Checking the basis of intraosseous access—Radiological study on tibial dimensions in the pediatric population
Bibliographic record
Abstract
Abstract Background Malposition of intraosseous needles in pediatric patients is frequently reported. Incorrect needle length and penetration depth related to the puncture site and level are possible causes. Aims Aim of this study was to analyze anatomic dimensions of the proximal tibia in the pediatric population with respect to intraosseous needle placement and needle tip position. Methods Plain lower leg radiographs of children aged from birth to 16 years of age were analyzed. Pretibial tissue layer, cortical bone thickness, and the diameter of the medullary cavity were measured at two different puncture levels. Data were analyzed as descriptive statistics and by polynomial regression plots and set in context to commonly used EZ‐IO® needle lengths of 15 and 25 mm. Results Radiographs from 190 patients (104 boys/86 girls) were included. When fully inserted to skin level, up to 10.5% of needles do not reach medullary cavity at one and 18.5% at two patient's fingerbreadths distal to tibial tuberosity. The opposite cortical wall is touched or penetrated in 16% and 25%, respectively. Up to 96% of too deep needle tip positions occur in children younger than 24 months, as do too superficial tip positions in 59%. Conclusions Puncture level and needle length have a great influence on potential needle tip positions. Infants and toddlers are at highest risk for malpositioning. Due to relevant growth‐related differences in tibial anatomy, an age‐related and well‐reflected approach is crucial to successfully establish intraosseous access.
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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 | 0.000 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".