The hospital length of stay and mortality and its risk and protective factors among patients with acute respiratory distress syndrome receiving extracorporeal membrane oxygenation: a systematic review and meta-analysis

Introduction

Acute respiratory distress syndrome (ARDS) is a life-threatening inflammatory lung injury characterized by bilateral pulmonary infiltrates and sudden onset, presenting with alveolar flooding, impaired gas exchange, and acute respiratory failure based on the Berlin definition (1). The incidence of ARDS is estimated to range from 10 to 86 cases per 100,000 people annually, with mortality rates varying between 26% to 61.5% (2,3). During the coronavirus disease 2019 (COVID-19) pandemic, mortality rates among ARDS patients were particularly high, documented with 57%, even reaching 94% (4-6). Despite significant advancements in critical care management, ARDS continues to pose a major global health challenge, with mortality rates remaining particularly high in severe cases. Veno-venous extracorporeal membrane oxygenation (VV-ECMO) is considered a key option for treating ARDS patients with refractory hypoxemia or those unable to tolerate volume-limited strategies, particularly in severe cases (7). Unlike veno-arterial (VA)-ECMO which provides cardiopulmonary support, VV-ECMO specifically offers respiratory support by temporarily assuming gas exchange functions (8). The treatment involves a mechanical pump that circulates blood through an artificial lung (oxygenator) for carbon dioxide removal and oxygenation before returning blood to the venous circulation (9). For ARDS patients, ECMO serves as a bridge to recovery, providing the lungs with time to heal while ensuring adequate oxygenation and ventilation (7).

Until today, ECMO has been a well-established strategy for supporting ARDS patients and has been successfully used in the management of COVID-19-related ARDS. However, despite advances in the understanding of the pathophysiology of ARDS, mortality among patients remains high with the use of VV-ECMO, with only a modest improvement over the last decade (10-12). Several systematic reviews have assessed mortality rates in ARDS patients receiving ECMO. For instance, Zampieri et al. [2013] conducted a systematic review reporting a pooled mortality rate of 43% among ARDS patients on ECMO (10). Similarly, another systematic review found a mortality rate of 38% in this patient population (12). A more recent systematic review found that the mortality rates ranged between 22% and 62.6% in ARDS patients receiving ECMO (11). Moreover, most of recent narrative review and meta-analyses mainly focused on ECMO utilization in patients with COVID-19-related ARDS found that pooled mortality rates for COVID-19 ARDS patients on ECMO were was 41% and ranged between 14.7% and 67% (13,14). These reviews encompassed studies with diverse patient populations and varying ECMO management protocols, which may have influenced the summarized mortality outcomes. Therefore, there is a clear need for an updated meta-analysis to comprehensively evaluate the overall mortality rates of ARDS patients treated with ECMO, taking into account the varying types of ARDS patients, such as those with mild, severe, or refractory ARDS, as well as distinguishing between ARDS cases with and without COVID-19. Additionally, this meta-analysis should consider differences in ECMO implementation and management protocols, such as the use of VV, VA, or veno-arterial-venous (VAV-ECMO) (VV combined with VA-ECMO), along with the duration of ECMO support.

The variety of mortality rates may be affected by several factors such as age, gender, body mass index (BMI), and Sequential Organ Failure Assessment (SOFA) score for the severity of organ dysfunction or failure on admission (15). Additionally, ventilation strategies during ECMO, such as the timing of ECMO initiation, duration of ECMO support, and complications associated with ECMO use, may also play a significant role (16). Despite these proposed potential predictors, these factors have been assessed in previous systematic reviews (11) and no meta-analysis has systematically summarized their impact on mortality in ARDS patients receiving ECMO. Consequently, this meta-analysis aims to address this gap by evaluating the mortality rates of ARDS patients supported by ECMO and identifying the key predictors associated with mortality. We present this article in accordance with the PRISMA reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-543/rc) (17).

Methods

This meta-analysis was pre-registered in the International Prospective Register of Systematic Reviews (PROSPERO, CRD42024570897). The protocol included the title, aims, inclusion and exclusion criteria, search strategies, data extraction, results, study quality assessment, publication bias, and data analytics strategies. Patient consent or ethical approval was not necessary, as all analyses were calculated based on previous studies.

Search strategy

We systematically searched in online databases, including PubMed, the Cochrane Library, Embase, and Web of Science for relevant studies from inception to April 27, 2024, without language or period restrictions. Medical Subject Headings (MeSH) plus free words were applied for document retrieval, including all known spellings of “acute respiratory distress syndrome” and “extracorporeal membrane oxygenation”. The search strategy of PubMed is shown in Table S1. In addition, trial registries including ClinicalTrials.gov and references of the relevant research and reviews were searched for relevant studies. Furthermore, in order to ensure that we are using the latest research data, the database will be systematically re-screened at the manuscript preparation stage to identify newly published studies, thereby minimizing temporal bias and ensuring comprehensive inclusion of contemporary evidence.

Inclusion and exclusion criteria

Inclusion criteria followed by the participant, study context, outcome, and study design are as follows:

• Patients: patients were diagnosed with ARDS based on the Berlin definition or American-European Consensus Conference on ARDS, and received ECMO (17,18).
• Study context: studies that reported the mortality rates after adult ARDS patients receiving ECMO support, or predictors for mortality were included.
• Outcomes: at least one of the following outcomes was reported: mortality, length of stay (LOS) following ECMO support, or related risk factors for mortality such as age, gender, BMI, SOFA score at the initiation of ECMO, and mechanical ventilation (MV) duration support prior to ECMO initiation.
• Study design: cohort studies including retrospective and prospective cohort studies.

The following studies were excluded: (I) non-ARDS patients; (II) patients received no ECMO; (III) incomplete or inexact quantitative data; (IV) meta-analyses, reviews, case reports, experimental plans, comments, letters, editorials, and conference papers; (V) studies with unavailable full text; (VI) gray literature, proposal papers, and non-English-language studies.

Study selection and data extraction

The included studies were first imported into EndNote software (version X9.3). After duplicate publications were removed, two researchers (J.P. and X.L.) independently screened the titles and abstracts based on the eligibility criteria, and then examined the full text. Any disagreement was resolved by discussion or consultation with a third researcher (J.Z.).

The following data were extracted by two researchers (J.P. and X.L.): (I) baseline study characteristics: title, name of the first author, and year of publication; (II) basic patient characteristics: age, gender, sample size, details about ECMO (type and duration), and the initial SOFA score; (III) outcome indicators mentioned above; (IV) key factors of risk of bias assessment.

Quality assessment

The included studies were evaluated for the risk of bias for every included study was assessed using the Newcastle-Ottawa Scale (NOS), which was deem to assess the quality of non-randomized studies in meta-analysis (19,20). This evaluation tool has considered three factors (e.g., selection of exposed and non-exposed cohort, comparability of cohorts based on the design or analysis, and outcome based on reliability and validity of the scale, adequate follow-up and dropout rate) to appraise the quality of each included study. Each study was rated as low (0–3 points), moderate (4–6 points), and high quality (7–9 points) depending on the guidelines of the NOS. Two researchers (J.P. and X.L.) independently conducted the quality evaluation, and any disagreement was resolved by discussion with a third researcher (J.Z.).

Statistical analysis

All data analyses were conducted with STATA software (version 16, College Station, TX, USA). The standardized mean difference (SMD) with a 95% confidence interval (CI) was calculated for continuous data, and the odds/hazard ratio (OR/HR) with 95% confidence interval (CI) extracted from the included studies was calculated for the effect size of predictors. The I² statistic was used to quantify heterogeneity (21). I²>50% indicated substantial heterogeneity, so a random-effects model was applied; otherwise, a fixed-effect model was applied. Subgroup analyses were used to identify the source of heterogeneity, and sensitivity analyses were also conducted to detect the impact of each study on the pooled effect size (22). To assess publication bias, Egger’s tests and funnel plots were used, provided that there were more than eight included studies for each outcome indicator (21). A P value <0.05 was considered statistically significant.

Results

Search results

Initially, 18,240 studies were retrieved. After duplicate publications (n=5,610) were removed, the remaining studies were examined for titles and abstracts, and then another 8,696 studies were excluded following a screening for potential studies (reasons for exclusion included non-ARDS patients as well as meta, reviews, guidelines, and conference abstracts). The remaining 3,594 studies were further screened with titles and abstracts, of which 3,372 were excluded because of not meeting the eligibility criteria. The remaining 222 studies were further assessed for eligibility by reading their full texts, of which 152 were excluded. Finally, 70 studies were included in this meta-analysis (Figure 1).

Figure 1 Flowchart for the search strategy qualifying studies for ARDS patients receiving ECMO. ARDS, acute respiratory distress syndrome; ECMO, extracorporeal membrane oxygenation; WoS, Web of Science.

Baseline study characteristics

The characteristics of each included study are presented in Table S2. A total of 70 studies involving 31,666 ARDS patients [age ranged from 27.3 years (22) to 65.5 years (5); male ratio, from 13.2% (23) to 96.5% (24)] were included. The SOFA scores at ECMO starting were ranging from 6.0 (25) to 14.0 (26,27). Besides, the durations of ECMO supporting ranged from 6.4 days (28) to 22.0 days (29,30). More details are presented in Table S2. Among the included studies, 19 studies were conducted in America, 21 in Asia, and 30 in Europe (Table 1). Depending on the study design, most of the included studies were retrospective studies except 2 prospective studies (31,32). ARDS patients were involved in 20 studies, 22 studies involved severe ASDS patients, 15 studies included ARDS patients with the COVID-19 (termed as COVID-19 ARDS), 6 studies included patients with severe COVID-19 ARDS (29,30,33-36), 3 studies included patients with trauma-related ARDS (22,37,38), and 2 studies included refractory ARDS patients (39,40). Regarding the diagnosis criteria for ARDS, 18 studies employed the Berlin definition, and 7 studies (31,33,41-45) utilized an arterial partial pressure of the oxygen/fraction of inspired oxygen (PaO₂/FiO₂) ratio threshold alone (predominantly <80 or <70 mmHg), 2 of which explicitly required concomitant FiO₂ ≥80% (33,43). Other criteria included International Classification of Diseases (ICD)-9/ICD-10 codes (3 studies) (46-48), Extracorporeal Life Support Organization (ELSO) guidelines (4 studies) (49-52), EOLIA trial enrollment criteria (3 studies) (27,53,54), and the World Health Organization (WHO) definition (3 studies) (5,55,56), while the specific criteria were not mentioned in 20 studies. Eight studies (29,30,33,35,50,57-59) used reverse transcription-polymerase chain reaction (RT-PCR) for COVID-19 diagnosis, while the diagnostic approach for COVID-19 ARDS remained consistent with general ARDS standards across other studies involving COVID-19 ARDS or severe COVID-19 ARDS patients (Table S2).

Quality assessment of included studies

The risk of bias for the retrospective and observational included articles are presented in Table S2. The average score for quality of studies based on the NOS was 7.7 for the included studies for the included studies. Specifically, 18 studies were 9 scores, 16 studies were 8 scores, and 35 studies were 7 scores. All studies were rated as low risk of bias (NOS scores ranged 7–9). Only 1 study with 6 scores was with high risk of bias (36).

Meta-analysis results

Overall mortality

The overall mortality in ARDS patients receiving ECMO support was reported in all included studies except 1 study (60). The meta-analyses indicated that the prevalence rate of overall mortality was 48% (95% CI: 43–52%) in ARDS patients receiving ECMO support (Figure 2). Moreover, we also pooled the meta-analyses according to different days after intensive care unit (ICU) admission. It was found that the 30-day overall mortality was 42% (95% CI: 36–48%), the 60-day overall mortality was 45% (95% CI: 40–49%), and the 90-day overall mortality was 48% (95% CI: 43–53%). According to Egger’s test and funnel plot, no publication bias was observed among the included studies (Figure S1, P>0.99).

Figure 2 Forest plot of overall mortality in ARDS patients receiving ECMO support. The x-axis represents the effect size, which is the prevalence rates for mortality in ARDS patients receiving ECMO. A value of 1 on the x-axis indicates that the incidence rate of the event was 100%, while a value of 0 on the x-axis means the incidence rate of the event was 0%. Moreover, a value of −1 on the x-axis is set to ensure the left end of the confidence interval is fully displayed, avoiding any graphical cuts. ARDS, acute respiratory distress syndrome; CI, confidence interval; DL, DerSimonian and Laird; ECMO, extracorporeal membrane oxygenation.

Substantial heterogeneity was observed among the included studies (I²=90.2%), but sensitive analysis did not identify the source of heterogeneity. Subgroup analyses were further conducted depending on several factors as follows: patient’s age (≤40, 41–50, 51–60, and ≥61 years old), the types of ARDS patients (ARDS, severe ARDS, COVID-19 ARDS, severe COVID-19 ARDS, and refractory ARDS), SOFA scores before ECMO support (6-14), the machine type of ECMO used (VV, VA, and VV- and VA-ECMO), and duration of ECMO (≤10, 11–15, and ≥16 days). The results indicated that age, the types of ARDS patients, and ECMO types were the source of heterogeneity (Table 2).

LOS

Hospital (LOS was reported in 12 studies (27,30,39,44,51,52,55,61-65). Of the included studies, 9 studies (30,39,44,51,52,55,61,62,65) reported LOS between survivors and non-survivors, and 10 studies (27,30,39,51,55,61-65) reported hospital LOS during ICU within the hospital stay (in the following termed as ICU LOS). The meta-analyses (Figure 3) revealed that the averaged LOS of survivors was significantly longer than non-survivors (SMD =1.11, 95% CI: 0.08–2.14, P=0.03). Depending on ICU LOS, survivors also showed significantly longer ICU LOS compared to non-survivors (SMD =0.84, 95% CI: 0.30–1.38, P=0.002). The included studies reporting mean LOS and ICU LOS had substantial heterogeneity (LOS, I²=97.4%; ICU LOS, I²=94.1%). The sensitivity analyses showed that the results remained consistent after excluding any study, indicating stable and reliable results (Figure S2). No publication bias was found among the included studies as seen from the funnel plot (Figure S3) and Egger’s tests (the averaged LOS, P=0.13; ICU LOS, P>0.99).

Figure 3 Forest plot of LOS in ARDS patients receiving ECMO support. The x-axis represents the effect size, which represents the SMD. An SMD value of 5 indicates that the mean value of the LOS for survivors is longer than that for non-survivors, and a value of 0 signifies that there is no difference in the mean LOS between the two groups (survivors and non-survivors). Conversely, an SMD value of −5 shows that the mean value of the averaged LOS for survivors is lower than that for non-survivors. ARDS, acute respiratory distress syndrome; CI, confidence interval; DL, DerSimonian and Laird; ECMO, extracorporeal membrane oxygenation; ICU, intensive care unit; LOS, length of stay; SMD, standardized mean difference.

Predictors for mortality

Among the included studies, predictors for mortality included patient’s age (n=20, Figure 4A) (23,25,28,32,37,38,40-43,50,52,53,60,62,63,65-68), gender (n=3, Figure 4B) (23,42,69), BMI (n=8, Figure 4C) (40,42,43,53,55,63,68,70), SOFA scores at ECMO starting (n=7, Figure 5A) (42,54,62,63,68,69,71), driving pressure of ECMO (driving pressure = plateau airway pressure-positive end-expiratory pressure) (n=6, Figure 5B) (42,43,54,63,65,69), MV duration support prior to ECMO initiation (n=6, Figure 5C) (23,28,43,62,63,68), ARDS’s immunocompromised status (n=5, Figure 5D) (41,43,65,69,72), the value of the PaO₂/FiO₂ concentration values ratio of patients before ECMO (n=6, Figure 6A) (23,25,42,63,64,66), and total respiratory rate from days 1 to 3 on ECMO (n=3, Figure 6B) (41,66,69) were extracted for meta-analyses. The results showed that patient’s age, BMI, SOFA, ECMO driving pressure, immunocompromised status, and total respiratory rate from days 1 to 3 on ECMO were significant predictors for mortality (Table 3). In detail, age in years was significant risk factor of mortality, with the older the ARDS patient, the higher the risk of mortality (Figure 4A, OR =1.02, 95% CI: 1.01–1.03, P<0.001). While BMI was a significant protective factor of mortality, indicating the higher BMI, the lower risk of mortality (Figure 4C, OR =0.96, 95% CI: 0.93–0.98, P<0.001). Higher SOFA scores (Figure 5A, HR =1.05, 95% CI: 1.02–1.08, P=0.009), higher driving pressure (Figure 5B, HR =1.07, 95% CI: 1.05–1.10, P<0.001), poor immunocompromised status (Figure 5D, HR =1.07, 95% CI: 1.05–1.09, P=0.01), and total respiratory rate from days 1 to 3 on ECMO (Figure 6B, HR =1.04, 95% CI: 1.01–1.08, P<0.001) corresponded to higher risk of mortality. In addition, substantial heterogeneity was presented in most of the predictors including age (I²=62.3%), gender (I²=80.6%), BMI (I²=53.6%), MV duration support prior to ECMO initiation (I²=83.3%), immunocompromised status (I²=74.5%), and PaO₂/FiO₂ ratio before ECMO (I²=67.4%). The sensitivity analyses showed that the results remained consistent after excluding any study, indicating stable and reliable results (Figures S4,S5). According to the funnel plots (Figure S6) and P values of Egger’s test, publication bias was only seen in SOFA scores (P=0.02).

Figure 4 Forest plot of risk and protective predictors of mortality in ARDS patients receiving ECMO support. (A) Age; (B) gender; (C) BMI. The x-axis in this forest plot represents the effect size, specifically the OR or HR, on a logarithmic scale. The central value of 1.0 is the line of no effect, meaning a predictor has no association with mortality. Values to the right of 1 (e.g., 5) indicate risk factors, where an OR/HR of 5 means a patient with that predictor has a five times higher odds/hazard of death. Conversely, values to the left of 1 (e.g., 0.1) indicate protective factors, where an OR/HR of 0.1 signifies a 90% reduction in the odds/hazard of death. ARDS, acute respiratory distress syndrome; BMI, body mass index; CI, confidence interval; DL, DerSimonian and Laird; ECMO, extracorporeal membrane oxygenation; HR, hazard ratio; OR, odds ratio.

Figure 5 Forest plot of risk predictors of mortality in ARDS patients receiving ECMO support. (A) SOFA score; (B) driving pressure; (C) MV duration support prior to ECMO initiation; (D) immunocompromised status. The x-axis in this forest plot represents the effect size, specifically the OR or HR, on a logarithmic scale. The central value of 1.0 is the line of no effect, meaning a predictor has no association with mortality. Values to the right of 1 (e.g., 5) indicate risk factors, where an OR/HR of 5 means a patient with that predictor has a five times higher odds/hazard of death. Conversely, values to the left of 1 (e.g., 0.1) indicate protective factors, where an OR/HR of 0.1 signifies a 90% reduction in the odds/hazard of death. ARDS, acute respiratory distress syndrome; CI, confidence interval; DL, DerSimonian and Laird; ECMO, extracorporeal membrane oxygenation; HR, hazard ratio; MV, mechanical ventilation; OR, odds ratio; SOFA, Sequential Organ Failure Assessment.

Figure 6 Forest plot of risk predictors of mortality in ARDS patients receiving ECMO support. (A) PaO₂/FiO₂ ratio before ECMO; (B) total respiratory rate from days 1 to 3 on ECMO. The x-axis in this forest plot represents the effect size, specifically the OR or HR, on a logarithmic scale. The central value of 1.0 is the line of no effect, meaning a predictor has no association with mortality. Values to the right of 1 (e.g., 5) indicate risk factors, where an OR/HR of 5 means a patient with that predictor has a five times higher odds/hazard of death. Conversely, values to the left of 1 (e.g., 0.1) indicate protective factors, where an OR/HR of 0.1 signifies a 90% reduction in the odds/hazard of death. CI, confidence interval; DL, DerSimonian and Laird; ARDS, acute respiratory distress syndrome; ECMO, extracorporeal membrane oxygenation; HR, hazard ratio; OR, odds ratio; PaO₂/FiO₂, the arterial partial pressure of the oxygen/fraction of inspired oxygen.

Discussion

In this systematic review and meta-analysis, 70 studies with 31,666 patients were included to investigate the overall mortality and its predictors. The mean age of patients ranged from 27.3 to 65.5 years. Moreover, the difference in hospital LOS was assessed between survivors and non-survivors. The results indicated that the overall mortality was 48%, and the significant predictors for mortality included patients’ age, BMI, SOFA score, driving pressure, immunocompromised status, and total respiratory rate from days 1 to 3 on ECMO. The hospital LOS and ICU LOS were significantly longer in survivors compared to non-survivors among ARDS patients receiving ECMO support, likely reflecting the extended recovery period required for patients who ultimately survived. These findings highlight the importance of early identification of high-risk patients and tailored ECMO management strategies to improve outcomes.

Although ECMO has been used for decades to support patients with ADRS (73) and is an established mode of rescue therapy (73-75), its use in ARDS patients is still debatable. ECMO is highly invasive and correlates to a high risk of complications such as hemorrhage, infection, renal failure, and mortality (76). This meta-analysis revealed that the overall mortality reached 48% regardless of the type of ARDS patients, which was consistent with previous reviews (11,77). Depending on the different kinds of ARDS patients, we found that the overall mortality was higher in more severe cases (severe ARDS > ARDS, and severe COVID-19 ARDS > COVID-19 ARDS), and it was similar between ARDS alone and COVID-19 ARDS. Moreover, ARDS patients with higher SOFA scores before ECMO had higher overall mortality, and ARDS patients receiving VV-ECMO support showed lower mortality rates compared to those receiving VV- and VA-ECMO support. Furthermore, both LOS and ICU LOS of survivors were significantly longer than non-survivors. Among the included studies, the averaged hospital LOS in survivors reached 44 days, while only 30 days in non-survivors. Similar results were observed in ICU LOS (survivors, averaged 30 days; non-survivors, 18 days). By enabling the lungs to heal while simultaneously ensuring oxygenation and ventilation, ECMO serves as a critical bridge to the recovery of ARDS patients (78).

The predictors for mortality identified. In the current this meta-analysis, age was identified as a significant predictor for mortality, which has previously been shown to be independently associated with risk of mortality in patients with ARDS (79,80). Although no specific age contraindication in the ECMO guideline was provided, it is important and necessary to consider increasing risk of mortality with increasing age (81). The subgroup analyses showed that the older the ARDS patients, the higher the mortality (i.e., the overall mortality reached 68% among ARDS patients aged over 60 years and 47% among patients aged under 40 years). On the contrary, a recent study held that the mean age >65 years was not a predictor for mortality in ARDS patients undergoing ECMO (24). The likelihood of unsuccessful weaning from ECMO is higher in older patients with ARDS (28). As a result, older patients with ARDS receive ECMO less frequently than younger patients (82). These findings suggest that age may be a predictor for mortality of adult ARDS patients rather than older patients. As a continuous variable, however, age is of statistical significance and its clinical significance is questionable. Therefore, it should be carefully considered whether age can serve as an important determinant of ECMO use for ARDS patients, or whether age can be an independent predictor for mortality in adult ARDS patients receiving ECMO support.

BMI, calculated as weight in kilograms divided by height in meters squared (kg/m²). Obesity, defined as BMI ≥30 kg/m² in accordance with WHO definitions (83), is a well-recognized serious risk factor for ICU admission, MV, and death in COVID-19 patients (84-86). In non-COVID-19 patients, BMI was demonstrated with an increased risk for developing ARDS, while there were inconsistent findings in increase in mortality. Consistent with a previous report (87), this study showed that BMI was a predictor for mortality in patients with ARDS receiving ECMO, with higher BMI corresponding to lower mortality. Several previous studies also found that higher BMI produces a higher ICU survival rate (88-90). A possible beneficial effect of obesity is to reduce lung inflammation, as well as the risk associated with changing respiratory dynamics in ARDS. Low-grade inflammation induced by obesity may be a protective factor in ARDS to prevent further progress (91). Furthermore, the mortality of immunocompromised ARDS patients was much higher than that of immunocompetent patients (92,93). The immunocompromised patients receiving ECMO often exhibit high infection rates, mixed pathogen infection, unfavorable outcomes, and even overuse of antibiotics. Moreover, ECMO-related complications such as major bleeding, ventilator-associated pneumonia, and cannula infections are commonly observed in immunocompromised patients (65). Therefore, this meta-analysis considered immunocompromised status a significant risk factor for mortality. However, the pathology of immunocompromised patients with ARDS receiving ECMO support is unclear, and the risk of mortality of ECMO for immunocompromised patients with ARDS should be further explored.

In this meta-analysis, it observed that higher SOFA scores were associated with higher risk of mortality, which was in accordance with previous studies (80,94,95). For instance, Roch et al. [2014] found that the SOFA score immediately before ECMO an independent risk factor for mortality (94). evidence shows that the initial SOFA score (calculated by collecting required variables—the ratio of PaO₂ to the fraction of inspired oxygen) is one of the important indexes for quantifying the severity of organ dysfunction or failure on admission (14). Although the SOFA score was not originally designed to predict outcomes, numerous studies have elucidated a clear association of SOFA with mortality (96,97). Hence, SOFA may be a good index for assessing organ dysfunction or failure and correlates to mortality (98). Bels et al. [2021] found in a cohort study involving 93 MV-treated patients with COVID-19 ARDS showing that the SOFA score was associated with patient survival even after adjusting for age, sex, and comorbidities (99). In this study, the subgroup analyses also indicated that higher SOFA scores before ECMO produced higher overall mortality (12–14, 68%; 6–8, 41%). To sum up, SOFA score may be important for predicting the mortality of ARDS patients.

In addition, driving pressure and total respiratory rate from days 1 to 3 on ECMO were also identified as predictors for mortality, i.e., higher driving pressure and total respiratory rate led to higher mortality. Evidence suggests that ECMO is effective in some patients with severe ARDS who receive ECMO support with very low ventilation and decreased respiratory rate and plateau pressure, potentially minimizing ventilator-induced lung injury (100,101). However, ECMO ventilation strategies have garnered limited attention, and it remains unclear how ECMO-treated ARDS patients are managed in clinical practice on a broader international scale. This may stem from the fact that respiratory system compliance is closely related to the functional lung size during disease. Various elements of the above lung-protective strategies, including low ventilation and reduced respiratory rate and driving pressure, can alleviate mechanical stress on the lungs, thereby relieving ventilator-induced lung injury (102). Therefore, these strategies are expected to enhance patient survival rates. However, clinicians frequently encounter a dilemma where optimizing one element of these strategies may adversely affect another, leading to uncertain overall outcomes (103). Furthermore, conflicting findings from previous clinical studies have been reported regarding the manipulation of different lung-protective elements (21,104). Given the increasing utilization of ECMO in the ICU for severe ARDS, further research into optimal ventilation strategies during ECMO support is imperative.

This is the first comprehensive meta-analysis assessing the overall mortality and investigating its associated predictors in ARDS patients who received ECMO support. Nonetheless, this study had certain limitations. Firstly, the included studies displayed significant heterogeneity with respect to the design, study populations, ECMO implementation and management protocols, and outcome definitions, which might contribute to the variations observed in reported mortality and influence the identification of related factors to mortality. Secondly, only English-language studies were included, which might have inadvertently excluded valuable data from studies published in other languages. Thirdly, this meta-analysis aimed to systematically synthesize the available evidence, but it could not address the limitations inherent in primary studies, and analyzing cohort studies was also particularly challenging due to heterogeneity in subjects, outcome definitions, study designs, and potential biases. Finally, the predictors were revealed based on a limited number of studies, which precluded confidence in the consistency of the results. In the end, it’s need to mention that the included studies lacked detailed reporting on modifiable risk factors such as driving pressure thresholds and respiratory rate adjustments, highlighting a critical gap in understanding their impact on mortality outcomes. Future research should prioritize systematic evaluation of these variables to refine ARDS management strategies.

Conclusions

ARDS remains a major public health challenge with a high mortality rate globally. ECMO has become a potentially life-saving therapy for patients with ARDS. Despite recent advances in technology and patient management, the optimal approach for patients with ARDS on ECMO remains a matter of debate, and the mortality rate is still high (48%). Patient’s age, SOFA score, immunocompromised status, and ventilation strategies during ECMO, such as driving pressure, and total respiratory rate from days 1 to 3 on ECMO are possible risk predictors for mortality in ARDS patients receiving ECMO support, while BMI is a possible protective predictor against mortality. A comprehensive understanding of the influencing factors for mortality of ARDS patients on ECMO can guide clinical practice, improve patient outcomes, and help reduce the global burden of ARDS.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-543/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-543/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-543/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Patient consent or ethical approval was not necessay, as all analyses were calculated based on previous studies.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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