The Prevalence of Clinically Significant Ischemia in Patients Undergoing Percutaneous Coronary Intervention: A Report from the Multicenter Registry
Bibliographic record
Abstract
BACKGROUND: Myocardial perfusion scintigraphy (MPS) plays an important role in the evaluation and quantification of myocardial ischemia, and those with significant ischemia (SI) benefit most from revascularization procedures. This study aimed to identify the clinical factors and anatomical features associated with SI in patients with stable ischemic heart disease (SIHD). METHODS AND RESULTS: Data were analyzed from 4197 SIHD patients undergoing percutaneous coronary intervention (PCI). Ischemia was based on MPS findings prior to PCI, with SI defined as an ischemic region of more than 10% of the total left ventricular area. Logistic regression analysis was performed to identify any clinical factors associated with SI. MPS was used to evaluate 1070 (25.5%) patients pre-procedurally. Patients with a history of heart failure, stroke, or anginal symptoms with Canadian Cardiovascular Society class 2 or more were more likely to have SI (odds ratio [OR] 1.63, p = 0.025, OR: 1.85, p = 0.009, and OR: 1.49, p = 0.003, respectively). When angiographic variables were considered, a proximal left anterior descending artery (pLAD) lesion was the sole factor associated with SI (OR: 1.45, p = 0.012). Importantly, those with SI had more in-hospital complications (p = 0.006), most notably post-PCI infarcts (p = 0.008). CONCLUSIONS: Patients' background data, such as stronger anginal symptoms or a pLAD lesion, were associated with SI. Patients with SI must be treated with PCI to improve their long-term prognosis; however, procedure-related complications happen more frequently in SI patients than in non-SI patients. Physicians must give their full attention when performing the PCI procedure in SI patients to minimize their complication rate.
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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 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.001 | 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".