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Record W3098944129 · doi:10.1161/circ.142.suppl_4.257

Abstract 257: Adherence to the Termination Recommendations in the Universal Termination of Resuscitation Rule and Survival After Out-of-hospital Cardiac Arrest

2020· article· en· W3098944129 on OpenAlexaff
Masashi Okubo, David J. Wallace, Brian Grunau, Mohamud Daya, Clifton W. Callaway

Bibliographic record

VenueCirculation · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicineInterquartile rangeQuartileResuscitationEmergency medical servicesReturn of spontaneous circulationCardiopulmonary resuscitationEmergency medicinePoisson regressionMedical emergencyInternal medicineConfidence intervalPopulation

Abstract

fetched live from OpenAlex

Introduction: Survival after out-of-hospital cardiac arrest (OHCA) varies across emergency medical services (EMS) systems, but the EMS practices that contribute to the outcome variation are unclear. We evaluated the association between EMS agency variation in adherence to the termination recommendations in the Universal Termination of Resuscitation (TOR) rule and survival after OHCA. Methods: We conducted a secondary analysis of the Resuscitation Outcomes Consortium Epistry, a prospective multicenter OHCA registry in North America. We included adults (≥ 18 years) with OHCA for whom EMS providers attempted resuscitation from 2011 through 2015. The main exposure was proportion of patients meeting the Universal TOR rule (not EMS-witnessed arrest, no return of spontaneous circulation prior to transport, and no shock delivery prior to transport) among those who had prehospital TOR at the level of EMS agency. We categorized EMS agencies into quartiles based on the adherence to the Universal TOR rule. Our primary outcome was survival to hospital discharge. We used multilevel modified Poisson regression model, including patient-level and EMS-level covariates with patients nested within EMS agencies. Results: We included 43,656 EMS-treated OHCAs from 112 EMS agencies. The median adherence to the Universal TOR rule was 75.6% (interquartile range [IQR] 67.5-83.7) across EMS agencies. Compared with patients resuscitated at EMS agencies in the quartile of the lowest adherence (median adherence 62.5% [IQR 58.9-65.7]), survival to hospital discharge was inversely associated with treatment at EMS agencies in the second quartile (median adherence 72.6% [IQR 70.2-74.7]) (adjusted risk ratio [aRR] 0.83, 95% confidence interval [CI] 0.71-0.96), the third quartile (median adherence 80.6% [IQR 78.5-81.9]) (aRR 0.71, 95% CI 0.60-0.85), and the fourth quartile (median adherence 90.6% [IQR 86.2-93.7]) (aRR 0.68, 95% CI 0.58-0.80). Conclusions: In this large cohort study of adult patients with OHCA, we observed variation in the adherence to the Universal TOR rule’s termination recommendations across EMS agencies, and an association between higher EMS-level adherence and worse survival to hospital discharge after OHCA.

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)0.004
metaresearch head score (Gemma)0.020
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 score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.023
GPT teacher head0.289
Teacher spread0.266 · 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
Published2020
Admission routes1
Has abstractyes

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