The Utility of Ultrasound Imaging in Predicting Ease of Performance of Spinal Anesthesia in an Orthopedic Patient Population
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Ultrasonography of the spine improves technical performance of spinal anesthesia, but what is unclear is whether it can predict difficulty. We tested the hypothesis that a good ultrasound view at a given intervertebral level is associated with absence of technical difficulty. METHODS: We performed preprocedural ultrasound of the L1-S1 intervertebral spaces in 100 patients undergoing orthopedic surgery. Visibility of the ligamentum flavum-dura mater and the posterior longitudinal ligament was evaluated using paramedian sagittal oblique and transverse midline (TM) views. Views were classified as good if both of these structures were visible on ultrasound. An operator, blinded to the ultrasound scan, performed surface landmark-guided spinal anesthesia using a midline approach. Absence of technical difficulty was defined as successful dural puncture within 2 skin punctures or 10 needle passes. RESULTS: A good TM view had the best diagnostic accuracy; if this view was obtained, absence of technical difficulty with dural puncture at that level was highly likely (positive predictive value, 85%). Dural puncture could still be feasible despite the absence of a good TM view, as reflected by a negative predictive value of 30%. This was attributed to the limitations of ultrasound imaging in this patient population, as well as the low overall prevalence of difficult dural puncture. Parasagittal oblique views did not have significant diagnostic utility for a midline needle approach. CONCLUSIONS: Ultrasound can be useful in predicting the absence of technical difficulty in performing dural puncture and thus in selecting the optimal intervertebral level for spinal anesthesia.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".