Abstract 11560: Systematic Deployment of AEDs in BC Schools: A Utility and Cost-Effectiveness Study of In-School and Nearby OHCAs
Bibliographic record
Abstract
Background: While pediatric out-of-hospital cardiac arrests (OHCAs) are relatively uncommon, they have a much higher number of potential years of life lost per event. School-located public access automated external defibrillators (AED) may be beneficial to school-aged OHCAs, but also other OHCAs within the school and in the surrounding community. We sought to identify the incidence of OHCAs within and nearby schools in British Columbia (BC), to estimate the number that may benefit from school-located AEDs. Methods: We used prospectively-collected data from the BC OHCA Registry from 2013 to 2018. We examined the addresses of all OHCAs to determine those occurring in public primary and secondary schools. We geo-plotted all OHCAs to identify the number of OHCAs within walking distance of a school. Assuming an average pedestrian speed for AED retrieval of 1.8 m/second, we calculated the number of school-vicinity OHCAs for which a bystander could retrieve an AED prior to a 6.5 minute emergency medical system response interval, assuming that AEDs would be located on the exterior of a school building. Results: There were a total of 401,423 children enrolled at 824 schools annually in the study footprint. Of a total of 12,480 EMS-treated OHCAs (220 aged < 18 years), 20 were in in schools, of which 4 were <18 years of age. Of school located OHCAs, 14 (70%) had initial shockable rhythms, 4 (20%) had an AED applied (of whom 3 survived), and 10 (50%) survived. Of the four school-located pediatric OHCAs, three were witnessed (75%), two had initial shockable rhythms (50%), and two (50%) survived until hospital discharge. A total of 1128/12,480 (9%) OHCAs were within retrieval distance of a school, corresponding to 0.228 per school per year (95% CI 0.201-0.255 year-to-year) , which is above current thresholds for cost-effectiveness. Conclusion: Outcomes of school-located OHCAs are encouraging, especially those with AED application. While the incidence of school-located OHCAs is low, a substantial proportion of OHCAs occur within a retrievable distance to a school, and thus accessible external school-located AEDs may improve overall OHCA outcomes of a community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".