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Record W1600414609 · doi:10.1111/anec.12278

The Value of Electrocardiographic Abnormalities in the Prognosis of Pulmonary Embolism: A Consensus Paper

2015· review· en· W1600414609 on OpenAlexaff
Geneviève C. Digby, Piotr Kukla, Zhong‐Qun Zhan, Carlos Alberto Pastore, Ryszard Piotrowicz, Edgardo Schapachnik, Wojciech Zaręba, Antoni Bayés de Luna, Piotr Pruszczyk, Adrián Baranchuk

Bibliographic record

VenueAnnals of Noninvasive Electrocardiology · 2015
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsKingston General HospitalQueen's University
Fundersnot available
KeywordsMedicinePulmonary embolismObservational studyInternal medicineCardiologyAutopsyElectrocardiographyMEDLINEIntensive care medicine

Abstract

fetched live from OpenAlex

Electrocardiographic (ECG) abnormalities in the setting of acute pulmonary embolism (PE) are being increasingly characterized and mounting evidence suggests that ECG plays a valuable role in prognostication for PE. We review the historical 21-point ECG prognostic score for the severity of PE and examine the updated evidence surrounding the utility of ECG abnormalities in prognostication for severity of acute PE. We performed a literature search of MEDLINE, EMBASE, and PubMed up to February 2015. Article titles and abstracts were screened, and articles were included if they were observational studies that used a surface 12-lead ECG as the instrument for measurement, a diagnosis of PE was confirmed by imaging, arteriography or autopsy, and analysis of prognostic outcomes was performed. Thirty-six articles met our inclusion criteria. We review the prognostic value of ECG abnormalities included in the 21-point ECG score, including new evidence that has arisen since the time of its publication. We also discuss the potential prognostic value of several ECG abnormalities with newly identified prognostic value in the setting of acute PE.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.072
GPT teacher head0.360
Teacher spread0.287 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations70
Published2015
Admission routes1
Has abstractyes

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