Complete heart block (CHB) is commonly encountered in older adults, yet its hemodynamic consequences extend beyond bradycardia and reduced cardiac output. Severe pulmonary hypertension (PH) secondary to atrioventricular (AV) dyssynchrony is exceedingly rare, particularly in patients with preserved left ventricular systolic function. Recognizing reversible PH due to rhythm disturbances is essential in the geriatric population where symptoms are often nonspecific. An 86-year-old man presented with progressive fatigue, orthopnea, and presyncope. Echocardiography revealed severe PH with an estimated pulmonary artery systolic pressure (PASP) of 120 mmHg, preserved left ventricular ejection fraction (LVEF) of 60

Background Primary percutaneous coronary intervention (PPCI) is the preferred treatment for ST-segment elevation myocardial infarction (STEMI). Treatment delay significantly affects the prognosis of STEMI patients. Objectives The aim of this study was to investigate the treatment delay and its influencing factors for STEMI in Beijing. Methods STEMI patients undergoing PPCI at 65 hospitals between 2018 and 2022 were enrolled. Treatment delays were collected and analyzed using mixed-effects models to assess the impact of admission time, arrival mode, and hospital level. Results Among 13,445 individuals, median total ischemic time (TIT), symptom onset-to-door time (S2D), and door-to-balloon time (D2B) were 188 minutes (Q1-Q3: 133-288 minutes), 116 minutes (Q1-Q3: 60-200 minutes), and 72 minutes (Q1-Q3: 58-89 minutes), respectively. Compared with off-hours admissions, S2D was longer and D2B was shorter for on-hours admissions (P < 0.001 for both). Median TIT, S2D, and D2B were longer for self-transported patients than for ambulance-transported patients (P < 0.001 for all). Median TIT and S2D were shorter and D2B was longer at nontertiary hospitals than at tertiary hospitals (P < 0.001 for all). According to linear mixed-effects models adjusting for confounders, off-hours admission was linked to 6.6% shorter S2D but 11.6% longer D2B. Ambulance transport was independently associated with 9.0% shorter S2D and 10.3% shorter D2B. Treatment at tertiary hospitals was associated with 19.0% longer S2D. Conclusions Despite advances in STEMI management, prehospital delay remains the dominant component of TIT in Beijing. Future strategies should focus on improving hospital preparedness, increasing ambulance use, and minimizing interhospital disparities to reduce treatment delay.

BACKGROUND:The multicenter, randomized, sham-controlled FAVOR III China trial (Comparison of Quantitative Flow Ratio-Guided and Angiography-Guided Percutaneous Intervention in Patients with Coronary Artery Disease) demonstrated that quantitative flow ratio (QFR)-guided percutaneous coronary intervention (PCI) resulted in better outcomes compared with angiographic guidance at 1-year and 2-year follow-up. Whether these benefits are sustained over long-term follow-up remains uncertain. OBJECTIVES:The purpose of this study was to evaluate the long-term effectiveness and safety of a QFR-guided PCI strategy compared with angiography-guided PCI at 5 years. METHODS:Patients with at least 1 angiographically intermediate coronary lesion (50%-90% diameter stenosis) in a vessel ≥2.5 mm diameter were randomized to a QFR-guided (PCI performed only if QFR ≤0.80) or angiography-guided strategy. The primary endpoint was major adverse cardiac events (a composite of all-cause death, myocardial infarction, or ischemia-driven revascularization) at 1 year; 5-year outcomes data are reported herein. RESULTS:At 5 years, major adverse cardiac events composite was lower with QFR guidance than with angiography guidance (17.5% vs 21.1%; HR: 0.80; 95% CI: 0.69-0.92; P = 0.002), driven by fewer myocardial infarctions (5.8% vs 9.0%; HR: 0.63; 95% CI: 0.49-0.80; P < 0.0001) and ischemia-driven revascularizations (9.6% vs 12.0%; HR: 0.78; 95% CI: 0.64-0.95; P = 0.02) in the QFR-guided group. All-cause death did not differ between groups. Landmark analysis showed that the benefit of QFR guidance accrued predominantly within the first 2 years (8.5% vs 12.5%; HR: 0.66; 95% CI: 0.54-0.81; P < 0.0001), with similar outcomes between 2 and 5 years (10.2% vs 11.2%; HR: 0.90; 95% CI: 0.73-1.11; P = 0.32; P for interaction = 0.001). CONCLUSIONS:Compared with angiography guidance, QFR-guided strategy improved 5-year clinical outcomes, with benefits primarily achieved within the first 2 years. (The FAVOR III China Study; NCT03656848).

Robotic percutaneous coronary intervention (PCI) remains predominantly teleoperated, while the most demanding part of the procedure, guidewire navigation through a moving coronary tree under fluoroscopy, still depends on the continuous human interpretation of vessel anatomy, cardiac phase, guidewire position, and target location. We present a preclinical perception-to-action framework for AI-driven robotic PCI that integrates fluoroscopic perception, dynamic coronary vessel memory, vessel-coordinate state estimation, and robot-executable guidewire command generation on a robotic PCI platform. During contrast angiography, phase-indexed vessel-catheter templates and a dynamic vessel-coordinate coronary map are generated. During guidewire manipulation without contrast injection, live fluoroscopy is segmented into catheter and guidewire structures, cardiac phase is estimated by overlap between the live catheter-guidewire skeleton and stored vessel-catheter templates, the guidewire is assigned to the most likely vessel branch, and the distal tip is projected to a vessel-coordinate target representation for robotic action generation. The segmentation dataset contained 6269/1567/957 vessel images, 3857/964/537 guidewire images, and 4796/1199/667 catheter images for training/validation/test splits, respectively. Test-set Dice scores were 90.7% for vessels, 92.6% for catheters, and 89.0% for guidewires. In 623 real-time fluoroscopy frames from physician-supervised animal experiments, phase selection accuracy was 589/623 (94.6%; 95% CI, 92.5-96.1%) and vessel assignment accuracy was 575/623 (92.3%; 95% CI, 89.9-94.1%). Across 34 scenario-level episodes and their associated command-level decisions, correct-command rates ranged from 83.6% to 95.6% across target navigation and safety scenarios. These results provide preclinical evidence that live fluoroscopic perception can be converted into robot-executable coronary guidewire actions within an integrated AI-robotic PCI workflow. The study was designed to establish early system feasibility rather than to prove clinical superiority, large-scale generalization, or comparative advantages over manual or teleoperated robotic PCI.

Coronary artery disease (CAD) remains a major global public health burden, yet scalable pre-imaging risk stratification tools are limited. In this multicenter study, we developed and validated an artificial intelligence-enabled electrocardiography (AI-ECG) model using coronary computed tomographic angiography (CCTA) as the anatomical reference to predict vessel-specific hemodynamically significant stenosis (≥70% for RCA, LAD, LCX; ≥50% for LM). The model was evaluated in internal and external cohorts, clinically normal ECGs, and prespecified demographic and clinical subgroups. It showed discrimination across vessels in internal validation and consistent external and normal ECG performance. Predicted probabilities increased with CCTA-defined stenosis severity and were converted into vessel-specific low-, intermediate-, and high-risk strata. Calibration and decision curve analyses supported its clinical utility. Integration with guideline-based pre-test probability improved risk reclassification, enhanced rule-out performance, and reduced the gray-zone proportion. In longitudinal follow-up, model-defined risk groups showed clear separation in major adverse cardiovascular events. Waveform- and attribution-based analyses identified structured ECG differences and physiologically meaningful signal regions linked to high-risk predictions. These results support AI-ECG as a feasible tool for pre-imaging risk stratification and clinical triage, warranting prospective validation in broader clinical settings.

Computational fluid dynamics (CFD)-based numerical calculation of fractional flow reserve (FFRCT) and instantaneous wave-free ratio (iFRCT) is a crucial non-invasive technology for assessing myocardial ischemia. Their diagnostic accuracy depends on precisely calculating epicardial coronary stenosis resistance and coronary microcirculatory resistance. However, conventional CFD models face two main limitations. First, they assume rigid vessel walls, failing to capture how different plaque types affect stenosis resistance through neural regulation-induced vasodilation changes. Second, the presence of compensatory mechanisms in coronary microcirculation leads to inaccuracies in calculating microcirculatory resistance. These physiological oversimplifications, combined with the low computational efficiency of traditional CFD, compromise diagnostic accuracy and hinder real-time clinical application. This paper systematically reviews existing FFRCT/iFRCT computational models, their limitations, and current research on model improvement and computational efficiency. Given the acute nature and high mortality of myocardial infarction, future efforts should focus on establishing high-fidelity cardiovascular simulation models by integrating multi-modal clinical data. Combining artificial intelligence with digital twin technology could enable dynamic early warning for acute myocardial ischemia and infarction in daily life applications. This direction represents a promising future development path for non-invasive diagnostic technologies and holds significant clinical value.

Clinical management of primary antiphospholipid syndrome (PAPS) complicated by acute myocardial infarction (AMI) is particularly challenging, especially when recurrent AMI and thrombocytopenia are present. This case report describes a 35-year-old male patient with PAPS who experienced two episodes of acute inferior ST-elevation myocardial infarction (STEMI). Comprehensive diagnostic evaluations including coronary imaging, physiology, immunology, bone marrow morphology, and molecular biology were performed to confirm the diagnosis. A personalized treatment regimen combining clopidogrel, low-molecular-weight heparin, methylprednisolone, hydroxychloroquine, and rituximab was administered, which resulted in a favorable long-term prognosis. This case underscores the importance of a multidisciplinary approach and individualized treatment strategies based on coronary functional assessment for managing patients with PAPS and AMI.

Structural heart disease (SHD) is a primary driver of heart failure and cardiovascular mortality, yet early detection remains constrained by the limited accessibility of echocardiography. While single-lead electrocardiogram (ECG) is ubiquitous through wearables, existing AI screening models often depend on 12-lead inputs, generalize poorly across institutions, or require massive, condition-specific labeled datasets. Recent work has demonstrated the feasibility of contrastive pre-training between single-lead ECGs and echocardiography reports within a single health system. Here, we present AnyECG-Echo, a framework that advance this paradigm toward clinical translation through three key developments: (1) evaluation in a geographically independent external cohort (n = 16,621); (2) diagnostic coverage of 13 fine-grained SHD subtypes spanning myocardial, chamber, valvular, and great-vessel pathologies; and (3) dual-axis mechanistic interpretability combining electrophysiology-grounded Shapley attribution with emergent correlations to quantitative measurements. Across validation cohorts totaling n = 25,222, the model demonstrated high AUROC for high-impact subtypes, including reduced left ventricular systolic function (AUROC 0.866-0.924), global heart enlargement (0.877-0.931), and mitral stenosis (0.836-0.906). Furthermore, we successfully validated the alignment of model outputs with established medical physiological traits, thereby enhancing interpretability. Notably, we discovered that AnyECG-Echo's outputs function as physiologically grounded digital biomarkers that accurately track objective metrics such as LVEF and myocardial wall thickness. These findings prove that wearable single-lead ECGs can effectively detect fine-grained structural heart disease, offering a practical solution for population-scale screening.

Background Intraoperative hypotension is associated with cardiovascular complications after major noncardiac surgery, but randomized trials assessing whether intensive blood pressure management during surgery can reduce these complications have shown inconsistent results. Objectives The purpose of this study was to determine whether intensive intraoperative blood pressure management reduces the incidence of a composite of cardiovascular complications within 30 days after major abdominal surgery. Methods In this investigator-initiated parallel-group trial, patients at 3 Chinese sites were randomly assigned (1:1) to intensive blood pressure management targeting intraoperative MAP ≥80 mm Hg (intensive strategy group) or conventional management targeting intraoperative MAP ≥ the higher of 65 mm Hg or 60% of preoperative baseline pressure (conventional strategy group). We included patients aged ≥45 years who had known cardiovascular disease or cardiovascular risk factors and were scheduled for inpatient abdominal surgery expected to last at least 2 hours. The primary outcome was a composite of myocardial injury or infarction, new-onset clinically important arrhythmias, acute heart failure, stroke, cardiac arrest, and all-cause death within 30 days of surgery. Results Between June 30, 2020, and September 23, 2022, 1,500 patients were enrolled, of whom 1,477 were included in the modified intention-to-treat population (739 in the intensive strategy group and 738 in the conventional strategy group). Patients assigned to intensive intraoperative blood pressure management experienced a lower burden of hypotension exposure, as assessed by several measures. For example, the median cumulative duration of MAP <65 mm Hg was 1 minute (Q1-Q3: 0-7 minutes) in the intensive strategy group, compared with 8 minutes (Q1-Q3: 0-20 minutes) in the conventional strategy group. The primary composite outcome occurred in 107 of 739 patients (14.5%) in the intensive strategy group and 100 of 738 patients (13.6%) in the conventional strategy group (relative risk: 1.07; 95% CI: 0.83-1.38; P = 0.61). Conclusions In high-risk patients having major abdominal inpatient surgery, intensive intraoperative blood pressure management targeting a mean arterial pressure ≥80 mm Hg did not reduce the incidence of cardiovascular events compared with the conventional target of ≥65 mm Hg and 60% of the preoperative baseline.

BackgroundCoronary artery bypass grafting (CABG) in patients with concurrent coronary artery disease (CAD) and hematological neoplasms presents unique challenges due to immunosuppression, hematologic dysfunction, and coagulopathy. This study aimed to assess the safety and feasibility of CABG in this population and to evaluate factors influencing prognosis.MethodsThis retrospective study included 41 patients with CAD and hematological neoplasms who underwent CABG between 2018 and 2023. Hematological neoplasms were classified into seven categories, and patients were stratified by hematological disease status: stable, disease-free, or progressive. Key perioperative outcomes, graft patency, and survival data were analyzed. Cox regression models identified independent predictors of prognosis.ResultsOf the 41 patients, 28 (68.3%) were stable, 10 (24.4%) were disease-free, and 3 (7.3%) were progressive. The median preoperative platelet count was 143 × 109/L, with 8 patients presenting counts <50 × 109/L requiring preoperative platelet transfusions. Postoperative transfusion rates for packed red blood cells (PRBCs), fresh frozen plasma (FFP) and platelets were 51.2%, 39.0%, and 12.2%, respectively. The median operation time was 210 min, with 87.8% undergoing off-pump CABG. Graft patency at discharge was 92.3%. Major infections occurred in 4.9% of patients, and 9 (22%) deaths were recorded during follow-up, 8 due to hematological progression and 1 due to myocardial infarction. Cox regression identified preoperative blood cell levels as independent predictors of survival (p < 0.05), while CABG-related factors showed no significant association (p > 0.05).ConclusionsCABG can be performed safely in most patients with stable hematological neoplasms, with no perioperative mortality, providing an opportunity for further hematological treatments. Preoperative blood cell levels significantly influence prognosis, underscoring the importance of multidisciplinary management. Larger studies are needed to validate these findings and refine treatment strategies.

ABSTRACTThe accurate non‐invasive detection and estimation of central aortic pressure waveforms (CAPW) are crucial for reliable treatments of cardiovascular system diseases. But the accuracy and practicality of current estimation methods need to be improved. Our study combines a meta‐learning neural network and a physics‐driven method to accurately estimate CAPW based on personalized physiological indicators. We collected data from 260 patients who underwent catheterization surgery, using measured CAPW and personalized physiological indicators (e.g., weight, body mass index (BMI), radial mean arterial pressure (MAP), heart rate (HR), cardiac output (CO), radial systolic blood pressure (SBP), and radial diastolic blood pressure (DBP)) as input for neural network training. The output of the neural network are the Gaussian characteristic parameters of the single‐period decomposed CAPW. The neural network model was constructed using the model‐agnostic meta‐learning (MAML) algorithm framework. Applying the physical characteristics of CAPW to the loss function, served to increase the constraints on the output and improve the accuracy of CAPW estimation. To verify the accuracy of the model, we compared measured and estimated CAPW in 52 patients. The results are consistent with a normalized root mean square error (NRMSE) of 0.0206. The predictions had low biases, namely SBP: 4.97 ± 4.42 mmHg, DBP: 4.78 ± 5.98 mmHg, and MAP: 0.35 ± 3.36 mmHg. The results demonstrate the accuracy and practicability of the approach to estimate CAPW. It can provide personalized parameters to calculate myocardial ischemia indicators (e.g., instantaneous wave‐free ratio [iFR] and fractional flow reserve [FFR]) and may contribute to the early monitoring and prevention of cardiovascular diseases.

Rapid methods that can replace traditional inefficient computational fluid dynamics (CFD) for solving flow field are missing. We reconstructed three-dimensional (3D) coronary vascular tree models based on coronary computed tomography angiography (CCTA) images from 205 patients. Two fluid materials, blood and contrast agent, were mixed to simulate the flow field with concentration information under diverse boundary conditions, obtaining 2255 CFD simulations as deep learning samples. A dual-path physics-data multi-derived neural network (PDMNN) was designed, inputting geometric 3D point cloud and concentration information, respectively, and outputting 3D flow velocity field. Flow velocity in the coronary artery was clinically measured in 26 patients to verify the proposed PDMNN. For the 100 cases in a test set, the mean square error of the flow field velocity between the CFD calculations and the PDMNN predictions is 0.0309. However, the time taken by the PDMNN is significantly reduced (10 s VS 0.5 h). Clinically measured mean blood flow velocity and PDMNN predictions did not yield statistically significant differences (0.00 ± 0.05 m/s, P > 0.05). The proposed PDMNN present excellent computation accuracy and efficiency, holding a significant technical value for the clinical and engineering application.

AIMS:As a special type of hypertrophic cardiomyopathy (HCM), apical HCM (ApHCM) has different clinical characteristics while its nature history and prognosis are not well recognized. We aimed to describe the characteristics and outcomes of ApHCM and identify predictors of adverse outcomes. METHODS:In this single-centre retrospective study, we included 479 patients with HCM and divided them into ApHCM and non-ApHCM groups. Clinical, electrocardiographic, echocardiographic and survival data were compared between the groups. The primary outcome was major adverse cardiac events in hospital and during follow-up. A two-sided P-value < 0.05 was considered statistically significant. RESULTS:A total of 109 ApHCM patients and 370 non-ApHCM patients were analysed and 379 patients completed the follow-up among them. The age of enrolled patients was 61.0 (50.0-69.0) years, and 289 (60.3%) were male. Compared with non-ApHCM patients, ApHCM patients were older at diagnosis [55.0 (45.0-64.0) vs. 50.0 (40.0-61.0) years, P = 0.006] and had less positive family history for HCM [3 (2.8%) vs. 34 (9.2%), P = 0.027], more electrocardiographic abnormalities [101 (92.7%) vs. 287 (77.6%), P < 0.001], lower brain natriuretic peptide level [135.5 (60.8-272.8) vs. 422.5 (182.8-888.2) pg/mL, P < 0.001] and better left ventricular ejection fraction (LVEF) [69.00 (64.00-73.87) vs. 67.00 (60.24-73.45) %, P = 0.048] at baseline. During a median follow-up of 5.59 (2.33-10.30) years, the primary outcome occurred less frequently in ApHCM patients [11.4% vs 27.2%; hazard ratio (HR)adj 0.360 (95% confidence interval, CI: 0.187-0.696), P = 0.002; log rank P = 0.001]. Specifically, ApHCM was characterized by fewer all-cause death (HRadj 0.545, 95% CI: 0.305-0.975; P = 0.041) and fatal ventricular arrhythmia or appropriate implantable cardioverter defibrillator intervention (HRadj 0.099, 95% CI: 0.013-0.724; P = 0.023). LVEF (HRadj 0.861, 95% CI: 0.763-0.971; P = 0.015) and age (HRadj 1.247, 95% CI: 1.095-1.419; P = 0.001) were identified as independent predictors of the composite outcome in ApHCM. CONCLUSIONS:Patients with ApHCM may have better prognosis. LVEF and age were independent predictors of long-term outcomes in ApHCM.

Myocardial bridging (MB) is a kind of congenital coronary abnormality. The functional impact of MB on coronary artery remains a subject of debate. This study aimed to assess the hemodynamic effects of MB using coronary angiography-derived fractional flow reserve (caFFR) and elucidate the relationship between MB anatomical parameters and diastolic caFFR (dcaFFR) in patients with isolated MB (iMB) and MB combined with proximal coronary atherosclerosis (MB+AS). A total of 683 patients diagnosed with MB located on left anterior descending (LAD) via coronary angiography (CAG) were retrospectively enrolled and categorized into two groups: iMB (n = 377) and MB+AS (n = 306). The dcaFFR was calculated to evaluate the hemodynamic impact of MB. Multivariate linear regression and mediation analysis were performed to identify predictors of dcaFFR. In the iMB group, diastolic minimal lumen diameter (MLD) of MB segment was the sole independent predictor of dcaFFR (B = 0.036, β = 0.253, p <0.001). In the group of MB+AS, the severity of proximal stenosis emerged as the only independent predictor of dcaFFR (B = -0.004, β = -0.674, p <0.001), with the hemodynamic effects of MB fully mediated by proximal stenosis. In conclusion, the hemodynamic impact of MB depends on the presence of proximal coronary atherosclerosis. In iMB cases, the diastolic MLD of MB segment directly determines hemodynamic impairment. However, the hemodynamic impact of MB is nonsignificant in cases of MB+AS, as its effect is fully mediated through proximal stenosis severity.

Metabolic disorders could cause dysregulated glucose and lipid at the systemic level, but how inter-tissue/organ communications contribute to glucolipotoxicity is difficult to dissect in animal models. To solve this problem, myocardium and nerve tissues were modelled by 3D engineered heart tissues (EHTs) and neural organoids (NOs), which were co-cultured in a generalised medium with normal or elevated glucose/fatty acid contents. Morphology, gene expression, cell death and functional assessments detected no apparent alterations of EHTs and NOs in co-culture under normal conditions. By contrast, NOs significantly ameliorated glucolipotoxicity in EHTs. Transcriptomic and protein secretion assays identified the extracellular matrix protein versican as a key molecule that was transferred from NOs into EHTs in the high-glucose/fatty acid condition. Recombinant versican protein treatment was sufficient to reduce glucolipotoxicity in EHTs. Adeno-associated virus-delivered versican overexpression was sufficient to ameliorate cardiac dysfunction in a murine model of diabetic cardiomyopathy. These data provide the proof-of-concept evidence that inter-tissue/organ communications exist in the co-culture of engineered tissues and organoids, which could be systemically studied to explore potential pathological mechanisms and therapeutic strategies for multi-organ diseases in vitro.

Aims:Bicuspid aortic valve (BAV) stenosis complicates transcatheter aortic valve replacement (TAVR) planning, with no validated automated measurement algorithm available. We developed Cardioverse, the first fully automated deep learning algorithm for BAV anatomical assessment in TAVR planning. Methods and results:We conducted a large-scale, multicenter retrospective study encompassing 1,147 consecutive patients with BAV undergoing TAVR across 16 high-volume Chinese centers (March 2019-February 2023). Cardioverse was trained on this cohort and evaluated in an internal (n = 437) and external (n = 110) validation cohorts. Our novel Cardioverse algorithm demonstrated exceptional segmentation performance across all anatomical targets with Dice similarity coefficients >0.97 for coronary cusps and ostia. Critically, the algorithm achieved unprecedented workflow efficiency gains: 80% reduction in assessment time [241.0 IQR (181.0, 297.0) vs. 1251.0 IQR (872.0, 1408.0) seconds], 85% reduction in user interactions [57.0 IQR (45.0, 78.0) vs. 382.5 IQR (285.5, 475.0) clicks], and 87% reduction in manual effort [7.5 IQR (4.8, 9.3) vs. 57.2 IQR (43.5, 68.4) meters mouse movement] compared to expert observers (P < 0.001). Importantly, accuracy was maintained across all BAV phenotypes with correlation coefficients >0.91 for all critical measurements, including annular dimensions, calcification quantification, and aortic root morphology assessment. Conclusion:Cardioverse transforms pre-TAVR assessment for BAV patients, offering a validated solution combining accuracy and efficiency. It reduces assessment time from over 20 min to < 5 min, addressing the need for standardized, rapid, and reliable BAV evaluation. Its robust performance across diverse BAV phenotypes makes it a crucial tool for enhancing TAVR planning consistency. Clinical trial registration:ClinicalTrials.gov Protocol Registration System (NCT05044338).

Background Little is known about impact of screen failures on enrollment process and patient characteristics in large-scale clinical trials. Objectives The objective of this paper is to determine the impact of screen failures on enrollment process and patient characteristics in the randomized FAVOR III China trial, a large-scale, multicenter, randomized trial comparing clinical outcomes between QFR-guided versus standard angiography-guided PCI. Methods The FAVOR III China trial identified patients for enrollment using a 2 stage screening process, patients met both general and angiographic inclusion criteria would be enrolled. Reasons for screen failure were prospectively recorded in a dedicated internet-enabled web-based response system. Center volume and experience were valuated according to total screen number of patients, and sequence of initiation time in the present study. Results Between December 25, 2018, and January 19, 2020, 5881 patients were screened for enrolment. Among them, 2034 patients were excluded. The most common reasons for screen failure were absence of at least 1 lesion present with DS% ≥50% and ≤90% in vessel with RVD ≥2.5 mm (860, 42.3%), eligibility for PCI according to the operators (526, 25.9%), and with only coronary artery lesion had diameter stenosis >90% with TIMI flow <3 (254, 12.5%). Patients excluded due to poor imaging quality or poor interrogated vessel condition that deemed unable for QFR measurement accounted for 6.2% (127). The percentage of screened failure patients were significantly higher in high-volume and more experience center (p<0.0001). Conclusions In clinical practice, approximately two-third of patients were eligible for QFR evaluation, based on the experience from the FAVOR III China trial. Additionally, center experience emerged as a key factor influencing the quality of a prospective trial.

Disorders of mineral metabolism, including elevated levels of serum calcium, phosphate, 25-hydroxyvitamin D (25OH-VitD), parathyroid hormone (PTH), and fibroblast growth factor 23 (FGF23), have been reported in patients with calcific aortic valve stenosis (CAVS). However, evidence of the causal role of mineral metabolism in CAVS is still lacking. In this study, we employed a systematic pipeline combining Mendelian randomization (MR), Steiger directionality test, colocalization analysis, protein-protein network, and enrichment analysis to investigate the causal effect of mineral metabolism on CAVS. Genome-wide association study (GWAS) and protein quantitative trait loci data for mineral metabolism markers were extracted from large-scale meta-analyses. Summary statistics for CAVS were obtained from two independent GWAS datasets as discovery and replication cohorts (n = 374,277 and 653,867). In MR analysis, genetic mimicry of serum FGF23 elevation was associated with increased CAVS risk [ORdiscovery = 3.081 (1.649-5.760), Pdiscovery = 4.21 × 10-4; ORreplication = 2.280 (1.461 - 3.558), Preplication = 2.82 × 10-4] without evidence of reverse causation (Psteiger= 7.21 × 10-98). Strong colocalisation association with CAVS was observed for FGF23 expression in the blood (PP.H4 = 0.96). Additionally, we identified some protein-protein interactions between FGF23 and known CAVS-associated genes. Serum calcium, phosphate, 25OH-VitD, and PTH failed to show causal effects on CAVS at Bonferroni-corrected significance (all P > 0.05/5 = 0.01). In conclusion, elevated serum FGF23 level may act as a causal risk factor for CAVS, and its mechanism of action in CAVS development may be independent of its function in regulating mineral metabolism. Hence, FGF23 may serve as a circulating marker and a promising preventive target for CAVS, warranting further investigation.