 (5)
LIS3.4 (0.6)Not collected
Complications and outcome
 Nosocomial pneumonia68 (62%)
 Length of ECMO, d11 (8–22)
 Length of MV, d28 (15–44)
 Length of ICU stay, d33 (17–59)
 Mortality44 (36%)

Definition of abbreviations: BMI = body mass index; ECMO = extracorporeal membrane oxygenation; HFOV = high-frequency oscillation ventilation; ICU = intensive care unit; IQR = interquartile range; LIS = modified lung injury score; MV = mechanical ventilation; PEEP = positive end-expiratory pressure; PBW = predicted body weight; V-V = venovenous.

*MacCabe 1: no or nonfatal underlying disease.

Driving pressure: (plateau pressure − PEEP).

The mean age of the 123 remaining patients was 42 years and 50% were men; 76% had one or more risk factors for influenza-related complications (13), mostly obesity with a BMI higher than 30 kg/m2 (40%), immunosuppression (19%), and pregnancy or postpartum status (15%). On admission, 28 (23%) patients had concomitant bacterial infection, and 49% had septic shock.

ICU Management and Ventilation Settings

All ECMO patients received antiviral therapy. ECMO was initiated a median of 2 days after mechanical ventilation, and 103 (84%) patients had been receiving mechanical ventilation for less than 8 days before ECMO (Table 1); only 16 (13%) received venoarterial ECMO and 107 received venovenous ECMO. Before initiation of ECMO, the mean modified Lung Injury Score was 3.4. Rescue therapies were used in 74% of patients, with 72% of patients receiving inhaled nitric oxide, and 45% prone positioning. A total of 42 patients (34%) had received steroids before ECMO initiation.

Before initiating ECMO, ventilation parameters included a tidal volume of 6.7 ml/kg predicted body weight, a high respiratory rate, and high positive end-expiratory pressure (PEEP) resulting in a mean plateau pressure (Pplat) of 32 cm H2O. Patients remained severely hypoxemic (Pao2/Fio2 ratio, 63 mm Hg; Sao2, 84%), hypercapnic (Paco2, 57 mm Hg), and acidotic (pH = 7.26), with a mean arterial lactate of 2.9 mmol/L.

After starting ECMO, physicians reduced tidal volume by 2.8 ml/kg predicted body weight and respiratory rate by 8 breaths/min, but did not change the PEEP level. Both Pplat and driving pressure (difference between Pplat and PEEP) decreased by 6 cm H2O and arterial blood gas improved (increase in Pao2/Fio2 by 42 mm Hg, decrease in Paco2 by 18 mm Hg).

Complications and Outcome

The median duration of ECMO, intubation, and ICU stay were 11, 28, and 33 days, respectively. Forty-four patients (36%; 95% confidence interval [CI], 27–44%) died in ICU: 22 of multiorgan failure, 8 of refractory hypoxemia, 6 of refractory shock (two hemorrhagic, one septic, and three unspecified shock), 5 of intracranial hemorrhage, and 3 patients had unspecified cause of death. Overall, 65 (53%) patients had one or more ECMO-related complication (see Table E2).

Except for a higher rate of early administration of steroids in nonsurvivors (P = 0.03), there was no difference between survivors and nonsurvivors in baseline characteristics and arterial blood gas results before and after ECMO in the two groups (Table 2). Nevertheless, nonsurvivors had higher plateau (P < 0.01) and driving (P = 0.03) pressures and arterial lactate levels (P = 0.004) and a smaller reduction in Pplat (P < 0.01) on the first day under ECMO (Figure 2). After multivariate analysis, age (odds ratio [OR], 1.09; 95% CI, 1.04–1.15; P < 0.01), higher Pplat (OR, 1.33; 95% CI, 1.14–1.59; P < 0.01), and lactate under ECMO (OR, 1.42; 95% CI, 1.18–1.82; P < 0.01) were the three variables that remained significantly associated with ICU death. Driving pressure was not retained in the model, but was highly correlated with Pplat (see Figure E4).

TABLE 2. BASELINE CHARACTERISTICS, ICU MANAGEMENT, AND OUTCOME OF 123 PATIENTS TREATED WITH ECMO, ACCORDING TO SURVIVAL

Mean (SD), Median (IQR), or N (%)
Survivors (n = 79)Nonsurvivors (n = 44)P Value
Baseline characteristics
 Age, yr40 (13)45 (13)0.06
 Male sex37 (47%)24 (55%)0.53
 MacCabe 1*71 (90%)37 (84%)0.51
 Risk factor for influenza complication62 (78%)31 (70%)0.44
 Pregnancy or postpartum14 (18%)4 (9%)0.30
 BMI, kg/m231.5 (8.9)28.6 (7.9)0.09
On admission
 SAPS3 score57 (13)61 (17)0.22
 SOFA score9.5 (3.9)9.4 (4.6)0.95
 Bacterial coinfection17 (22%)11 (26%)0.80
Before ECMO
 Shock35 (44%)25 (57%)0.25
 Steroids21 (27%)21 (48%)0.03
 Rescue therapy57 (72%)34 (77%)0.68
 Time from MV to ECMO, d2 (1–5)2 (1–6)0.51
 V-V ECMO71 (90%)36 (82%)0.32
Pre-ECMO
 Tidal volume, ml/kg PBW6.4 (5.8–7.4)6.7 (5.8–7.2)0.96
 Respiratory rate, min−127 (5)28 (7)0.33
 PEEP, cm H2O13 (4)12 (4)0.13
 Plateau pressure, cm H2O32 (5)32 (5)0.86
 Pao2/Fio2 ratio62 (17)65 (27)0.58
 Sao2, %84 (11)84 (11)0.80
 Arterial pH7.27 (0.12)7.24 (0.14)0.32
 Paco2, mm Hg60 (14)58 (20)0.75
 Arterial lactate, mmol/L2.4 (2)4.1 (4.4)0.06
 Driving pressure19 (7)20 (6)0.33
 LIS3.5 (0.5)3.3 (0.5)0.27
First day on ECMO
 Tidal volume, ml/kg PBW3.6 (2.7–4.5)4.1 (3.5–5.4)0.07
 Respiratory rate, min−119 (8)20 (8)0.51
 PEEP, cm H2O13 (4)12 (4)0.93
 Plateau pressure, cm H2O25 (3)29 (5)<0.01
 Pao2/Fio2 ratio105 (66)116 (88)0.53
 Sao2, %95 (4)94 (6)0.36
 Arterial pH7.40 (0.09)7.37 (0.16)0.20
 Paco2, mm Hg37 (9)39 (9)0.26
 Arterial lactate, mmol/L2.7 (2.1)7 (8.5)<0.01
 Driving pressure13 (4)16 (7)0.03
 Delta plateau pressure−7 (6)−3 (5)<0.01
Complications and outcome
 Nosocomial pneumonia45 (64%)24 (58%)0.69
 Length of ECMO, d12 (8–23)10 (4–21)0.1
 Length of MV, d32 (23–53)17.5 (9.5–32)<0.01
 Length of ICU stay, d44 (29–67)16.5 (9.5–34)<0.01

Definition of abbreviations: BMI = body mass index; ECMO = extracorporeal membrane oxygenation; HFOV = high-frequency oscillation ventilation; ICU = intensive care unit; IQR = interquartile range; LIS = modified lung injury score; MV = mechanical ventilation; PBW = predicted body weight; PEEP = positive end-expiratory pressure; V-V = venovenous.

*MacCabe 1: no or nonfatal underlying disease.

Driving pressure: (plateau pressure − PEEP).

Matched Analysis

The 103 patients who received ECMO within the first week of mechanical ventilation were compared with 157 patients who had severe ARDS criteria but did not receive ECMO (non-ECMO group). These two groups differed in many respects (Table 3 “before matching”). Patients receiving ECMO were younger, included a higher proportion of pregnant women and obese patients, had less comorbidities and immune suppression and less bacterial infection on admission, and a lower proportion received early steroid treatment. They had more organ failures and a more severe pulmonary failure (with a higher Lung Injury Score, a lower Pao2/Fio2 ratio, and higher Pplat). In-ICU mortality rate was similar between the ECMO and non-ECMO groups (36% vs. 34%; P = 0.90). Matching (without replacement) on the PS allowed selecting only 52 unique pairs of patients with similar medical history and initial severity, minimizing all baseline differences (Table 3,“after matching”). Using this well-matched subgroup of patients, we found no significant difference in ICU mortality (40% in the conventional treatment group vs. 50% in the ECMO group; OR for death of ECMO patients, 1.48; 95% CI, 0.68–3.23; P = 0.32).

TABLE 3. BASELINE CHARACTERISTICS OF ECMO AND NON-ECMO ARDS PATIENTS BEFORE AND AFTER MATCHING ON THE PROPENSITY SCORE FOR RECEIVING ECMO*

Before Matching
After Matching
Non-ECMO Patients (n = 157)ECMO Patients (n = 103)P ValueNon-ECMO Patients (n = 52)ECMO Patients (n = 52)P Value
Baseline characteristics
 Age, yr48 (15)42 (13)<0.0145 (15)45 (13)0.86
 Male sex83 (53%)49 (48%)0.4129 (56%)30 (58%)0.83
 MacCabe 1112 (71%)92 (89%)<0.0139 (75%)45 (87%)0.24
 Risk factor for influenza complication119 (76%)81 (79%)0.7039 (75%)37 (71%)0.80
 Pregnancy or postpartum3 (2%)16 (16%)<0.012 (4%)3 (6%)1.00
 BMI, kg/m229 (9)32 (9)0.0231 (11)30 (7)0.44
 Immunosuppression49 (31%)18 (17%)0.0216 (31%)12 (23%)0.48
On admission
 SAPS3 score58 (17)60 (14)0.3158 (18)60 (14)0.29
 SOFA score8.6 (4)9.8 (4.2)0.059.5 (4)9.6 (4.6)0.98
 Bacterial coinfection55 (35%)22 (21%)0.0210 (19%)13 (25%)0.81
 Shock113 (72%)77 (75%)0.7235 (67%)40 (77%)0.54
Before Day 7 or before ECMO
 Steroids74 (47%)32 (31%)0.0123 (44%)24 (46%)1.00
 Rescue therapy67 (42%)84 (82%)<0.0136 (69%)40 (77%)0.54
 TV, ml/kg PBW7 (1.2)6.7 (1.6)0.186.8 (1.1)6.6 (1.4)0.40
 Respiratory rate, min−128 (5)27 (6)0.1328 (5)28 (6)0.80
 PEEP, cm H2O13 (3)13 (4)0.6513 (3)13 (4)0.49
 Plateau pressure, cm H2O29 (4)32 (6)<0.0131 (5)31 (5)0.24
 Pao2/Fio2 ratio83 (27)63 (22)<0.0168 (20)70 (26)0.76
 Sao2, %90 (7)83 (11)<0.0188 (8)87 (9)0.99
 Arterial pH7.27 (0.12)7.26 (0.12)0.397.25 (0.16)7.24 (0.13)0.75
 Paco2, mm Hg55 (14)54 (16)0.855 (16)56 (15)0.97
 Lactate, mM3.7 (5.4)3.1 (3.1)0.364.6 (6)3.4 (2.9)0.63
 LIS3.2 (0.6)3.6 (0.4)<0.013.3 (0.7)3.3 (0.7)1.00
Complications and outcome
 Length of MV, d17 (9–25)25 (14–40)<0.0113.5 (7–21)22 (11.7–35)<0.01
 Length of ICU stay, d21 (12–32)32 (15.25–56)<0.0119.5 (9–26)27 (12–52)0.04
 Mortality54 (34%)37 (36%)0.9021 (40%)26 (50%)0.44

Definition of abbreviations: ARDS = acute respiratory distress syndrome; BMI = body mass index; ECMO = extracorporeal membrane oxygenation; HFOV = high-frequency oscillation ventilation; ICU = intensive care unit; LIS = modified lung injury score; MV = mechanical ventilation; PBW = predicted body weight; PEEP = positive end-expiratory pressure; TV = tidal volume; V-V = venovenous.

Data presented as n (%), mean (SD), or median (interquartile range).

*Only 52 of the 103 ECMO recipients could be matched to non-ECMO patients of corresponding severity based on the propensity score.

MacCabe 1: no or nonfatal underlying disease.

Of note, the 51 ECMO patients excluded from this analysis because of the absence of adequately matched non-ECMO patients (Table 4) were younger (P < 0.01), had a higher BMI (P = 0.03), included a higher proportion of pregnant women (P = 0.01), and less frequently received early steroids (P < 0.01) than those retained in the matched cohort; they also had lower Pao2/Fio2 (P < 0.01) and Sao2 (P < 0.01), and a higher Pplat before ECMO (P < 0.01), but had a twice lower ICU mortality (50% vs. 22%; P < 0.01).

TABLE 4. BASELINE CHARACTERISTICS, ICU MANAGEMENT, AND OUTCOME OF ECMO PATIENTS SELECTED AND EXCLUDED FROM THE MATCHED ANALYSES

Selected for Matching (52)Not Selected for Matching (51)P Value
Baseline characteristics
 Age, yr45 (13)38 (13)<0.01
 Male sex30 (58%)19 (37%)0.06
 MacCabe 1*45 (87%)47 (92%)0.55
 Risk factor for flu complication37 (71%)44 (86%)0.10
 Pregnancy or postpartum3 (6%)13 (25%)0.01
 BMI, kg/m230 (8)33 (10)0.03
 Obesity17 (33%)29 (57%)0.04
 Immunosuppression12 (23%)6 (12%)0.21
On admission
 SAPS3 score61 (14)58 (14)0.28
 SOFA score9.6 (4.8)10 (3.7)0.70
 Bacterial coinfection13 (25%)9 (18%)0.50
 Shock40 (77%)37 (73%)0.78
Before ECMO
 Steroids24 (46%)8 (16%)<0.01
 Rescue therapy40 (77%)44 (86%)0.33
 Time from MV to ECMO2 (1–4)1 (0–3.5)0.47
 V-V ECMO44 (85%)44 (86%)0.97
Pre-ECMO
 Tidal volume, ml/kg PBW6.6 (1.4)6.8 (1.8)0.52
 Respiratory rate, min−128 (6)26 (5)0.22
 PEEP, cm H2O13 (4)13 (3)0.86
 Plateau pressure, cm H2O31 (5)33 (6)0.03
 Pao2/Fio2 ratio70 (26)54 (13)<0.01
 Sao2, %87 (9)80 (11)<0.01
 pH7.24 (0.13)7.26 (0.13)0.40
 Paco2, mm Hg56 (15)52 (17)0.22
 Lactate, mM3.4 (2.9)2.9 (3.3)0.42
 Driving pressure21 (7)18 (6)0.03
 LIS3.4 (0.6)3.6 (0.4)0.19
First day under ECMO
 Tidal volume, ml/kg PBW4 (1.5)3.7 (1.3)0.17
 Respiratory rate, min−119 (8)20 (7)0.84
 PEEP, cm H2O13 (5)12 (4)0.22
 Plateau pressure, cm H2O26 (4)27 (5)0.52
 Pao2/Fio2 ratio, mm Hg108 (54)109 (76)0.97
 Sao2, %95 (5)95 (4)0.95
 Arterial pH7.36 (0.13)7.38 (0.10)0.46
 Paco2, mm Hg38 (10)38 (8)0.91
 Lactate, mmol/L5 (5.1)4.27 (6.8)0.54
 Driving pressure, cm H2O13.5 (5)14 (5)0.46
Complications and outcome
 Nosocomial pneumonia, n32 (61%)22 (43%)0.09
 Length of ECMO, d9 (7–18)13 (9–23)0.31
 Length of MV, d22 (12–35)30 (15–42)0.11
 Length of ICU stay, d27 (11–52)34.5 (21–58)0.72
 In-ICU mortality, n26 (50%)11 (22%)<0.01

Definition of abbreviations: BMI = body mass index; ECMO = extracorporeal membrane oxygenation; HFOV = high-frequency oscillation ventilation; ICU = intensive care unit; LIS = modified lung injury score; MV = mechanical ventilation; PBW = predicted body weight; PEEP = positive end-expiratory pressure; V-V = venovenous.

Data presented as n (%), mean (SD), or median (interquartile range).

*MacCabe 1: no or nonfatal underlying disease.

Driving pressure: (plateau pressure − PEEP).

To explain the differences between our results and those of a recent similar analysis (6), we repeated the matching using different techniques (see online supplement). In a complementary PS analysis using a matching procedure with replacement similar to that used in the UK study (6), 102 of the 103 ECMO-treated patients could be retained in the analysis; because of repeated allocations, however, only 58 unique non–ECMO-treated patients were then used for matching (see Table E3 and Figure E4). In this analysis, treatment with ECMO seemed to be associated with a significantly lower risk of death (OR, 0.45; 95% CI, 0.25–0.78; P < 0.01).

To our knowledge, this is the largest cohort of influenza A(H1N1)pdm–related ARDS treated with ECMO. We found several new and relevant findings: (1) in addition to age, higher lactate levels on the first day of ECMO treatment was associated with increased mortality, whereas a reduced Pplat the first day under ECMO was significantly associated with survival; (2) in a one-to-one matched paired propensity adjusted analysis, overall survival did not differ between ECMO-treated patients and those managed conventionally; and (3) the ECMO-treated patients who could not be matched to non–ECMO-treated patients were younger, had more severe respiratory failure, and had a markedly lower mortality.

Similarly to previous cohorts of patients infected with influenza A(H1N1)pdm treated with ECMO (46), patients were young, obese, previously healthy, and had a rapidly extensive viral pneumonia with extremely severe initial pulmonary injury. Nevertheless, some differences in management deserve to be highlighted: more French patients received inhaled nitric oxide or prone positioning (72% and 45%, respectively; 43% received both) before ECMO than Australian (4) (32% and 20%), UK (6) (19% and 34%), or Italian (5) patients (15% and 28%), suggesting that French intensivists considered ECMO as a last-line rescue therapy. Whereas other countries relied on 4 (UK) or 15 (Australia and New Zealand) referral centers, more than 30 different centers provided ECMO therapy in France, which was possibly associated with a higher heterogeneity in patients’ management; however, overall mortality did not differ between the most experienced French centers and those that cared for fewer ECMO patients (data not shown).

Pre-ECMO ventilator settings in our cohort (Table 1) show that physicians generally followed recommendations for maximal protective ventilation and ventilator settings algorithms issued by French scientific societies (24) soon after the pandemic started (including a low tidal volume, a high respiratory rate to maintain pH between 7.30 and 7.45, and high PEEP levels to allow for a maximal Pplat of 28–30 cm H2O). Ventilation settings under ECMO were also consistent with recommendations (Table 1): tidal volume and respiratory rate were lowered, resulting in a lower Pplat while PEEP level was maintained.

More than half ECMO patients experienced at least one device-related complication (see Table E1). The rate of intracranial bleeding (4%) in our patients is higher than the 1% rate recorded in the Italian series (5), but lower than the 11% rate reported in the Australian or UK cohorts (4, 6). Comparison of these bleeding rates is difficult because the anticoagulation strategy and monitoring were not reported in any of these cohorts. Experts now recommend targeting a relatively low level of anticoagulation, but no guideline is available to date (25).

We identified older age, higher lactate, and Pplat under ECMO as all associated with increased odds of ICU death in ECMO recipients. Age was consistently found predictive of a poor outcome in several studies (26, 27), leading most teams to restrict ECMO treatment to the youngest patients. In one study of 42 patients receiving ECMO for cardiac failure, lactate measured after 48 hours of ECMO therapy was associated with mortality (28); persistently severe hypoxia or circulatory failure on the first ECMO day may account for this finding in our patients. Importantly, Pplat under ECMO was the only ventilator parameter associated with ICU death. Optimal ECMO settings with large cannulas and high circuit blood flows permitting full respiratory support might have allowed physicians to apply a maximal protective ventilation hence lowering Pplat to below 25 cm H2O, which in itself was beneficial on outcome of patients; indeed, it has been suggested that reducing Pplat below the accepted safe range of 28–30 cm H2O might enhance lung protection and reduce ARDS-associated mortality (29, 30).

Our major objective was to estimate the effect of ECMO treatment on patients’ outcome. Although a RCT to study the potential benefit of ECMO for severe ARDS caused by influenza A(H1N1)pdm did not seem feasible for logistical and ethical reasons, a PS-matched analysis appeared to be a suitable alternative. This well-validated method allows minimizing the biases and replicates a RCT by creating two groups of patients (treated or not) as similar as possible on measured confounders (19, 31). The matching procedure used in this study (matching without replacement using a caliper of width of 0.2 of the standard deviation of the logit of the PS) is considered to minimize differences between treatment groups and thus selection bias in estimating treatment effect (18, 19). Interestingly, this procedure allowed matching only 52 of our ECMO patients (50% of those receiving ECMO during the first week) to a unique similarly severe non-ECMO patient. Patients not selected for the matched analysis were younger and had more severe respiratory failure (Table 4). Despite their extremely severe respiratory failure, this subgroup had a twice lower ICU mortality than the ECMO subgroup selected for the matched analysis (22% vs. 50%; P < 0.01). Thus, ECMO patients not selected by our matching procedure seem to define a subgroup that may have actually benefited most from ECMO, although this could not be formally tested.

Our finding of a lack of survival difference in the matched treated and untreated groups differs from the results of the UK study based on a similar approach (6). First, this points out that PS analysis can be done in several ways (32) (see online supplement), and that clearly reporting the whole process of the PS approach in published studies should be done. There are several important methodologic differences between the two analyses: we included more covariates in the PS and used more stringent matching parameters (narrower caliper and matching without replacement). To better understand the differences between these two studies, we repeated the analysis with replacement (i.e., reusing the same controls several times), and this procedure provided very similar results to the UK study, with an odds ratio of survival under ECMO of 0.45 (95% CI, 0.25–0.78; P < 0.01) (see online supplement). By using more ECMO-treated patients, and the same severe non-ECMO patients, this latter procedure may artificially favor the ECMO group.

In this study describing the largest cohort of ECMO-treated patients for influenza A(H1N1)pdm–related ARDS, we included almost all French patients treated with this procedure. Some of these patients have already been included in previous publications but none of these describe the whole ECMO population treated in France (7, 8, 3336). Data were collected prospectively and pre-ECMO characteristics were consistent with previous published data (4, 5). Although every effort was made to minimize missing data by contacting all ICUs, some remained missing (see Table E1), but multiple imputation of missing data was used to determine the propensity PS and for the sensitivity analysis. The results of our multivariate and the matched analyses seemed robust, however, because all the different models performed with different sets of covariates concluded the same results. Our analysis was limited to in-ICU mortality because hospital mortality was not available for every patient after ICU discharge, but the two main published cohorts on influenza A(H1N1)pdm ECMO patients from Australia and Italy have shown identical mortality at ICU and hospital discharge (4, 5).

Data from non-ECMO patients were not collected in the 2010–2011 winter to minimize physicians’ workload. Nevertheless, ICU patients with severe influenza had similar characteristics during the 2 consecutive years of the study (37).

The PS-matched analysis decreased our sample size from 103 to 52 ECMO patients comparable with 52 control patients. As other countries reported their experience on ECMO for H1N1-related ARDS (46), an international study linking available datasets could increase the capability to better define the potential benefit of this technique in a larger population.

Our results may not be generalizable to all patients with ARDS from various causes. Indeed, the effectiveness and safety of venovenous ECMO in patients with ARDS remains an open question (38). Whether these patients should be treated by such an invasive technique still remains debatable and more information will be brought in the near future by ongoing studies (EOLIA; ClinicalTrial.gov Identifier NCT 01470703).

In summary, our results indicate that an ultraprotective ventilation strategy with reduction of Pplat to around 25 cm H2O from the first day under ECMO may be required to improve survival. We could not demonstrate a benefit of ECMO on ICU survival when compared with conventional management in matched patients of similar severity; however, only 50% of ECMO patients were successfully matched. A specific subgroup of young patients with severe respiratory failure receiving ECMO remained unmatched and had a more favorable outcome. Whether such a better outcome may be related to ECMO is still an open issue because it may also be caused solely by patient selection.

The authors are grateful to Dr Isabelle Bonmarin (Institut de Veille Sanitaire, St Maurice, France) for her help in checking the exhaustiveness of ECMO cases. They thank all the medical and nursing staff of participating centers.

Collaborators (REVA Research Network) are as follows:

ECMO centers (CHU = university hospital; CH = non-university hospital):

CHU d’Amiens: E. Zogheib, H. Dupont

CHU d’Angers: A. Mercat, M. Pierrot

CHU J. Minjoz, Besançon: G. Capellier

CHU L. Pradel, Bron: B. Verdiere, O. Bastien, J.-J. Lehot

CHU de Brest: J. M. Tonnelier

CHU Clermont-Ferrand: D. Guelon

CHU Côte de Nacre, Caen: D. du Cheyron

CHU Henri Mondor, Créteil: A. Thille, T. Pham, C. Brun-Buisson

CHU Dijon: P. Quenot

CHU A. Michallon, Grenoble (Medical ICU): C. Arasomoano, C. Minet, J.-F. Timsit

CHU A. Michallon, Grenoble (Surgical ICU): G. Dessertaine

CHU de Lille: L. Robriquet, E. Jaillette

CHU Marseille: M. Castanier, A. Roch, L. Papazian

CHU Arnaud de Villeneuve, Montpellier: J. Eliet, P. Gaudard, S. Machado

CHG Emile Muller, Mulhouse: K. Kuteifan

CHU Nancy: A. Kimmoun, B. Levy

CHU Nantes: P. Bizouarn, D. Villiers, C. Guitton

CHU Archet 1, Nice: J. Dellamonica

CHR Orléans: T. Boulain

CHU Bichat Claude Bernard, Paris: B. Mourvillier, J. Bailly Salin, M. Wolff

CHU Cochin, Paris: J. Charpentier, J.-D. Chiche, S. Ricome

CHU Lariboisière, Paris: B. Megarbane

CHU Pitié Salpetrière, Paris: A. Combes, M. Schmidt, N. Bréchot, J. Chastre

CHU Haut Lévêque, Pessac: H. Rozé, A. Ouattara

CHU Poitiers: R. Robert, E. Carise

CHD Les Oudaries, La Roche s/Yon: J. Reignier

CHU Charles Nicolle, Rouen: G. Beduneau, J.-C.M. Richard

CHU Pontchaillou, Rennes: Y. Le Tulzo

CHU St. Etienne: F. Zeni, R. Jospe

CHU de Strasbourg: C. Kummerlen, J. P. Gouello

Hôpital Foch, Suresnes: C. Cerf, J. Devaquet

CHU Purpan, Toulouse: B. Riu-Poulenc, A. Luzi

CHU Rangueil, Toulouse: B. Georges, N. Mayeur

CHU Bretonneau, Tours: E. Mercier, A. Guillon

CH Bretagne Atlantique, Vannes: M. L. Eustache

Non-ECMO centers (CHU = university hospital; CH = non-university hospital):

Hôpital de Sallanches: L. Monon, S. Cagnin, J. Ronda

CH d’Agen: A. Khechache, B. Morteau

CH d’Ajaccio: B. Lecomte

CH d’Alençon: K. Merouani

CH d’Annecy: M. Siradot

CH d’Antibes Juan les Pins: F. Tiger

Hôpital Privé d’Antony: M. Benhamou

CH d’Armantières: C. Canevet

CH R. Ballanger, Aulnay sous bois: F. Santoli

CH d’Avignon: K. Debbat

CHI Oise, Beauvais: A.-M. Guerin

CH de Bézier: L. Favier

CHU Pellegrin, Bordeaux: G. Hilbert, Y. Castaing

CHU Saint André, Bordeaux: J. Youssef

CHU A. Paré, Boulogne Billancourt: C. Charron

Clinique J. Villar, Bruges: P. Ragot

CH de Cannes: A. Freche

CH de Carpentras: B. Colin

CHU L. Mourier, Colombes: J.-D. Ricard

CH de Douai: C. Boulle Geronimi

CHSF, Evry: Y. Abadie

CH Val d’Ariège, Foix: J. Desbordes

CHU de Garches: M. Antona

CH de Hyere: C. Cheval

CH de la Dracerie, Draguignan: R. Farhat

CH du Havre: M. Bousta

CH de Laon: J.-C. Guilbaud

CHU R. Salengros, Lille: F. Fourrier

CHU de Limoges: H. Gastinne, M. Clavel, P. Vignon

CH de Lons le Saulnier: A. Gill

CH de Bretagne Sud, Lorient: P. Quiniot

CHU Croix Rousse, Lyon: C. Guerin

CH Saint Luc, Lyon: S. Rosselli

CHU Lyon Sud: V. Piriou

CHU E. Herriot, Lyon: L. Argaud

CH du Mans: F. Grelon

CH F. Quesnay, Mantes

CH de Martigues: P. Courtin

CH de Montauban: S. Vimieux

CH de Mont de Marsan: M. Pascal, A. Karcenty

CHI A. Grégoire, Montreuil: M. Daumal

CHU de Nancy: P.-E. Bollaert

CH de Nîmes: C. Bengler

CHG de Niort: J. Voultoury

CH d’Orléans: T. Boulain

CH d’Orsay: N. Rezgui

CHU Hotel Dieu, Paris: A. Rabat

CHU Pitié Salpétrière: A. Duguet

CHU G. Pompidou, Paris: C. Faizy

CHU St. Antoine, Paris: B. Guidet

CHU St. Louis, Paris: V. Lemiale, E. Azoulay

CHU Tenon, Paris: M. Fartoukh

CHG F. Mitterand, Pau: P. Badia

CH de Périgueux: Y. Monseau

CH de Pontoise: J. Richecoeur

CH L. Binet, Provins: T.-H. Chau

CH de Roanne: P. Beuret

CH de Rodez: A. Delahaye

CH de Saint Bieux: G. Guivarch

CH de Saint Germain: J.-C. Lachérade

CH de Salon de Provence: J. Theodore

CH G. Ramon, Sens: D. Tonduangu

CHU de Strasbourg: P. Lutun

CH Bigorre, Tarbes: T. Dulac, C. Boubien

CH Font pré, Toulon: J.-M. Arnal

CH de Clocheville, Tours: S. Cantagrel

CH de Trappes: B. Granclerc

CH de Vesoul: C. Floriot

CH Mignot Versailles: M. Henry-Lagarrigue

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Correspondence and requests for reprints should be addressed to Tài Pham, M.D., Service de Réanimation Médicale, CHU Henri Mondor, 51 Avenue du Maréchal de Lattre de Tassigny, 94000 Créteil, France. E-mail:

*A complete list of members may be found before the beginning of the References.

Author Contributions: Study concept and design, T.P., L.B., A. Combes, S.C., C.B.-B., A.M., and J.-C.M.R. Acquisition of data, T.P., C.B.-B., J.-C.M.R., and A. Constan. Analysis and interpretation of the data, T.P., S.C., H.R., L.B., and A. Combes. Drafting of the manuscript, T.P., A. Combes, H.R., S.C., J.-C.M.R., C.B.-B., and L.B. Revision of the manuscript: all authors. Statistical analysis, T.P. and S.C. Obtained funding, L.B. and A.M.

This article has an online supplement, which is accessible from this issue's table of contents at www.atsjournals.org

Originally Published in Press as DOI: 10.1164/rccm.201205-0815OC on November 15, 2012

Author disclosures are available with the text of this article at www.atsjournals.org.

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