Feasibility of ultrasound‐assisted lumbar punctures performed by pediatric oncologists at the point of care
Bibliographic record
Abstract
BACKGROUND: Ultrasound assistance improves success rates and reduces adverse outcomes of lumbar punctures (LPs) among adult patients in the emergency room and the operating room, but has not been evaluated in pediatric patients with cancer. Our objectives were (1) to determine whether pediatric oncologists could perform ultrasound-assisted LPs following a structured teaching curriculum, and (2) to determine the feasibility of recruiting pediatric cancer patients to a clinical trial of this procedure. METHODS: Three pediatric oncologists completed a curriculum composed of didactic teaching followed by hands-on workshops. Each learner was evaluated during 20 attempts at three ultrasound tasks using the cumulative sum method. The three pediatric oncologists then performed ultrasound assessments prior to routinely scheduled LPs. Feasibility was defined as ability to perform at least 30 ultrasound-assisted LPs within 6 months. Secondary outcomes were the proportion of successful, bloody, or traumatic LPs, time required, and perceived helpfulness of ultrasound. RESULTS: All three pediatric oncologists achieved competence in the three tasks of ultrasound scanning within 20 evaluated attempts. We recruited 62 patients within 1 month, and 58 underwent an ultrasound-assisted LP. All LPs were successful. Two LPs (4%) had ≥500 red blood cells (RBCs)/μl, and nine (16%) had ≥10 RBCs/μl. Median time to conduct the scan was 1.9 minutes (range 0.8-4.0 minutes). In 37 (64%) of the LPs, ultrasound assistance was considered helpful or very helpful. CONCLUSIONS: Pediatric oncologists readily achieved competence in ultrasound-assisted LPs, and ultrasound was commonly perceived as helpful. It is feasible to proceed to a randomized trial of this procedure in pediatric cancer.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".