Augmented Reality in Pediatric Septic Shock Simulation: Randomized Controlled Feasibility Trial
Bibliographic record
Abstract
BACKGROUND: Septic shock is a low-frequency but high-stakes condition in children requiring prompt resuscitation, which makes it an important target for simulation-based education. OBJECTIVE: In this study, we aimed to design and implement an augmented reality app (PediSepsisAR) for septic shock simulation, test the feasibility of measuring the timing and volume of fluid administration during septic shock simulation with and without PediSepsisAR, and describe PediSepsisAR as an educational tool. We hypothesized that we could feasibly measure our desired data during the simulation in 90% of the participants in each group. With regard to using PediSepsisAR as an educational tool, we hypothesized that the PediSepsisAR group would report that it enhanced their awareness of simulated patient blood flow and would more rapidly verbalize recognition of abnormal patient status and desired management steps. METHODS: We performed a randomized controlled feasibility trial with a convenience sample of pediatric care providers at a large tertiary care pediatric center. Participants completed a prestudy questionnaire and were randomized to either the PediSepsisAR or control (traditional simulation) arms. We measured the participants' time to administer 20, 40, and 60 cc/kg of intravenous fluids during a septic shock simulation using each modality. In addition, facilitators timed how long participants took to verbalize they had recognized tachycardia, hypotension, or septic shock and desired to initiate the sepsis pathway and administer antibiotics. Participants in the PediSepsisAR arm completed a poststudy questionnaire. We analyzed data using descriptive statistics and a Wilcoxon rank-sum test to compare the median time with event variables between groups. RESULTS: We enrolled 50 participants (n=25 in each arm). The timing and volume of fluid administration were captured in all the participants in each group. There was no statistically significant difference regarding time to administration of intravenous fluids between the two groups. Similarly, there was no statistically significant difference between the groups regarding time to verbalized recognition of patient status or desired management steps. Most participants in the PediSepsisAR group reported that PediSepsisAR enhanced their awareness of the patient's perfusion. CONCLUSIONS: We developed an augmented reality app for use in pediatric septic shock simulations and demonstrated the feasibility of measuring the volume and timing of fluid administration during simulation using this modality. In addition, our findings suggest that PediSepsisAR may enhance participants' awareness of abnormal perfusion.
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".