Ultrasound Using the Transverse Approach to the Lumbar Spine Provides Reliable Landmarks for Labor Epidurals
Bibliographic record
Abstract
In Brief BACKGROUND: Ultrasound imaging of the spine has recently been proposed to facilitate identification of the epidural space. In this study, we assessed the accuracy and precision of the transverse approach, using a “single-screen” method, to facilitate labor epidurals. METHODS: We enrolled 61 patients requesting labor epidurals. Ultrasound imaging (transverse approach, 2–5 MHz curved array probe) identified the midline, the intervertebral space, and the distance from the skin to the epidural space (ultrasound depth/UD). During the epidural puncture, we recorded the success of the insertion point, and measured the distance to the epidural space to the nearest half-centimeter of the marked Tuohy needle (needle depth/ND). We calculated the agreement between UD and ND by the concordance correlation coefficient and Bland–Altman analysis with 95% limits of agreement. RESULTS: The average maternal age was 33 ± 4.6 yr, body mass index 29.7 ± 4.8, UD 4.66 ± 0.68 cm, and ND 4.65 ± 0.72 cm. The success of the insertion point was 91.8%, with no need to redirect the needle in 73.8% of the patients. The concordance correlation coefficient between UD and ND was 0.881 (95% CI 0.820–0.942). The 95% limits of agreement were −0.666 to 0.687 cm. CONCLUSIONS: We found a good level of success in the ultrasound-determined insertion point, and very good agreement between UD and ND. This suggests that our proposed ultrasound single-screen method, using the transverse approach, can be a reliable guide to facilitate labor epidural insertion. IMPLICATIONS: This study was designed to assess the accuracy and precision of ultrasound, using the transverse approach, to facilitate placement of labor epidurals. Agreement between ultrasound depth and needle depth were compared and found to be statistically significant. Our findings suggest that ultrasound using the transverse approach may facilitate labor epidural insertion.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".