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Record W4224280058 · doi:10.24908/pocus.v7i1.15296

The Takotsubo Syndrome: Clinical Diagnosis Using POCUS

2022· article· en· W4224280058 on OpenAlexvenueno aff
Josu López Libano, Lorenzo Alomar Lladó, Leire Zarraga López

Bibliographic record

VenuePOCUS Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicTakotsubo Cardiomyopathy and Associated Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiologyInternal medicineAcute coronary syndromeCoronary angiographyCardiomyopathyCoronary arteriesTakotsubo syndromeMyocardial ischemiaAngiographyIschemiaArteryMyocardial infarctionHeart failure

Abstract

fetched live from OpenAlex

Takotsubo syndrome is a cardiomyopathy that can mimic an acute heart attack, in terms of clinical presentation, electrocardiographic changes, and findings on echocardiogram. Point-of-care-ultrasound (POCUS) can be used to detect this condition, even though the definitive diagnosis is made angiographically. We present the case of an 84-year-old woman with a subacute coronary syndrome and high levels of myocardial ischemia markers. The POCUS performed on admission showed characteristic left ventricular dysfunction involving the apex but sparing the base. The coronary angiography ruled out significant arteriosclerotic in the coronary arteries. The wall motion abnormalities were partially corrected in the 48 hours after admission. POCUS might be a useful tool to establish an early diagnosis of Takotsubo syndrome at time of admission.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.051
GPT teacher head0.342
Teacher spread0.291 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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