Abstract 12639: The Disparities of Gender-Based Out of Hospital Cardiac Arrest Characteristics and Outcomes: Comparing Rural to Urban Vancouver Island
Bibliographic record
Abstract
Introduction: The relationship between the “chain of survival” metrics of Out of Hospital Cardiac Arrest (OHCA) and survival rates in rural settings has not been fully examined. In previous studies, low survival rate was attributable to the modifiable prehospital metrics and Return Of Spontaneous Circulation (ROSC). Hypothesis: Gender-based disparities in the modifiable and non-modifiable OHCA characteristics and outcomes are significant between rural and urban settings. Methods: We did a post-hoc analyses of data from the British Columbia cardiac arrest registry, which enrolled all emergency medical system (EMS)-treated OHCAs. All non-EMS-witnessed OHCAs on Vancouver Island from Jan. 2019 to Oct. 2020 were included. The independent variable of interest was rural versus urban settings. Rural areas were defined as all areas outside the urban clusters (population ≥ 1000 and a population density of ≥ 400/km2). Our outcomes were 1. Post resuscitation ROSC, and 2. Survival to hospital discharge. We reported gender-mediated measures and adjusted odds ratios using logistic regression models. Results: We included 1172 OHCA patients, with 23% in rural settings, 33% female, 30% had ROSC, and 23% survived to hospital discharge. The median EMS response time, from 911-call to first EMS arrival, was prolonged [10.5 mins (IQR 7.5-15)] in rural settings compared to urban settings [6.5 mins (IQR 5-9)] (p value<.001). Among females, rural settings were associated with higher odds of bystander CPR compared to males [(OR 1.86; 95% CI 1.04-3.35), (OR 1.42; 95% CI 0.95-2.13)], respectively. After adjusting for all covariates, rural settings were associated with lower odds of ROSC among males compared to females [(OR 0.53; 95% CI 0.31-0.90), (OR 0.70; 95% CI 0.34-1.41)], respectively; however, not associated with survival to hospital discharge. Conclusions: There are significant disparities in the modifiable prehospital OHCA characteristics, and post resuscitation ROSC between rural and urban Vancouver Island. An officially integrated rural CPR community-based program, and innovations focused on gender-based implementation may significantly improve OHCA survival rates and subsequent prognostication.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".