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Record W4213091155 · doi:10.1161/circ.138.suppl_2.243

Abstract 243: Variation in Both Layperson Cardiopulmonary Resuscitation Delivery and Subsequent Survival From Sudden Cardiac Arrest Based on Neighborhood-Level Ethnic Characteristics

2018· article· en· W4213091155 on OpenAlexaff
Audrey L Blewer, Shaun K. McGovern, Robert H. Schmicker, Susanne May, Laurie J. Morrison, Tom P. Aufderheide, Mohamud Daya, Ahamed H. Idris, Clifton W. Callaway, Peter J. Kudenchuk, Gary M. Vilke, Benjamin S. Abella

Bibliographic record

VenueCirculation · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineCardiopulmonary resuscitationLaypersonSudden cardiac arrestEthnic groupPopulationDemographyResuscitationEmergency medicineInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Background: Bystander cardiopulmonary resuscitation (B-CPR) delivery and survival from sudden cardiac arrest (SCA) varies at the neighborhood-level with poorer outcomes seen in predominantly black neighborhoods. Despite Latinos being the fastest growing minority population in the US, few studies have assessed whether the proportion of Latinos in a neighborhood is associated with B-CPR delivery and survival from SCA. Objective: We sought to assess whether there is variation in B-CPR rates and survival by neighborhood-level ethnicity. We hypothesized that neighborhoods with a higher proportion of Latinos are associated with lower B-CPR rates and lower survival. Methods: We conducted a retrospective cohort study, using data from the Resuscitation Outcomes Consortium (ROC) Epistry Registry US sites. Neighborhoods were classified by census tract, based on percentage of Latino residents: < 25%, 25%-50%, 51%-75%, or > 75%. We independently modelled the likelihood of receipt of layperson B-CPR and survival by neighborhood-level ethnicity controlling for site and patient-level confounding characteristics. Results: From 2011-2015, ROC collected 27,481 US arrest events; after excluding pediatric arrests, those witnessed by EMS, or occurred in a healthcare or institutional facility, 18,544 were included. B-CPR was administered in 37% events. Among neighborhoods with <25% Latino residents, B-CPR was administered in 39% of events, while it was administered in 27% of events among neighborhoods with >75% Latino residents. B-CPR delivery varied by patient ethnicity with Latinos being less likely to receive B-CPR compared to Whites (OR: 0.73 (CI: 0.62-0.88), p<0.01). Compared with <25% Latino neighborhoods, those in predominantly Latino neighborhoods had lower B-CPR rates (50%-75% Latino: OR: 0.79 (CI:0.69-90), p<0.01, >75% Latino: OR: 0.75 (CI: 0.62-0.90), p<0.01) and lower rates of survival (50%-75% Latino: OR: 0.81 (CI: 0.67-0.97), p=0.02, >75% Latino: OR: 0.62 (CI: 0.47-0.81), p<0.01). Conclusion: Individuals in predominantly Latino neighborhoods were less likely to receive B-CPR and had lower likelihood of survival. These findings could inform future messaging around B-CPR educational initiatives targeting largely Latino neighborhoods.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.037
GPT teacher head0.276
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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