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Record W1580015052 · doi:10.1111/anec.12194

Prinzmetal Angina: ECG Changes and Clinical Considerations: A Consensus Paper

2014· review· en· W1580015052 on OpenAlexaff
Antoni Bayés de Luna, Iwona Cygankiewicz, Adrián Baranchuk, Miquel Fiol, Yochai Birnbaum, Kjell Nikus, Diego Goldwasser, Javier García‐Niebla, Samuel Sclarovsky, Hein J.J. Wellens, Günter Breithardt

Bibliographic record

VenueAnnals of Noninvasive Electrocardiology · 2014
Typereview
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsKingston General HospitalQueen's University
Fundersnot available
KeywordsMedicineAnginaCardiologyInternal medicineIntensive care medicineMyocardial infarction

Abstract

fetched live from OpenAlex

BACKGROUND: We will focus our attention in this article in the ECG changes of classical Prinzmetal angina that occur during occlusive proximal coronary spasm usually in patients with normal or noncritical coronary stenosis. RESULTS: The most important ECG change during a focal proximal coronary spasm is in around 50% of cases the appearance of peaked and symmetrical T wave that is followed, if the spasm persist, by progressive ST-segment elevation that last for a few minutes, and later progressively resolve. The most frequent ECG changes associated with ST-segment elevation are: (a) increased height of the R wave, (b) coincident S-wave diminution, (c) upsloping TQ in many cases, and (d) alternans of the elevated ST-segment and negative T wave deepness in 20% of cases. The presence of arrhythmias is very frequent during Prinzmetal angina crises, especially ventricular arrhythmias. The prevalence and importance of ventricular arrhythmias were related to: (a) duration of episodes, (b) degree of ST-segment elevation, (c) presence of ST-T wave alternans, and (d) the presence of >25% increase of the R wave. CONCLUSIONS: The incidence of Prinzmetal angina is much lower then 50 years ago for many reasons including treatment with calcium channel blocks to treat hypertension and ischemia heart disease and the decrease of smoking habits.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.113
GPT teacher head0.420
Teacher spread0.307 · 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

Citations38
Published2014
Admission routes1
Has abstractyes

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