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Record W2765419058 · doi:10.1136/emermed-2017-206878

Utility of prehospital electrocardiogram characteristics as prognostic markers in out-of-hospital pulseless electrical activity arrests

2017· article· en· W2765419058 on OpenAlexafffundabout
Michael L. Ho, Mathieu Gatien, Christian Vaillancourt, Veronica Whitham, Ian G. Stiell

Bibliographic record

VenueEmergency Medicine Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersChina Academy of Engineering PhysicsCanadian Association of Emergency Physicians
KeywordsMedicinePulseless electrical activityInternal medicineCardiologyElectrocardiographyEmergency medicineMedical emergencyCardiopulmonary resuscitationResuscitation

Abstract

fetched live from OpenAlex

BACKGROUND: It is unclear if there are predictors of survival, including ECG characteristics, that can guide resuscitative efforts in pulseless electrical activity (PEA) cardiac arrests. We studied the predictive potential of presenting prehospital ECGs on survival for patients with out-of-hospital cardiac arrest (OHCA) with PEA. METHODS: We studied prehospital ECGs of patients with OHCA prospectively enrolled between June 2007 and November 2009 at the Ottawa/OPALS (Ontario Prehospital Advanced Life Support Study) site of the Resuscitation Outcomes Consortium PRIMED study (Prehospital Resuscitation using an IMpedance valve and Early versus Delayed analysis). We included adult non-traumatic OHCA with PEA rhythm where resuscitation was attempted. We measured HR, QRS interval and presence of P waves, and determined their impact on return of spontaneous circulation (ROSC) and survival to hospital discharge (SHD) using multivariate regression analysis. RESULTS: The demographic characteristics of the 332 included cases were the following: mean age 71.8, male 58.4%, SHD 5.4% and ROSC at ED arrival 26.5%. Survivors had similar HR (56.8 vs 52.0 beats per minute (bpm), p=0.53) and QRS intervals (128.7 vs 129.6 ms, p=0.95) compared with non-survivors. Prehospital ECG characteristics did not predict SHD or ROSC on multivariate analyses. Patients with initial HR <30 bpm had a 3.8% survival rate; those with both HR <30 bpm and QRS≥120 ms had a 3.7% survival rate. Location of arrest predicted SHD (adjusted OR (AdjOR)=1.49, 1.11 to 1.99; p=0.007). Atropine use negatively predicted SHD (AdjOR=0.06, 0.02 to 0.22; p<0.001). Predictors of ROSC ALS paramedic on scene (AdjOR=8.90, 1.11 to 71.41; p=0.04) and successful intubation (AdjOR=3.35, 1.75 to 6.39; p<0.001). Atropine use negatively predicted ROSC (AdjOR=0.27, 0.14 to 0.50; p<0.001). CONCLUSIONS: Presenting prehospital ECG characteristics did not predict SHD or ROSC in OHCA PEA victims and should not be used to guide termination of resuscitation. Location of arrest was a positive predictor for SHD; atropine use was a negative predictor. ALS paramedic on scene and successful intubation were positive predictors of ROSC; atropine use was a negative predictor. TRIAL REGISTRATION NUMBER: NCT00394706; post-results.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.018
GPT teacher head0.330
Teacher spread0.311 · 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

Citations11
Published2017
Admission routes3
Has abstractyes

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