Prognostic value of negative stress cardiac magnetic resonance imaging in patients with moderate-severe coronary artery stenosis
Bibliographic record
Abstract
Objective This study aims to evaluate the prognostic value of stress cardiac magnetic resonance (CMR) without inducible ischemia in a real-world cohort of patients with known severe coronary artery stenosis. Background The prognosis of patients with severe coronary artery stenosis and without inducible ischemia using stress CMR remains uncertain, even though its identification of functionally significant coronary artery disease (CAD) is excellent. Materials and methods Patients without inducible ischemia and known CAD who underwent stress CMR between February 2015 and December 2016 were included in this retrospective study. These patients were divided into two groups: group 1 with stenosis of 50%–75% and group 2 with stenosis of >75%. The primary endpoint was defined as the occurrence of a major adverse cardiovascular event (MACE) [cardiac death, non-fatal myocardial infarction (MI), percutaneous coronary intervention (PCI), or coronary artery bypass grafting (CABG)]. Results Real-world data collected from 169 patients with a median age of 69 (60–75) years were included. The median follow-up was 5.5 (IQR 4.1–6.6) years. Events occurred after a mean time of 3.0 ± 2.2 years in group 1 and 3.7 ± 2.0 years in group 2 (p = 0.35). Sixteen (18.8%) patients in group 1 and 23 (27.4%) patients in group 2 suffered from MACE without a significant difference between the two groups (p = 0.33). In group 2, one cardiac death (1.2%), seven non-fatal MI (8.3%), 15 PCI (17.9%), and one CABG (1.2%) occurred. Conclusion The findings of this pilot study suggest that long-term outcomes in a real-world patient cohort with known severe and moderate coronary artery stenosis but without inducible ischemia were similar. Stress CMR may provide valuable risk stratification in patients with angiographically significant but hemodynamically non-obstructive coronary lesions.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".