Determination of the Pretibial Soft Tissue Thickness in Children
Bibliographic record
Abstract
OBJECTIVE: The EZ-IO intraosseous (IO) needle is available in 2 needle sizes for children based on the patient weight. To date, there is no published evidence validating the use of weight-based scaling in children. We hypothesized that pretibial subcutaneous tissue thickness (PSTT) does not correspond with patient weight but rather with age and body mass index (BMI). Our objective was to describe the relationship of a patient's PSTT to their weight, age, and BMI in children less than 40 kg. METHOD: One hundred patients who weighed less than 40 kg were recruited prospectively from October 2013 to April 2015 at a tertiary care pediatric emergency department. All sonographic assessments were performed by 1 of 2 emergency physicians certified in point-of-care ultrasound. A single sonographic image was taken over the proximal tibia corresponding to the site of IO insertion. In patients where both sonographers performed independent measurements, a Pearson correlation coefficient was determined. Univariate linear regression was performed to determine the relationship between age, weight, and BMI with PSTT. RESULTS: One hundred participants were recruited and ranged in age from 10 days to 14 years (mean [SD], 5.01 [3.14] years). Fifty-seven percent of participants were male. Patients' weights ranged from 3.5 to 39.3 kg (mean [SD], 21.42 [9.12] kg), and BMI ranged from 12.1 to 45.0 kg/m (mean [SD], 17.31 [4.00]). The mean (SD) PSTT across participants was 0.68 (0.2) cm. The intraclass correlation coefficient for agreement between the 2 sonographers was moderate (intraclass correlation coefficient, 0.602 [confidence interval, 0.385-0.757]). There were significant positive correlations between BMI and PSTT (r = 0.562, P = <0.001) as well as weight and PSTT (r = 0.293, P < 0.003). There was a weak correlation between age and PSTT (0.065, P = 0.521). CONCLUSIONS: Pretibial subcutaneous tissue thickness correlates most strongly with BMI, followed by weight, and weakly with age. Our findings suggest that current IO needle length recommendations should be based on BMI rather than weight. This would suggest that clinicians need to be aware that young patients in particular with large BMIs may pose problems with current weight-based needle length recommendations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".