Comparing treatment outcomes of fractional flow reserve-guided and angiography-guided percutaneous coronary intervention in patients with multi-vessel coronary artery diseases: a systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: Fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) is used to assess the need for angioplasty in vessels with intermediate blockages. The treatment outcomes of FFR-guided vs. conventional angiography-guided PCI were evaluated in patients with multi-vessel coronary artery disease (CAD). METHODS: Prospective and retrospective studies comparing FFR-guided vs. angiography-guided PCI in patients with multi-vessel CAD were identified from medical databases by two independent reviewers using the terms "percutaneous coronary intervention, fractional flow reserve, angiography, coronary heart disease, major adverse cardiac events (MACE) and myocardial infarction". The primary outcome was the number of stents placed, and the secondary outcomes were procedure time, mortality, myocardial infarction (MI) and MACE rates. RESULTS: Seven studies (three retrospective and four prospective), which included 49,517 patients, were included in this review. A total of 4,755 patients underwent FFR, while 44,697 received angiography-guided PCI. The mean patient age ranged from 58 to 71.7 years. The average number of stents used in FFR patients ranged from 0.3-1.9, and in angiography-guided PCI patients ranged from 0.7-2.7. Analysis indicated there was a greater number of stents placed in the angiography-guided group compared with the FFR group (pooled difference in means: -0.64, 95% confidence interval [CI]: -0.81 to -0.47, P < 0.001). There were no differences in the secondary outcomes between the two groups. CONCLUSIONS: Both procedures produce similar clinical outcomes, but the fewer number of stents used with FFR may have clinical as was as cost implications.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.027 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".