Instrumentation of the Loss-of-Resistance Technique for Epidural Needle Insertion
Bibliographic record
Abstract
Epidural anesthesia is the most common form of anesthesia in obstetrics. The loss-of-resistance to saline injection is used to confirm when the needle tip enters the epidural space. This procedure is highly dependent on skill and expertise, so it is useful to quantify the tissue resistance during insertion. Sensors are used to measure the force and displacement of the plunger of the syringe and the pressure at the needle tip. A model is also developed to estimate the pressure from the force and displacement. Tests are first performed on porcine tissue to compare the continuous-pressure and intermittent-pressure versions of the technique and to compare the paramedian and midline needle approaches. The accuracy of the pressure model is 12% of peak pressure for the continuous technique and 20% for the intermittent technique. Significant differences in injection flow rate were also found for the muscle, interspinous ligament, and ligamentum flavum encountered in the two approaches. A small clinical study on human subjects was performed and again significant differences were found in flow rate for different tissues. These quantitative results improve the understanding of small differences in feel that have been previously known qualitatively and may help in the development of simulators.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".