Suppah, Mustafa

Abstract Introduction Drug-coated balloons (DCBs) have reduced restenosis and reintervention of femoropopliteal lesions compared to uncoated percutaneous transluminal angioplasty (PTA). However, limited data are available on different dosages of the DCBs. Purpose We aimed to give a comprehensive analysis in this regard and update the current evidence. Methods We searched Scopus, Cochrane, PubMed, and WOS from inception till February 2024 to include all randomized controlled trials (RCTs) that addressed different dosages of DCBs in femoropopliteal lesions. The primary endpoint was all-cause death, primary patency, and amputation at six months, while the secondary outcomes were all-cause death, primary patency, and amputation at 12 months. Dichotomous data were pooled using Odds Ratio (OR) and 95% Confidence Interval (CI) in a random-effect model. Results A total of 21 studies, including 4081 patients in the analysis. Low-dose DCB was associated with high rates of primary patency compared to the standard dose at both 6 and 12 months of follow-up with the following values (OR: 2.46, 95% CI: 1.48 to 4.08, and 1.93, 95% CI: 1.5 to 2.49, receptively). Also, low-dose DCB reduced the incidence of clinically driven target lesion revascularization (CD-TLR) compared to the standard dose at 12 months (OR: 0.45, 95% CI: 0.31 to 0.65). Regarding high-dose DCB, higher primary patency rates were observed when compared to standard doses at 6 and 12 months (OR: 1.89, 95% CI: 1.19 to 2.99, and 5.47, 95% CI: 4.31 to 6.95, respectively). Moreover, high-dose DCB reduced the incidence of CD-TLR at 6 and 12 months of follow-up (OR: 0.33, 95% CI: 0.18 to 0.63, and 0.63, 95% CI: 0.48 to 0.84, respectively). Conclusion Low-dose DCBs were associated with higher primary patency without significant differences in all-cause mortality or amputation. On the other hand, high-dose DCBs were associated with a higher incidence of amputation without significant differences in other studied outcomes.Low dose Paclitaxel coated balloon vs CoHigh dose Paclitaxel coated balloon vs C

Abstract Aims Cardiac amyloidosis (CA) is common in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Cardiac amyloidosis has poor outcomes, and its assessment in all TAVR patients is costly and challenging. Electrocardiogram (ECG) artificial intelligence (AI) algorithms that screen for CA may be useful to identify at-risk patients. Methods and results In this retrospective analysis of our institutional National Cardiovascular Disease Registry (NCDR)-TAVR database, patients undergoing TAVR between January 2012 and December 2018 were included. Pre-TAVR CA probability was analysed by an ECG AI predictive model, with >50% risk defined as high probability for CA. Univariable and propensity score covariate adjustment analyses using Cox regression were performed to compare clinical outcomes between patients with high CA probability vs. those with low probability at 1-year follow-up after TAVR. Of 1426 patients who underwent TAVR (mean age 81.0 ± 8.5 years, 57.6% male), 349 (24.4%) had high CA probability on pre-procedure ECG. Only 17 (1.2%) had a clinical diagnosis of CA. After multivariable adjustment, high probability of CA by ECG AI algorithm was significantly associated with increased all-cause mortality [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.01–1.96, P = 0.046] and higher rates of major adverse cardiovascular events (transient ischaemic attack (TIA)/stroke, myocardial infarction, and heart failure hospitalizations] (HR 1.36, 95% CI 1.01–1.82, P = 0.041), driven primarily by heart failure hospitalizations (HR 1.58, 95% CI 1.13–2.20, P = 0.008) at 1-year follow-up. There were no significant differences in TIA/stroke or myocardial infarction. Conclusion Artificial intelligence applied to pre-TAVR ECGs identifies a subgroup at higher risk of clinical events. These targeted patients may benefit from further diagnostic evaluation for CA.

Introduction: Cardiac amyloidosis (CA) has been suggested to be common (up to 16%) in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). CA has poorer outcomes and its assessment in all TAVR patients may be costly and challenging. Hypothesis: CA may be screened for with an artificial intelligence (AI) clinical predictive model applied to pre-TAVR ECGs, and high probability (>50%) for CA may be associated with worse clinical outcomes. Methods: In this retrospective analysis of the Mayo institutional National Cardiovascular Disease Registry (NCDR)-TAVR, patients undergoing a TAVR between Jan-2012 and Dec-2017 were included. Pre-TAVR ECGs were analyzed by the AI predictive model for CA embedded in the EMR. EMRs were reviewed to assess for a clinical diagnosis of CA in those identified as high probability (>50%) by the AI tool. Clinical outcomes on 1 year follow-up were extracted from the NCDR-TAVR database and Kaplan-Meier curves were created to compare patients with high CA probability (≥50%) versus those with low probability (<50%). Results: Of 1070 patients who underwent TAVR (mean age 81.1± 8.5 years, 58.2% male), 263 (24.6%) had ≥50% probability for CA on pre-procedure ECG. Only 18 (1.7%) of these had clinical diagnosis of CA. In the survival analysis, high probability of CA by AI tool was associated with higher all-cause mortality (HR 1.60, 95%CI 1.09-2.34, p=0.01) and greater HF admissions (HR 1.59, 95%CI 1.08-2.35, p<0.01). Neither TIA/stroke nor myocardial infarction were statistically significant. MACE (TIA/stroke, myocardial infarction, heart failure admissions) was higher in the ≥50% CA probability group (HR 1.68, 95%CI 1.17-2.40, p<0.01), (Figure) . Conclusion: CA is clinically underdiagnosed in patients undergoing TAVR. AI applied to pre-TAVR ECGs suggesting higher probability for CA identifies a subgroup at higher risk of clinical events, who may benefit from further diagnostic evaluation for CA.