Extracorporeal membrane oxygenation (ECMO) in patients with severe COVID-19 adult respiratory distress syndrome: a systematic review and meta-analysis 
Bibliographic record
Abstract
Abstract Background: COVID 19 is the most recent cause of Adult respiratory distress syndrome ARDS. Extracorporeal membrane oxygenation (ECMO) can support gas exchange in patients failing conventional mechanical ventilation, but its role is still controversial. We conducted a systematic review and meta-analysis on ECMO for COVID-associated ARDS to study its outcome.Materials and Methods: CENTRAL, MEDLINE/PubMed, Cochrane Library, and Scopus were systematically searched from inception to May 28, 2020. Studies reporting five or more patients with COVID 19 infection treated venovenous with ECMO were included. The main outcome assessed was mortality. Baseline, procedural, outcome, and validity data were systematically appraised and pooled with random-effect methods. The validity of all the included observational studies was appraised with the Newcastle Ottawa scale. Meta-regression and publication bias were tested. This trial was registered with PROSPERO under registration number CRD42020183861Results: From 1647 initial citations, 34 full text articles were analysed and 12 studies were selected, including 194 patients with confirmed COVID 19 infection requiring ICU admission and venovenous ECMO treatment. Median New Castle Ottawa scale was 6 indicating acceptable study validity. 136 patients reached an endpoint of weaning from ECMO or death while the rest were still on ECMO. The median Berlin score for ARDS prior to starting ECMO was III. Patients received mechanical ventilation before ECMO implementation for a median of four days and ECMO was maintained for a median of 13 days. In hospital and short-term mortality were highly variable among the included studies ranging between 0% and 100%. Random-effect pooled estimates suggested an overall in-hospital mortality risk ratio of 0.49 (95% confidence interval 0.259 to 0.721; I2 = 94%). Subgroup analysis according to country of origin showed persistent heterogeneity only in the 7 Chinese studies with pooled estimate mortality risk ratio of 0.66 (I2 = 87%) (95% CI = 0.39-0.93), while the later larger studies coming from the USA showed pooled estimate mortality risk ratio of 0.41 (95% CI 0.28-0.53) with homogeneity (p=0.67) similar to France with a pooled mortality risk ratio of 0.26 (95% CI 0.08-0.43) with homogeneity (p=0.86). Meta-regression showed only younger age as a predictor of mortality (p=0.02). Publication bias was excluded by visualizing the funnel plot of standard error, Egger's test with p=0.566 and Begg&Mazumdar test with p=0.373Conclusion: The study included the largest number of patients with outcome findings of ECMO in this current pandemic. Our findings showed that the use of venovenous ECMO at high-volume ECMO centres may be beneficial for selected COVID 19 patients with severe ARDS. However, none of the included studies involve prospective randomized analyses; and therefore, all the included studies were of low or moderate quality according to the Newcastle-Ottawa scale. In the current era and environment of the pandemic, it will likely be very challenging to conduct a prospective randomized trial of ECMO versus no-ECMO for COVID-19. Therefore, the information contained in this systematic review of the literature is valuable and provides important guidance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.028 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".