The Nerves of the Adductor Canal and the Innervation of the Knee
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Adductor canal block contributes to analgesia after total knee arthroplasty. However, controversy exists regarding the target nerves and the ideal site of local anesthetic administration. The aim of this cadaveric study was to identify the trajectory of all nerves that course in the adductor canal from their origin to their termination and describe their relative contributions to the innervation of the knee joint. METHODS: After research ethics board approval, 20 cadaveric lower limbs were examined using standard dissection technique. Branches of both the femoral and obturator nerves were explored along the adductor canal and all branches followed to their termination. RESULTS: Both the saphenous nerve (SN) and the nerve to vastus medialis (NVM) were consistently identified, whereas branches of the anterior obturator nerve were inconsistently present. The NVM contributed significantly to the innervation of the knee capsule, through intramuscular, extramuscular, and deep genicular nerves. The SN had a relatively more modest contribution through superficial infrapatellar and posterior branches as well as contributing to the origin of the deep genicular nerves. CONCLUSIONS: The results suggest that both the SN and NVM contribute to the innervation of the anteromedial knee joint and are therefore important targets of adductor canal block. Given the site of exit of both nerves in the distal third of the adductor canal, the midportion of the adductor canal is suggested as an optimal site of local anesthetic administration to block both target nerves while minimizing the possibility of proximal spread to the femoral triangle.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".