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A macroscopic electrocardiographic diagnosis of hypertrophic cardiomyopathy: a comparison between the Italian and European guidelines

2023· article· en· W4319987569 on OpenAlexaff
Elio ASSISI, Christine MUR, Simone GROSSGASTEIGER, Elettra LIBENER, Stefan RESNYAK

Bibliographic record

VenueGazzetta Medica Italiana Archivio per le Scienze Mediche · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsProvincial Health Services Authority
Fundersnot available
KeywordsHypertrophic cardiomyopathyMedicineCardiologyVentricleInternal medicineElectrocardiographyMagnetic resonance imagingCompetitive athletesRadiologyAthletesPhysical therapy

Abstract

fetched live from OpenAlex

The presence of deep and diffuse negative T waves in the lateral leads should evoke the suspect of hypertrophic cardiomyopathy, whose diagnosis occurs through echocardiography. In this article we want to consider the comparison between the COCIS Italian Guidelines (Cardiological Committee for eligibility to competitive sport) of 2009 and 2017, and the European ESC Guidelines (European Society of Cardiology) regarding the judgment of suitability for competitive sports. The echocardiographic finding of a hypertrophic left ventricle characterized by an interventricular septum of 22 mm, posterior wall of 13 mm, and a reduced size of the ventricular cavity to 51 mm, confirms the initial electrocardiography suspicion. The aim of our article was to compare the COCIS and ESC Guidelines on the subject with hypertrophic cardiomyopathy whose diagnosis, which is evident on an electrocardiographic level, needs an ultrasound confirmation without the need for additional imaging tests such as magnetic resonance. The question arises whether our sportsman can practice sports at a competitive level and, possibly, what type of activity.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.035
GPT teacher head0.308
Teacher spread0.273 · 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 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
Published2023
Admission routes1
Has abstractyes

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