Effect of COVID-19 on the prevalence of bystanders performing cardiopulmonary resuscitation: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The importance of bystander cardiopulmonary resuscitation (CPR) during out-of-hospital cardiac arrests is especially important in the context of coronavirus disease 2029 (COVID-19) because it can significantly influence survival outcomes. The objective of this meta-analysis was to examine the primary outcomes of bystander CPR during the pandemic and pre-pandemic periods. METHODS: A search was conducted in the PubMed Central, Scopus, and EMBASE databases, as well as the Cochrane Central Register of Controlled Trials database, up to December 10, 2023. In cases where the value of I² was greater than or equal to 50% or the Q-test indicated that the p-value was less than or equal to 0.05, the studies were considered to be heterogeneous. Sensitivity assessment was performed using the leave-one-out methodology. The study protocol was registered in PROSPERO with the ID number CRD42023494912. RESULTS: Twenty-five articles were included in this meta-analysis. Pooled analysis showed that bystander CPR frequency during the COVID-19 pandemic was 38.8%, compared to 44.8% for the pre-pandemic period (odds ratio: 1.04; 95% confidence interval: 0.93-1.16; p = 0.48). CONCLUSIONS: The article's conclusions indicate that the COVID-19 pandemic influenced a reduction in bystander CPR compared to the pre-pandemic period, but this difference was not statistically significant. Further research is recommended to understand attitudes, including the fears of witnesses, before performing CPR on patients with suspected or confirmed infectious diseases. The study highlights the importance of bystander intervention in emergency situations and the impact of a pandemic on public health response behaviors.
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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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.053 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".