Resuscitative endovascular balloon occlusion of the aorta (REBOA): indications: advantages and challenges of implementation in traumatic non-compressible torso hemorrhage
Bibliographic record
Abstract
BACKGROUND: Resuscitative endovascular balloon occlusion of the aorta (REBOA) is regaining popularity in the treatment of traumatic non-compressible torso bleeding. Advances in invasive radiology coupled with new damage control measures assisted in the refinement of the technique with promising outcomes. The literature continues to have substantial heterogeneity about REBOA indications, applications, and the challenges confronted when implementing the technique in a level I trauma center. Scoping reviews are excellent platforms to assess the diverse literature of a new technique. It is for the first time that a scoping review is adopted for this topic. Advances in invasive radiology coupled with new damage control measures assisted in the refinement of the technique with promising outcomes. The literature continues to have substantial heterogeneity about REBOA indications, applications, and the challenges confronted when implementing the technique in a level I trauma center. Scoping reviews are excellent platforms to assess the diverse literature of a new technique. It is for the first time that a scoping review is adopted for this topic. METHODS: Critical search from MEDLINE, EMBASE, BIOSIS, COCHRANE CENTRAL, PUBMED and SCOPUS were conducted from the earliest available dates until March 2018. Evidence-based articles, as well as gray literature at large, were analyzed regardless of the quality of articles. RESULTS: We identified 1176 articles related to the topic from all available database sources and 57 reviews from the gray literature search. The final review yielded 105 articles. Quantitative and qualitative variables included patient demographics, study design, study objectives, methods of data collection, indications, REBOA protocol used, time to deployment, zone of deployment, occlusion time, complications, outcome, and the level of expertise at the concerned trauma center. CONCLUSION: Growing levels of evidence support the use of REBOA in selected indications. Our data analysis showed an advantage for its use in terms of morbidities and physiologic derangement in comparison to other resuscitation measures. Current challenges remain in the selective application, implementation, competency assessment, and credentialing for the use of REBOA in trauma settings. The identification of the proper indication, terms of use, and possible advantage of the prehospital and partial REBOA are topics for further research. LEVEL OF EVIDENCE: Level III.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".