Performance of a novel artificial intelligence software developed to derive coronary fractional flow reserve values from diagnostic angiograms.

BACKGROUND: Although invasive measurement of fractional flow reserve (FFR) is recommended to guide revascularization, its routine use is underutilized. Recently, a novel non-invasive software that can instantaneously produce FFR values from the diagnostic angiograms, derived completely from artificial intelligence (AI) algorithms has been developed. We aim to assess the accuracy and diagnostic performance of AI-FFR in a real-world retrospective study. METHODS: Retrospective, three-center study comparing AI-FFR values with invasive pressure wire-derived FFR obtained in patients undergoing routine diagnostic angiography. The accuracy, sensitivity, and specificity of AI-FFR were analyzed. RESULTS: A total of 304 vessels from 297 patients were included. Mean invasive FFR was 0.86 vs. 0.85 AI-FFR (mean difference: -0.005, P  = 0.159). The diagnostic performance of AI-FFR demonstrated sensitivity of 91%, specificity 95%, positive predictive value 83% and negative predictive value 97%. Overall accuracy was 94% and the area under curve was 0.93 (95% CI 0.88-0.97). 105 lesions fell around the cutoff value (FFR = 0.75-0.85); in this sub-group, AI-FFR demonstrated sensitivity of 95%, and specificity 94%, with an AUC of 0.94 (95% CI 88.2-98.0). AI-FFR calculation time was 37.5 ±â€…7.4 s for each angiographic video. In 89% of cases, the software located the target lesion and in 11%, the operator manually marked the target lesion. CONCLUSION: AI-FFR calculated by an AI-based, angio-derived method, demonstrated excellent diagnostic performance against invasive FFR. AI-FFR calculation was fast with high reproducibility.

Aspirin with Low-Dose Ticagrelor or with Low-Dose Rivaroxaban for Secondary Prevention: A Cost per Outcome Analysis.

INTRODUCTION: Secondary prevention of cardiovascular events among patients with diagnosed cardiovascular disease and high ischemic risk poses a significant challenge in clinical practice. The combinations of aspirin with low-dose (LD) ticagrelor or LD rivaroxaban have shown superiority in preventing major adverse cardiovascular events (MACE) compared with aspirin treatment alone. The comparative value for money of these two regimens remains unexplored. METHODS: We analyzed each regimen's annual cost needed to treat (CNT) by multiplying the annualized number needed to treat (aNNT) by the annual cost of each drug. The aNNTs were based on outcome data from PEGASUS TIMI-54 and COMPASS trials. Scenario analyses were performed to overcome variances in terms of population risk. Costs were calculated as 75% of US National Average Drug Acquisition Cost (NADAC), extracted in January 2022. The primary outcome was defined as CNT to prevent one MACE across the two regimens. Secondary value analysis was performed for myocardial infarction (MI), stroke, and cardiovascular death as separate outcomes. RESULTS: The aNNTs to prevent MACE with LD ticagrelor and with LD rivaroxaban were 229 [95% confidence interval (CI) 141-734] and 147 (95% CI 104-252), respectively. At an annual cost of US$3726 versus US$4533, the corresponding CNTs were US$853,254 (95% CI 525,366-2,734,884) with LD ticagrelor and US$666,351 (95% CI 471,432-1,142,316) with LD rivaroxaban. CONCLUSION: Combining aspirin with LD rivaroxaban provides better value for money than with LD ticagrelor for secondary prevention of MACE.

Early Feasibility of Automated Artificial Intelligence Angiography Based Fractional Flow Reserve Estimation.

Despite the evidence of improved patients' outcome, fractional flow reserve (FFR) is underused in current everyday practice. We aimed to evaluate the feasibility of a novel automated artificial intelligence angiography-based FFR software (AutocathFFR) as a decision supporting tool for interventional cardiologists. AutocathFFR was performed on angiographic images of patients who underwent coronary angiography with a pressure wire FFR measurement. Sensitivity and specificity for detection of FFR cut-off of 0.8 were calculated. Thirty-one patients were included in the present study, with a mean age of 64 ± 10 years, 80% were males, 32% patients had diabetes, 39% had previous percutaneous coronary intervention. The left anterior descending artery was the target vessel in 80% of patients. Automatic lesion detection was successful in all of the lesions with FFR value of ≤0.8. The sensitivity of AutocathFFR for predicting a wire based FFR ≤0.8 was 88% and the specificity for FFR >0.8 was 93%, with a positive predictive value of 94% and negative predictive value of 87%, indicating an accuracy level of 90% and area under the curve of 0.91. AutocathFFR has excellent accuracy in prediction of wire based FFR and is a promising technology that may facilitate appropriate decision and treatment choices for coronary artery disease patients.

The impact of lockdown enforcement during the SARSCoV-2 pandemic on the timing of presentation and early outcomes of patients with ST-elevation myocardial infarction.

INTRODUCTION: Early reports described decreased admissions for acute cardiovascular events during the SarsCoV-2 pandemic. We aimed to explore whether the lockdown enforced during the SARSCoV-2 pandemic in Israel impacted the characteristics of presentation, reperfusion times, and early outcomes of ST-elevation myocardial infarction (STEMI) patients. METHODS: A multicenter prospective cohort comprising all STEMI patients treated by primary percutaneous coronary intervention admitted to four high-volume cardiac centers in Israel during lockdown (20/3/2020-30/4/2020). STEMI patients treated during the same period in 2019 served as controls. RESULTS: The study comprised 243 patients, 107 during the lockdown period of 2020 and 136 during the same period in 2019, with no difference in demographics and clinical characteristics. Patients admitted in 2020 had higher admission and peak troponin levels, had a 2.4 fold greater likelihood of Door-to-balloon times> 90 min (95%CI: 1.2-4.9, p = 0.01) and 3.3 fold greater likelihood of pain-to-balloon times> 12 hours (OR 3.3, 95%CI: 1.3-8.1, p<0.01). They experienced higher rates hemodynamic instability (25.2% vs 14.7%, p = 0.04), longer hospital stay (median, IQR [4, 3-6 Vs 5, 4-6, p = 0.03]), and fewer early (<72 hours) discharge (12.4% Vs 32.4%, p<0.001). CONCLUSIONS: The lockdown imposed during the SARSCoV-2 pandemic was associated with a significant lag in the time to reperfusion of STEMI patients. Measures to improves this metric should be implemented during future lockdowns.