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Record W3081874254 · doi:10.1161/circ.138.suppl_2.316

Abstract 316: Cardiac Arrest Rhythm Transitions in Drug Overdose-Related Resuscitation

2018· article· en· W3081874254 on OpenAlexaboutno aff
Allison C Koller, David D. Salcido, James J. Menegazzi

Bibliographic record

VenueCirculation · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAsystoleRhythmVentricular fibrillationResuscitationPulseless electrical activityInternal medicineCardiopulmonary resuscitationEmergency medical servicesHeart RhythmCardiologyEmergency departmentMedical emergencyEmergency medicine

Abstract

fetched live from OpenAlex

Introduction: The prehospital electrocardiogram (ECG) may inform treatment of out-of-hospital cardiac arrest (OHCA) patients regardless of etiology. While drug overdose (OD)-OHCA is increasingly common, little is known about the characteristics and utility of the intra-resuscitation OD-OHCA ECG signal. In this study, we sought to investigate the evolving ECG rhythm state of OD-OHCA patients to identify potentially informative patterns or phenomena. Methods: Case data, including electronic defibrillator files, for emergency medical services treated OD-OHCA were obtained from the Resuscitation Outcomes Consortium, a multi-site clinical research network in the US and Canada. OD-OHCA case status was previously established by site-level data abstractors reviewing prehospital and in-hospital electronic medical records for evidence of drug involvement. Continuous ECG traces were extracted and chest compression-free ECG segments were parsed with custom MATLAB (vR2017a) software. Each ECG segment was manually rhythm-classified by a research specialist. Rhythm transitions were identified as changes in rhythm between sequential analyzable rhythm segments. Transitions were tabulated and summarized by their rhythms and timing. Results: Complete prehospital ECG data were available for 130 patients, comprising 1,112 ECG segments of which 771 (69.3%) were analyzable. The mean (SD) age was 33.6 (11.3) years and 68.3% were male. The most commonly observed rhythm at the segment level was low amplitude (“fine”) ventricular fibrillation (VF), accounting for 44.1% of all segments, although at the case level asystole was the most common rhythm, present in 47.7% of all cases. We recorded 292 rhythm transitions, with a mean (SD) 2.5 (1.5) transitions per case. Mean (SD) time to first transition was 11.1 (6.9) minutes and mean (SD) time to last transition was 19.8(8.8) minutes. The most frequently observed transition was from asystole to low amplitude ventricular fibrillation (17.1%). Conclusions: The OD-OHCA ECG is varied and dynamic, presenting in numerous rhythms and transitioning between rhythms throughout the course of resuscitation.

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)0.004
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.012
GPT teacher head0.268
Teacher spread0.256 · 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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