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
Bibliographic record
Abstract
Background: Extracorporeal membrane oxygenation (ECMO) has emerged as an advanced therapeutic option for managing acute respiratory distress syndrome (ARDS), especially severe cases of ARDS. However, the mortality remains high among these patients. Therefore, this meta-analysis aims to evaluate the mortality rates and its potential risk and protective factors in ARDS patients receiving ECMO support. Methods: We systematically searched databases including PubMed, the Cochrane Library, Embase, and Web of Science for relevant studies from their respective inception to April 27, 2024. STATA 16 was used for data analysis. The quality of the included studies was assessed by the Newcastle-Ottawa Scale (NOS). Results: A total of 70 studies involving 31,666 ARDS patients were included. The overall mortality was 48% in ARDS patients receiving ECMO support, especially high in coronavirus disease 2019 (COVID-19) related ARDS patients (60%), and the average hospital length of stay (LOS) of survivors [standardized mean difference (SMD) =0.84, 95% CI: 0.30-1.38] was significantly longer than non-survivors. Moreover, the results showed that age [odds ratio (OR) =1.02, 95% confidence interval (CI): 1.01-1.03], body mass index (BMI) [hazard ratio (HR) =0.96, 95% CI: 0.9-0.98], Sequential Organ Failure Assessment (SOFA) score (OR =1.05, 95% CI: 1.02-1.08), ECMO driving pressure (OR =1.07, 95% CI: 1.05-1.10), immunocompromised status (OR =1.07, 95% CI: 1.05-1.09), and total respiratory rate from days 1 to 3 on ECMO (OR =1.04, 95% CI: 1.01-1.08) were all significant predictors for mortality. Conclusions: The current meta-analysis provides valuable insights into the intricate factors influencing mortality rate in ARDS patients on ECMO. The influencing factors for mortality should be further explored in the future, which may help reduce the global burden of ARDS.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.039 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".