Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
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The New England journal of medicine
Intravascular Ultrasound-Guided or Angiography-Guided Complex High-Risk PCI
BACKGROUND: Intravascular ultrasound (IVUS) guidance during percutaneous coronary intervention (PCI) has been associated with increased stent optimization and reduced adverse events among patients with complex coronary-artery lesions, but adoption of this strategy in Western countries remains low. Although practice guidelines recommend intracoronary imaging for anatomically complex lesions, evidence from current European practice is limited. METHODS: In this investigator-initiated, international, open-label, randomized, controlled trial, we assigned patients undergoing complex PCI to either IVUS-guided PCI, performed with the use of prespecified stent-optimization criteria, or angiography-guided PCI. The primary end point was target-vessel failure, defined as a composite of death from cardiac causes, target-vessel myocardial infarction, or clinically indicated target-vessel revascularization. RESULTS: Of the 2020 patients who underwent randomization, 1010 in the IVUS-guided PCI group and 1009 in the angiography-guided PCI group were included in the primary analysis. The mean age of the patients was 69 years, 79.4% were men, and 27.4% presented with an acute coronary syndrome. The mean procedure duration was 88.8 minutes with IVUS-guided PCI and 66.2 minutes with angiography-guided PCI. Dilation with balloon angioplasty after stent implantation was performed in 91.3% of the IVUS-guided PCI procedures and in 84.5% of the angiography-guided PCI procedures. At a median follow-up of 19.0 months (interquartile range, 15.2 to 23.4), target-vessel failure had occurred in 140 patients (13.9%) in the IVUS-guided PCI group and in 112 patients (11.1%) in the angiography-guided PCI group (hazard ratio, 1.25; 95% confidence interval, 0.97 to 1.60; P = 0.08). Procedural complications occurred in 11.3% of the IVUS-guided PCI procedures and in 10.2% of the angiography-guided PCI procedures. The frequency of adverse events appeared to be similar in the two groups. CONCLUSIONS: Among patients undergoing complex high-risk PCI, a strategy of routine IVUS-guided PCI performed with the use of prespecified stent-optimization criteria was not associated with a lower risk of target-vessel failure than angiography-guided PCI alone. (Funded by Boston Scientific; IVUS-CHIP ClinicalTrials.gov number, NCT04854070.).
13 June 2026
Read appraisal →EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
Quantitative flow ratio versus fractional flow reserve: 2-year follow-up of the FAVOR III Europe trial
BACKGROUND: Quantitative flow ratio (QFR) is an angiography-based method for estimating fractional flow reserve (FFR). The FAVOR III Europe trial showed that QFR guidance did not meet non-inferiority to FFR guidance, as measured by a composite endpoint of all-cause death, myocardial infarction, and unplanned revascularisation at 12 months. AIMS: We sought to report the 2-year outcomes of the QFR-guided diagnostic strategy and the FFR-guided strategy as applied in the FAVOR III Europe trial. METHODS: FAVOR III Europe was a multicentre, randomised, open-label, non-inferiority trial. A total of 2,000 patients from 34 European medical centres were randomised to undergo QFR- or FFR-guided revascularisation of intermediate coronary artery stenoses. Endpoints assessed at the 2-year follow-up included the rates of major adverse cardiac events (MACE) and its individual components of all-cause death, myocardial infarction, and unplanned revascularisation. The rates of MACE were compared for superiority by unadjusted Cox regression analysis. The outcomes from 1 to 2 years were explored in a landmark analysis. RESULTS: At 2 years, the rates of MACE were 9.7% in the QFR group and 7.4% in the FFR group (hazard ratio [HR] 1.34, 95% confidence interval [CI]: 0.98-1.81; p=0.064). In the landmark analysis, the rates of MACE between 1 and 2 years were 3.2% in the QFR group and 3.2% in the FFR group (HR 0.97, 95% CI: 0.58-1.62; p=0.92). CONCLUSIONS: The excess risks associated with QFR-guided revascularisation compared with FFR were confined to the first year. From 1 to 2 years, the rates of MACE developed similarly in the QFR and the FFR groups.
10 May 2026
Read appraisal →International journal of cardiology
Predicting functional results of percutaneous coronary intervention using machine learning modelling
BACKGROUND: Post-percutaneous coronary intervention (PCI) Murray's law-based quantitative flow ratio (μFR) is associated with long-term clinical outcomes. A tool capable of accurately predicting post-PCI μFR before intervention could support procedural planning, reduce the risk of suboptimal physiological results, and improve prognosis. OBJECTIVES: To develop and validate machine-learning models that predict continuous post-PCI μFR using only pre-procedural angiographic, physiological and clinical data, and to assess their ability to classify PCI outcomes as optimal (μFR ≥ 0.91) or sub-optimal (μFR < 0.91). METHODS: Four machine learning models were trained using pre-PCI variables. Internal bootstrap validation (1000 iterations) identified the best-performing model based on lowest root mean square error (RMSE) for continuous prediction. Predicted μFR values were subsequently used to classify PCI outcomes. RESULTS: In 343 vessels (291 patients), machine learning achieved high accuracy for continuous post-PCI μFR prediction (RMSE 0.036; 95% CI: 0.033-0.040; mean absolute error 0.030; 95% CI: 0.027-0.032; mean absolute percentage error 3.2%; 95% CI: 2.9-3.5), indicating reliable estimation of post-PCI μFR using only pre-procedural data. When the predicted μFR was used to classify PCI outcomes, performance remained clinically meaningful, with accuracy 0.72 (95% CI: 0.70-0.75), area under the curve 0.72 (95% CI: 0.69-0.74), sensitivity 0.90 (95% CI: 0.88-0.93), and specificity 0.29 (95% CI: 0.23-0.34). The high sensitivity ensures reliable upfront identification of vessels likely to achieve optimal physiology. CONCLUSIONS: Machine-learning models accurately predict post-PCI μFR and reliably distinguish optimal from sub-optimal outcomes before intervention. This approach supports personalized PCI planning and improves strategy selection.
17 Apr 2026
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