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Record W3000857488 · doi:10.1161/circ.140.suppl_2.474

Abstract 474: Higher Mortality From Cardiac Arrest in North Carolina versus Washington State and Denmark: Implications for Improving Systems of Care

2019· article· en· W3000857488 on OpenAlexaff
Sidsel Moeller, Carolina Malta Hansen, Matthew E. Dupre, Tom Rea, Sean van Diepen, Lisa Monk, Clark Tyson, Bryan McNally, Monique A. Starks, Christopher B. Fordyce, Jenny Shin, Fredrik Folke, Christian Torp‐Pedersen, James G. Jollis, Christopher B. Granger

Bibliographic record

VenueCirculation · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of British ColumbiaUniversity of Alberta
Fundersnot available
KeywordsMedicineDefibrillationCardiopulmonary resuscitationDanishEmergency medical servicesCohortLogistic regressionEmergency medicineVentricular fibrillationFirst responderResuscitationDemographyInternal medicine

Abstract

fetched live from OpenAlex

Introduction: Survival from out-of-hospital cardiac arrest (OHCA) remains low and with major regional variation. This study explored differences in patients, care, and survival in patients with OHCA in North Carolina (NC), Washington State (WA), and Denmark. Methods: We identified a total of 17,277 adult patients with OHCA from the Cardiac Arrest Registry to Enhance Survival (CARES) registry and the Danish Cardiac Arrest Register of presumed cardiac cause from 2013-2014. Patients were categorized into three regions: two states in the United States (NC, 9.1 million inhabitants, WA, 7.5 million inhabitants) and the country of Denmark (5.8 million inhabitants). Outcomes of cardiopulmonary resuscitation (CPR) and defibrillation performed by either professional first responder or lay bystanders prior to emergency medical service (EMS) arrival, as well as overall survival. Data were analyzed using multivariable logistic regression analyses adjusted for age, sex, calendar year, location of arrest and witnessed status. Results: Patients in NC and WA were younger and had more racial variation compared to Denmark. Survival was 9.3% in NC, 14.5% in WA and 13.3% in Denmark. Using the Danish cohort as reference, the odds for bystander CPR and defibrillation in NC (CPR: OR 0.41, 95%CI 0.38-0.44; defibrillation: OR 0.30, 95%CI 0.23-0.38) and WA (CPR: OR 0.71, 95%CI 0.65-0.77; defibrillation: OR 0.41, 95%CI 0.31-0.53) were lower, respectively. CPR and defibrillation performed by either a bystander or a professional first responder prior to EMS arrival were higher in NC (CPR: OR 2.67, 95%CI 2.43-2.93; defibrillation: OR 2.72 95%CI 2.30-3.21), but not in WA (CPR: OR 1.01, 95%CI 0.92-1.11; defibrillation OR 0.73, 95%CI 0.58-0.90), respectively. Compared with Denmark, survival was lower in NC (OR 0.39, 95%CI 0.34-0.45) and WA (OR 0.83, 95%CI 0.72-0.95). Conclusion: Survival following OHCA was higher in Denmark and WA than in NC, and was associated with higher rates of bystander CPR and defibrillation. However, CPR and defibrillation prior to EMS arrival, mainly from professional first responders, was significantly higher in NC. A combination of both bystander and first responder interventions may be the optimal approach to improve outcomes of cardiac arrest.

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 score0.247
Threshold uncertainty score0.491

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.284
Teacher spread0.263 · 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
Published2019
Admission routes1
Has abstractyes

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