Rationale and Design of the CREDENCE Trial: computed TomogRaphic evaluation of atherosclerotic DEtermiNants of myocardial IsChEmia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Coronary computed tomography angiography (CCTA) allows for non-invasive assessment of obstructive coronary artery disease (CAD) beyond measures of stenosis severity alone. This assessment includes atherosclerotic plaque characteristics (APCs) and calculation of fractional flow reserve (FFR) from CCTA (FFRCT). Similarly, stress imaging by myocardial perfusion scintigraphy (MPS) provides vital information. To date, the diagnostic performance of integrated CCTA assessment versus integrated MPS assessment for diagnosis of vessel-specific ischemia remains underexplored. CREDENCE will enroll adult individuals with symptoms suspicious of CAD referred for non-emergent invasive coronary angiography (ICA), but without known CAD. All participants will undergo CCTA, MPS, ICA and FFR. FFR will be performed for lesions identified at the time of ICA to be ≥40 and <90 % stenosis, or those clinically indicated for evaluation. Study analyses will focus on diagnostic performance of CCTA versus MPS against invasive FFR reference standard. An integrated stenosis-APC-FFRCT metric by CCTA for vessel-specific ischemia will be developed from derivation cohort and tested against a validation cohort. Similarly, integrated metric by MPS for vessel-specific ischemia will be developed, validated and compared. An FFR value of ≤0.80 will be considered as ischemia causing. The primary endpoint will be the diagnostic accuracy of vessel territory-specific ischemia of integrated stenosis-APC-FFRCT measure by CCTA, compared with perfusion or perfusion–myocardial blood flow stress imaging testing, against invasive FFR. CREDENCE will determine the performance of integrated CCTA metric compared to integrated MPS measure for diagnosis of vessel-specific ischemia. If proven successful, this study may reduce the number of missed diagnoses and help to optimally predict ischemia-causing lesions. ClinicalTrials.gov, NCT02173275 . Registered on June 23, 2014.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it