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Record W2046893450 · doi:10.3109/10903127.2011.614045

Serial Prehospital 12-Lead Electrocardiograms Increase Identification of ST-segment Elevation Myocardial Infarction

2011· article· en· W2046893450 on OpenAlexaff
P. Richard Verbeek, Damien Ryan, Linda Turner, Alan Craig

Bibliographic record

VenuePrehospital Emergency Care · 2011
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsUniversity of TorontoSunnybrook Health Science CentreSt. Michael's Hospital
Fundersnot available
KeywordsMedicineMyocardial infarctionCardiologyInternal medicineST segmentElevation (ballistics)ElectrocardiographyLead (geology)Myocardial infarction diagnosisEmergency medicineMedical emergency

Abstract

fetched live from OpenAlex

BACKGROUND: Many prehospital protocols require acquisition of a single 12-lead electrocardiogram (ECG) when assessing a patient for ST-segment elevation myocardial infarction (STEMI). However, it is known that ECG evidence of STEMI can evolve over time. OBJECTIVES: To determine how often the first and, if necessary, second or third prehospital ECGs identified STEMI, and the time intervals associated with acquiring these ECGs and arrival at the emergency department (ED). METHODS: We retrospectively analyzed 325 consecutive prehospital STEMIs identified between June 2008 and May 2009 in a large third-service emergency medical services (EMS) system. If the first ECG did not identify STEMI, protocol required a second ECG just before transport and, if necessary, a third ECG before entering the receiving ED. Paramedics who identified STEMI at any time bypassed participating local EDs, taking patients directly to the percutaneous coronary intervention (PCI) center. Paramedics used computerized ECG interpretation with STEMI diagnosis defined as an "acute MI" report by GE/Marquette 12-SL software in ZOLL E-series defibrillator/cardiac monitors (ZOLL Medical, Chelmsford, MA). We recorded the time of each ECG, and the ordinal number of the diagnostic ECG. We then determined the number of cases and frequency of STEMI diagnosis on the first, second, or third ECG. We also measured the interval between ECGs and the interval from the initial positive ECG to arrival at the ED. Results. STEMI was identified on the first prehospital ECG in 275 cases, on the second ECG in 30 cases, and on the third ECG in 20 cases (cumulative percentages of 84.6%, 93.8%, and 100%, respectively). For STEMIs identified on the second or third ECG, 90% were identified within 25 minutes after the first ECG. The median times from identification of STEMI to arrival at the ED were 17.5 minutes, 11.0 minutes, and 0.7 minutes for STEMIs identified on the first, second, and third ECGs, respectively. CONCLUSIONS: A single prehospital ECG would have identified only 84.6% of STEMI patients. This suggests caution using a single prehospital ECG to rule out STEMI. Three serial ECGs acquired over 25 minutes is feasible and may be valuable in maximizing prehospital diagnostic yield, particularly where emergent access to PCI exists.

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)0.000
metaresearch head score (Gemma)0.005
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
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 science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.279
Teacher spread0.258 · 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

Citations30
Published2011
Admission routes1
Has abstractyes

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