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Record W3128516208 · doi:10.1016/j.cjco.2020.12.028

Patterns of Left-Ventricular Function Assessment in Patients With Acute Coronary Syndromes

2021· article· en· W3128516208 on OpenAlexafffund
Daniel Malebranche, Sarah Hasan, Marinda Fung, Bryan Har, Patrick Champagne, Gregory Schnell, Stephen B. Wilton, Todd J. Anderson

Bibliographic record

VenueCJC Open · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
FundersUniversity of CalgaryAlberta Health Services
KeywordsEjection fractionMedicineCardiologyAcute coronary syndromeInternal medicineCohortCardiac catheterizationVentricular functionHeart failureMyocardial infarction

Abstract

fetched live from OpenAlex

BACKGROUND: In patients with acute coronary syndromes (ACS), guidelines recommend the assessment of left-ventricular ejection fraction (LVEF). Many patients with ACS undergo multiple assessments of LVEF, the clinical value of which is unknown. METHODS: Patients with ACS undergoing cardiac catheterization between 2012 and 2016 were evaluated and assessments of LV function identified. To evaluate changes in LVEF over time, available echocardiograms were reviewed in a subsample of patients with LVEF data available (n = 3221). Patients with ACS were classified into 3 groups: group 1 (LVEF > 50%), group 2 (LVEF 35% to 50%), and group 3 (LVEF < 35%). RESULTS: Our cohort consisted of 8327 patients with ACS (76% men), presenting with a mean age of 62.4 ± 12.4 years. At index presentation, 66% of patients had an LVEF > 50%, 27% had an LVEF between 35% and 50%, and 7% had severely reduced LVEF of < 35%. More than half of the cohort (n = 4600) had follow-up assessment of LV function, performed over an average of 2.71 ± 1.31 years. In the subsample of 3221 patients, only 1.1% of those in group 1, and 5.1% of those in group 2, deteriorated to an LVEF < 35%. CONCLUSIONS: Patients with ACS often undergo multiple assessments of LV function. Those with initially preserved EF rarely demonstrate a decline in EF to < 35%. A reduction in low-value cardiac tests may be an important first step in improving the quality of care for patients with ACS.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.330
Teacher spread0.308 · 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

Citations10
Published2021
Admission routes2
Has abstractyes

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