Physical Rehabilitation and Mobilization in Patients Receiving Extracorporeal Life Support: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: We planned to synthesize evidence examining the potential efficacy and safety of performing physical rehabilitation and/or mobilization (PR&M) in adult patients receiving extracorporeal life support (ECLS). DATA SOURCES: We included any study that compared PR&M to no PR&M or among different PR&M strategies in adult patients receiving any ECLS for any indication and any cannulation. We searched seven electronic databases with no language limitations. STUDY SELECTION AND DATA EXTRACTION: Two reviewers, independently and in duplicate, screened all citations for eligibility. We used the Cochrane Risk of Bias 2 and Cochrane Risk Of Bias In Non-randomized Studies of Interventions tools to assess individual study risk of bias. Although we had planned for meta-analysis, this was not possible due to insufficient data, so we used narrative and tabular data summaries for presenting results. We assessed the overall certainty of the evidence for each outcome using the Grading of Recommendations Assessment, Development, and Evaluation framework. DATA SYNTHESIS: We included 17 studies that enrolled 996 patients. Most studies examined venovenous extracorporeal membrane oxygenation (ECMO) and/or venoarterial ECMO as a bridge to recovery in the ICU. We found an uncertain effect of high-intensity/active PR&M on mortality, duration of mechanical ventilation, ICU length of stay, hospital length of stay, or quality of life compared with low-intensity/passive PR&M in patients receiving ECLS (very low certainty due to very serious imprecision). There was similarly an uncertain effect on safety events including clinically important bleeding, spontaneous intracerebral hemorrhage, limb ischemia, accidental decannulation, or ECLS circuit dysfunction (very low certainty due to very serious risk of bias and imprecision). CONCLUSIONS: Based on the currently available summary of evidence, there is an uncertain effect of high-intensity/active PR&M on patient important outcomes or safety in patients receiving ECLS. Despite indirect data from other populations suggesting potential benefit of high-intensity PR&M in the ICU; further high-quality randomized trials evaluating the benefits and risks of physical therapy and/or mobilization in this population are needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".