Use of fascial plane blocks for traumatic rib fractures: a scoping review
Bibliographic record
Abstract
BACKGROUND: The primary cause of morbidity and mortality in traumatic rib fractures is respiratory complications due to compromised respiratory mechanics secondary to pain and opioid-related respiratory depression. Thoracic epidural analgesia (TEA) provides effective analgesia but may not be possible in patients due to spinal cord injuries, thoracic vertebral fractures, and coagulopathy. New thoracic fascial plane blocks provide new options for patients with multiple rib fractures (MRFs). OBJECTIVE: Our primary objective was to assess the effectiveness of thoracic fascial plane blocks for patients with MRFs by looking at pain control, opioid consumption, and respiratory function postblock compared with preblock. EVIDENCE REVIEW: Literature was searched using keywords and controlled terms, based on the two concepts "rib fractures" and "fascial plane blocks". Terms were searched in PubMed, Embase, Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews, Web of Science, Scopus, Google Scholar and ClinicalTrials.gov from inception to October 11, 2023, using medical subject headings (MeSH) and free-text terms without date or language restrictions. The terms included rib fractures, thoracic trauma, chest injuries, fascial plane blocks, PEC 1, PEC 2, PEC 3, pectoralis plane, serratus anterior plane (SAPB) and erector spinae plane block. FINDINGS: The available evidence shows that erector spinae plane block and SAPB are effective blocks to provide analgesia and reduce opioid requirements in patients with unilateral or bilateral rib fractures. CONCLUSIONS: More randomized control studies are needed to compare these blocks with paravertebral block or TEA to see if they provide analgesia, improve respiratory function, and reduce opioid requirements.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".