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Record W2554032239 · doi:10.1097/jcn.0000000000000380

The Value of Detecting Asymptomatic Signs of Myocardial Ischemia in Patients With Coronary Artery Disease in Outpatient Cardiac Rehabilitation

2016· article· en· W2554032239 on OpenAlexaff
Patricia Lounsbury, Ahmed Elokda, Jennifer M. Bunning, Ross Arena, Ellen Gordon

Bibliographic record

VenueThe Journal of Cardiovascular Nursing · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsVancouver Coastal Health
Fundersnot available
KeywordsMedicineAsymptomaticCardiologyCoronary artery diseaseInternal medicineMyocardial ischemiaRehabilitationDiseaseIschemiaPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Electrocardiographic (ECG) monitored outpatient cardiac rehabilitation (OP-CR) is routinely performed following a variety of cardiovascular procedures and conditions. OBJECTIVE: The aim of this study is to determine if diagnostic-quality ECG monitoring in patients with coronary artery disease (CAD) during OP-CR is useful in identifying asymptomatic myocardial ischemia, resulting in change(s) in care or medical management. METHODS: A retrospective analysis of ECG monitoring was done on all OP-CR patients diagnosed with CAD (n = 1213) from January 2000 through June 2013. RESULTS: Nearly a quarter of the patients (24%; n = 288) displayed at least 1 mm of asymptomatic ST-segment depression at 80 milliseconds after the J-point during at least 1 session of OP-CR. Of these patients, 57% had medical management change(s) compared with 24% for those who did not show ECG changes suggesting ischemia (P < .0001). In patients with asymptomatic ischemia having medical management change(s), 84% resulted directly from OP-CR staff detection. Fewer patients diagnosed with myocardial infarction and coronary artery bypass graft surgery demonstrated ECG signs of ischemia, whereas more patients diagnosed with stable angina and percutaneous coronary interventions demonstrated ECG signs of ischemia. CONCLUSION: This study demonstrates that most patients with CAD showing asymptomatic ECG signs suggesting ischemia undergo medical management change(s) as a result of the finding. Diagnostic-quality ECG monitoring during OP-CR appears warranted in this population.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0000.000

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 head0.006
GPT teacher head0.249
Teacher spread0.243 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2016
Admission routes1
Has abstractyes

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