Retrospective review of spinal magnetic resonance images to determine the margin of safety for epidural analgesia in pediatric patients
Bibliographic record
Abstract
BACKGROUND: Deeply sedated children cannot provide feedback if an epidural needle traumatizes the Spinal Cord (SC). Knowing relevant structure depths may, therefore, improve safety. We aimed to determine the epidural margin of safety, i.e., distances from the Ligamentum Flavum (LF) and from the dura mater to the SC in pediatric patients measured (i) Perpendicular to the SC and (ii) Parallel to the spinous process (to approximate needle trajectory). METHODS: Retrospective review of pediatric (0‒12 years-old) T2-weighted sagittal MRI spine scans without spinal pathology. Three investigators independently measured distances from the ventral edge of the LF, and from the ventral edge of the dura mater to the SC at T5/T6, T9/T10, and L1/L2. All measurements were taken perpendicular to the SC and parallel to the angle of the spinous process of the inferior vertebra. RESULTS: 111 MRI scans [52 females, 0.08‒12 (median 7) years-old] were analyzed. The conus medullaris was identified superior to the L1 vertebra in 47 scans, requiring L1/L2 measurement exclusion. When all ages were combined, the largest median (range) depth [dura-mater-SC = 4.87 (2.30‒10.30) mm, LF-SC = 8.10 (4.57‒12.53) mm, measured perpendicular to the SC; and dura-mater-SC = 8.20 (3.75‒19.57) mm; LF-SC = 13.40 (5.50‒39.77) mm, measured at the angle parallel to the inferior spinous process] was at T5/T6. CONCLUSION: Our results suggest that the margin of safety (dura-mater-SC distance and LF-SC distance) for performing epidurals in children may be greatest at the mid-thoracic spinal region. The measured ranges were very wide. Further studies are warranted to validate these findings in pediatric patients with other relevant "epidural placement" positions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".