A N EW S YSTEM FOR S TERNAL I NTRAOSSEOUS I NFUSION IN A DULTS
Bibliographic record
Abstract
BACKGROUND: Intraosseous (IO) infusion provides an alternative route for the administration of fluids and medications when difficulty with peripheral or central lines is encountered during resuscitation of critically ill and injured patients. OBJECTIVE: To report the first 50 uses of a new system for emergency IO infusion into the sternum in adults, the Pyng F.A.S.T.1 IO infusion system. METHODS: Six emergency departments and five prehospital emergency medical services (EMS) sites in Canada and the United States provided clinical and/or research data on their use of the IO system in a pilot study of success rates, insertion times, and complications. Indications for use included adult patient, urgent need for fluids or medications, and unacceptable delay or inability to achieve standard vascular access. A basic data set was standardized for all sites, and some sites collected additional data. RESULTS: The overall success rate for achieving vascular access with the system was 84%. Success rates were 74% for first-time users, and 95% for experienced users. Failure to achieve vascular access occurred most frequently in patients (5 of 9) described subjectively by the user as "very obese," in whom there was a thick layer of tissue overlying the sternum. Mean time to achieve vascular access was 77 seconds. Flow rates of up to 80 mL/min were reported for gravity drip, and more than 150 mL/min by syringe bolus. Pressure cuffs were also used successfully, although fluid rate was controlled by clamping the line. Further research on flow rates is needed. No complications or complaints were reported at two-month follow-up. CONCLUSION: These early data indicate that sternal IO infusion using the new F.A.S.T.1 IO system may provide rapid, safe vascular access and may be a useful technique for reducing unacceptable delays in the provision of emergency treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".