Mechanisms of action of fascial plane blocks: a narrative review
Bibliographic record
Abstract
BACKGROUND: Fascial plane blocks (FPBs) target the space between two fasciae, rather than discrete peripheral nerves. Despite their popularity, their mechanisms of action remain controversial, particularly for erector spinae plane and quadratus lumborum blocks. OBJECTIVES: This narrative review describes the scientific evidence underpinning proposed mechanisms of action, highlights existing knowledge gaps, and discusses implications for clinical practice and research. FINDINGS: There are currently two plausible mechanisms of analgesia. The first is a local effect on nociceptors and neurons within the plane itself or within adjacent muscle and tissue compartments. Dispersion of local anesthetic occurs through bulk flow and diffusion, and the resulting conduction block is dictated by the mass of local anesthetic reaching these targets. The extent of spread, analgesia, and cutaneous sensory loss is variable and imperfectly correlated. Explanations include anatomical variation, factors governing fluid dispersion, and local anesthetic pharmacodynamics. The second is vascular absorption of local anesthetic and a systemic analgesic effect at distant sites. Direct evidence is presently lacking but preliminary data indicate that FPBs can produce transient elevations in plasma concentrations similar to intravenous lidocaine infusion. The relative contributions of these local and systemic effects remain uncertain. CONCLUSION: Our current understanding of FPB mechanisms supports their demonstrated analgesic efficacy, but also highlights the unpredictability and variability that result from myriad factors at play. Potential strategies to improve efficacy include accurate deposition close to targets of interest, injections of sufficient volume to encourage physical spread by bulk flow, and manipulation of concentration to promote diffusion.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".