The impact of the COVID-19 pandemic on bystander CPR and AED rates in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To evaluate whether the COVID-19 pandemic was associated with changes in bystander CPR and automated external defibrillator (AED) application in Canada. We included adult emergency medical services (EMS)-treated out-of-hospital cardiac arrests (OHCAs) from the Canadian national cardiac arrest registry. The outcomes were bystander CPR and AED application. We fit adjusted piecewise linear segmented logistic regression models to estimate whether the peri-COVID period (February 2020-December 2021), in comparison to pre-COVID (January 2018-January 2020), was associated with a change in the odds of bystander CPR and AED application. We also examined subgroups of private and public only OHCAs. Among the 24,410 OHCAs, the median age was 65 years (IQR 50,77), with 7,822 (32%) females. In the pre-COVID (n=11,271) and peri-COVID (n=13,139) periods, 6,244 (55%) and 7,924 (60%) cases received bystander CPR (+4.9% difference, 95% CI 3.7, 6.2), and 502 (4.5%) and 432 (3.3%) were treated with bystander AEDs (-1.2% difference, 95% CI -1.7, -0.68) respectively. The peri-COVID period was associated with an increased odds of bystander CPR (aOR 1.15; 95% CI 1.03, 1.27) and a decreased odds of bystander AED application (aOR 0.65; 95% CI 0.48, 0.86). This appears to be driven by increases in private-setting bystander CPR (aOR 1.19; 95% CI 1.06, 1.33) and decreases in public-setting AED use (aOR 0.59; 95% CI 0.40, 0.88). The COVID-19 pandemic was associated with an increase in bystander CPR and a decrease in bystander AED application.
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.
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 | 0.001 |
| 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 it