Surgeon-performed pericapsular nerve group (PENG) block for total hip arthroplasty using the direct anterior approach: a cadaveric study
Bibliographic record
Abstract
BACKGROUND: During total hip arthroplasty (THA) using the direct anterior approach, orthopaedic surgeons can identify all anatomical landmarks required for pericapsular nerve group (PENG) blocks and carry out the latter under direct vision. This cadaveric study investigated the success of surgeon-performed PENG block. Success was defined as dye staining of the articular branches of the femoral and accessory obturator nerves. METHODS: 11 cadavers (18 hip specimens) were included in the current study. To simulate THA in live patients, an orthopaedic surgeon inserted trial prostheses using the direct anterior approach. Subsequently, a block needle was advanced until contact with the bone (between the anterior inferior iliac spine and iliopubic eminence). 20 mL of 0.1% methylene blue was injected. Cadavers were then dissected to document the presence and dye staining of the femoral, lateral femoral cutaneous, obturator and accessory obturator nerves as well as the articular branches of the femoral, obturator and accessory obturator nerves. RESULTS: Methylene blue stained the articular branches of the femoral nerve and the articular branches of the accessory obturator nerve (when present) in all hip specimens. Therefore, surgical PENG block achieved a 100% success rate. Dye stained the femoral and obturator nerve in one (5.6%) and two (11.1%) hip specimens, respectively. No dye staining was observed over the accessory obturator nerve in the pelvis nor the lateral femoral cutaneous nerve. CONCLUSION: Surgeon-performed PENG block during direct anterior THA reliably targets the articular branches of the femoral and accessory obturator nerves. Future trials are required to compare surgeon-performed PENG block with anaesthesiologist-performed, ultrasound-guided PENG block, and surgeon-performed periarticular local anaesthetic infiltration.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".