To use intraosseous access or not to use intraosseous access: determinants of traineesʼ decision in paediatric emergencies
Bibliographic record
Abstract
OBJECTIVES: We aim to determine whether the duration of paediatric training and previous real life intraosseous (IO) insertion experience influence a trainee paediatrician's decision on emergency vascular access choices. METHODS: A survey was conducted using a predesigned proforma to collect data on paediatric trainees' previous paediatric experience including IO training, and their first choice of vascular access in three hypothetical cases modified from real life scenarios. RESULTS: Of the 105 trainees contacted, 98 participated in the survey, all of which were Advanced Paediatric Life Support Course trained, and 65 had previous real life IO needle insertion experience. Experienced trainees (i.e. with more than 6 years paediatric experience) were more likely to have previous real life experience in IO insertion (odds ratio: 5.94, 95% confidence interval: 2.25-15.72). Despite resuscitation councils' clear recommendation to use IO access in the arrested infant, only 51 participants (52%) chose IO as their first vascular access choice in this situation. Previous real life IO insertion experience significantly increased trainees' willingness to use IO as their first emergency vascular access choice (P<0.0001, Fisher's exact test; odds ratio: 10.13, 95% confidence interval: 3.62-28.35). CONCLUSION: Nothing helps more than previous real life IO needle insertion experience to reduce trainee paediatricians' reluctance in using IO access in an emergency, but this experience was only found more frequently among the more experienced trainees. IO access-specific workshops may provide useful supplemental training to traditional resuscitation courses, and may reduce trainees' reluctance in its use.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".