MétaCan
Menu
Back to cohort
Record W2063675949 · doi:10.1097/hco.0b013e32834903fc

Stress testing

2011· review· en· W2063675949 on OpenAlexaboutno aff
Todd D. Miller

Bibliographic record

VenueCurrent Opinion in Cardiology · 2011
Typereview
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
FundersAstellas PharmaLantheus Medical Imaging
KeywordsMedicineEjection fractionCoronary artery diseaseCardiologyTreadmillRevascularizationInternal medicineStress testing (software)CADBypass graftingCanadian Cardiovascular SocietyArteryRadiologyHeart failureAnginaMyocardial infarction

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This review examines the diagnostic and prognostic performance of the standard exercise treadmill test (ETT) in comparison to stress imaging procedures. This topic is timely and relevant due to increasing healthcare expenditures and the substantially lower cost of the ETT. RECENT FINDINGS: The most important goal of noninvasive testing is to identify patients with left main or three-vessel coronary artery disease (CAD) or severely reduced left ventricular ejection fraction (LVEF) less than 35%. These patient subsets demonstrate a survival advantage when treated with coronary artery bypass grafting (severe CAD) or a defibrillator (LVEF <35%). This benefit is not present for patients with one-vessel or two-vessel CAD or preserved LVEF. For patients who have a normal resting ECG, studies have shown that the standard ETT is as accurate as imaging for identifying these high-risk patients. Outcome of patients with a low-risk exercise treadmill score is excellent. SUMMARY: The standard ETT should be the initial test in patients presenting for evaluation of CAD with the following characteristics: (1) ability to exercise adequately; (2) normal resting ECG; and (3) no prior revascularization. Applying this strategy should not sacrifice prognostic accuracy and should result in significant cost savings.

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)0.001
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 score0.953
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.265
GPT teacher head0.444
Teacher spread0.178 · 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

Citations19
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in CardiologySame topicCardiac Imaging and DiagnosticsFrench-language works237,207