Anatomical basis of fascial plane blocks
Bibliographic record
Abstract
Fascial plane blocks (FPBs) are regional anesthesia techniques in which the space ("plane") between two discrete fascial layers is the target of needle insertion and injection. Analgesia is primarily achieved by local anesthetic spread to nerves traveling within this plane and adjacent tissues. This narrative review discusses key fundamental anatomical concepts relevant to FPBs, with a focus on blocks of the torso. Fascia, in this context, refers to any sheet of connective tissue that encloses or separates muscles and internal organs. The basic composition of fascia is a latticework of collagen fibers filled with a hydrated glycosaminoglycan matrix and infiltrated by adipocytes and fibroblasts; fluid can cross this by diffusion but not bulk flow. The plane between fascial layers is filled with a similar fat-glycosaminoglycan matric and provides gliding and cushioning between structures, as well as a pathway for nerves and vessels. The planes between the various muscle layers of the thorax, abdomen, and paraspinal area close to the thoracic paravertebral space and vertebral canal, are popular targets for ultrasound-guided local anesthetic injection. The pertinent musculofascial anatomy of these regions, together with the nerves involved in somatic and visceral innervation, are summarized. This knowledge will aid not only sonographic identification of landmarks and block performance, but also understanding of the potential pathways and barriers for spread of local anesthetic. It is also critical as the basis for further exploration and refinement of FPBs, with an emphasis on improving their clinical utility, efficacy, and safety.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".