Clinical outcomes of patients with diffuse coronary artery disease following physiology-guided treatment strategy: insights from AJIP registry
Bibliographic record
Abstract
Abstract Background Physiology-guided treatment strategy improves clinical outcomes of patients with coronary artery disease. However, it has not been fully evaluated whether such guideline-based strategy is useful for patients with diffuse coronary artery disease as well, which is known to be one of the major factors affecting morbidity and mortality. Purpose The aim of this study was to clarify clinical outcomes of patients with diffuse coronary artery disease whose treatment strategy was based on coronary physiology. Methods From an international multicentre registry of iFR-pullback, consecutive 1067 patients (1185 vessels) with stable angina were included in whom coronary lesions were deferred or revascularized according to the iFR cutoff: 0.89. The physiological pattern of disease was classified according to the iFR-pullback recording as predominantly physiologically diffuse (n=463) or predominantly physiologically focal (n=722). Major adverse cardiovascular events (MACEs), defined as a composite of cardiac death, non-fatal myocardial infarction, and ischemia-driven target lesion revascularization during follow-up period, were compared between diffuse and focal groups, in both deferred and revascularized groups, respectively. Results Mean age was 67.1±10.7 years and 75.8% of patients were men. Median iFR was 0.88 (interquartile range: 0.80 to 0.92). At a median follow-up period of 18 months, no significant differences in MACEs were found between diffuse and focal groups, in both iFR-based deferred and revascularized groups. In the deferred group (n=480), MACEs occurred in 6.9% patients (15/217) in the diffuse group and 8.0% patients (21/263) in the focal group (p=0.44). In the revascularized group (n=705), MACEs occurred in 8.9% patients (22/246) in the diffuse group and 7.2% patients (33/459) in the focal group (p=0.49). Conclusions Despite potentially higher risks in patients with diffuse coronary artery disease, clinical outcomes of those patients were comparable to those of patients without diffuse disease, as long as treatment strategy was based on the physiology guidance, which is globally recommended by international guidelines. Funding Acknowledgement Type of funding source: None
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".