Surging Role of Extracorporeal Membrane Oxygenation in Refractory ARDS Due COVID-19 and In-depth Review of Existing Applications
Bibliographic record
Abstract
Introduction: Extra Corporeal Membrane Oxygenation (ECMO) is a device applied to maintain cardiopulmonary support in patients in whom there is a failure of the cardiopulmonary function to maintain perfusion to vital organs. Previously, ECMO was used in pulmonary embolism, cardiogenic shock, myocarditis, and heart failure cases. Its use in refractory acute respiratory distress syndrome (ARDS) in coronavirus disease 2019 (COVID-19) has increased, but the data regarding its safety, efficacy, and mortality benefit remains unclear. The focus of our review is to further expand on these areas and outline the indication, techniques, and complications associated with its use. Methods: We did an extensive search of various databases such as PubMed, Cochrane, ScienceDirect, and Jama Network and studied 41 papers, including free full articles such as systematic reviews, meta-analyses, and clinical trials published within the past five years. Results: Implementation of ECMO is advantageous when the PaO2/FiO2 is in the range of 100 to 150 mmHg. For COVID-19 patients, the most appropriate approach is to drain from a femoral venous cannula and thread it to the inferior vena cava just 1-2cm below the cavoatrial junction. It was seen that the most common complication of ECMO use is coagulopathy. Limb ischemia had a variable incidence from 10 to 70% and is more common in venous-arterial ECMO. Conclusion: ECMO is lifesaving in a highly selected group of patients to prolong survival, reduce complications and provide a good prognosis in terms of mortality. To prevent circuit thrombosis, anticoagulation is key, and understanding feasible intra-atrial communication sites, such as a patent foramen ovale or atrial septal defects, is beneficial to mitigate the risk of stroke and cutting down consequences of thromboembolism.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".