Ultrasound-Guided Multi-Branch Rectus Femoris Nerve Block for Spasticity Assessment
Bibliographic record
Abstract
Background: Stiff-knee gait commonly involves rectus femoris spasticity in patients with central nervous system lesions. Diagnostic nerve blocks aid in predicting treatment outcomes; however, current techniques may overlook multiple nerve branches that innervate the rectus femoris muscle, potentially resulting in an incomplete assessment of treatment outcomes. Methods: We present an ultrasound-guided approach that we currently use in our practice, using anatomical landmarks, including the femoral artery, the sartorius muscle, and the rectus femoris’ characteristic “J-shaped” internal tendon. The technique employs an “elevator” scanning method to identify all motor nerve branches (typically 2–3) entering the proximal third of the rectus femoris muscle. Each branch is blocked using an in-plane needle approach with 1–2 mL of 2% lidocaine. Results: The technique enables the visualization of hyperechoic nerve branches entering the rectus femoris muscle from medial to lateral, sometimes accompanied by small vascular branches that are identifiable with a Doppler ultrasound. Optimal ultrasound settings include probes >8 MHz, appropriate focus positioning, and dynamic range < 60 dB. The multi-branch approach produces rapid-onset motor weakness (5–10 min). Conclusions: This comprehensive multi-branch rectus femoris nerve block technique may enhance diagnostic accuracy for spasticity assessment, potentially leading to more informed treatment selection for stiff-knee gait.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".