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Record W2752904056 · doi:10.1001/jamacardio.2017.2671

Association of Neighborhood Demographics With Out-of-Hospital Cardiac Arrest Treatment and Outcomes

2017· article· en· W2752904056 on OpenAlexafffund
Monique A. Starks, Robert H. Schmicker, Eric D. Peterson, Susanne May, Jason E. Buick, Peter J. Kudenchuk, Ian R. Drennan, Heather Herren, Jamie Jasti, Michael R. Sayre, Dion Stub, Gary M. Vilke, Shannon W. Stephens, Anna Marie Chang, Jack Nuttall, Graham Nichol

Bibliographic record

VenueJAMA Cardiology · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicineInterquartile rangeCardiopulmonary resuscitationEmergency medicineRetrospective cohort studyResuscitationReturn of spontaneous circulationEmergency medical servicesLogistic regressionSudden cardiac arrestDefibrillationCohortEmergency departmentInternal medicine

Abstract

fetched live from OpenAlex

Importance: We examined whether resuscitation care and outcomes vary by the racial composition of the neighborhood where out-of-hospital cardiac arrests (OHCAs) occur. Objective: To evaluate the association between bystander treatments (cardiopulmonary resuscitation and automatic external defibrillation) and timing of emergency medical services personnel on OHCA outcomes according to the racial composition of the neighborhood where the OHCA event occurred. Design, Setting, and Participants: This retrospective observational cohort study examined patients with OHCA from January 1, 2008, to December 31, 2011, using data from the Resuscitation Outcomes Consortium. Neighborhoods where OHCA occurred were classified by census tract, based on percentage of black residents: less than 25%, 25% to 50%, 51% to 75%, or more than 75%. Multilevel mixed-effects logistic regression modeling examined the association between racial composition of neighborhoods and OHCA survival, adjusting for patient, neighborhood, and treatment characteristics. Main Outcomes and Measures: Survival to discharge, return of spontaneous circulation on emergency department arrival, and favorable neurologic status at discharge. Results: We examined 22 816 adult patients with nontraumatic OHCA at Resuscitation Outcomes Consortium sites in the United States. The median age of patients with OHCA was 64 years (interquartile range [IQR], 51-78). Compared with patients who experienced OHCA in neighborhoods with a lower proportion of black residents, those in neighborhoods with more than 75% black residents were slightly younger, were more frequently women, had lower rates of initial shockable rhythm, and less frequently experienced OHCA in a public location. The percentage of patients with OHCA receiving bystander cardiopulmonary resuscitation or a lay automatic external defibrillation was inversely associated with the percentage of black residents in neighborhoods. Compared with OHCA in predominantly white neighborhoods (<25% black), those with OHCA in mixed to majority black neighborhoods had lower adjusted survival rates to hospital discharge (25%-50% black: odds ratio, 0.76; 95% CI, 0.61-0.93; 51%-75% black: odds ratio, 0.67; 95% CI, 0.49-0.90; >75% black: odds ratio, 0.63; 95% CI, 0.50-0.79; P < .001). There was similar mortality risk for black and white patients with OHCA in each neighborhood racial quantile. When the primary model included geographic site, there was an attenuated nonsignificant association between racial composition in a neighborhood and survival. Conclusions and Relevance: Those with OHCA in predominantly black neighborhoods had the lowest rates of bystander cardiopulmonary resuscitation and automatic external defibrillation use and significantly lower likelihood for survival compared with predominantly white neighborhoods. Improving bystander treatments in these neighborhoods may improve cardiac arrest survival.

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)0.003
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 score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.269
Teacher spread0.259 · 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

Citations118
Published2017
Admission routes2
Has abstractyes

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