Gulati, Rajiv

Background: Coronary microvascular disease (CMD) may be endothelium-independent (coronary flow reserve, CFR < 2.5) or endothelium-dependent (<50% increase in coronary blood flow in response to acetylcholine). CMD has been implicated in abnormal myocardial relaxation and impaired diastolic function. Wave intensity analysis (WIA) is a hemodynamic method that quantifies the energy of pressure-flow waves driving coronary blood flow. The backward expansion wave (BEW) is the dominant distally originating wave, generated by microvascular suction during ventricular relaxation. Thus, the BEW may offer mechanistic insight into the link between CMD and diastolic dysfunction. Hypothesis: We hypothesized that diastolic dysfunction would be more common in patients with CMD, and that the backward expansion wave (BEW) intensity would be lower in those with diastolic dysfunction compared to those without. Methods: Patients with non-obstructive coronary artery disease undergoing invasive coronary physiology assessment of the left anterior descending artery were included (n = 113). Pressure and Doppler flow were recorded at rest, with adenosine, and with acetylcholine for categorization of CMD as endothelium-independent (CMD-Ei) and/or endothelium-dependent (CMD-Ed). Wave intensity analysis was used to calculate cumulative BEW (J×m -2 ) at rest in CMD, CMD-Ei (endothelium-independent), and CMD-Ed (endothelium-dependent) subgroups. Diastolic dysfunction was diagnosed by transthoracic echocardiogram using the 2016 American Society of Echocardiography (ASE) guidelines. Results: Of the 113 study patients, 88 (77.9%) had CMD and 25 (22.1%) did not. Among those with CMD, 39 patients (44.3%) had diastolic dysfunction (Figure 1). In the patients with CMD, the BEW intensity was significantly lower in patients with diastolic dysfunction compared to those without (6.5 vs. 9.0 × 10 3 W×m -2 ×s -1 , p < 0.05). The same trend was observed for the CMD-Ei (7.2 vs. 9.7 × 10 3 W×m -2 ×s -1 , p < 0.05) and CMD-Ed (6.2 vs. 9.1 × 10 3 W×m -2 ×s -1 , p < 0.05) subtypes. Conclusions: Diastolic dysfunction is frequent in patients with invasively diagnosed CMD. Patients with CMD who have diastolic dysfunction have comparatively lower BEW intensity, regardless of endothelial subtype. Since the BEW is the major driver of coronary flow during diastole, this suggests a mechanism by which CMD may lead to diastolic dysfunction.

Background: Coronary wave intensity analysis (WIA) provides a mechanistic view of coronary hemodynamics and has been increasingly used to phenotype coronary microvascular disease (CMD). Standard WIA requires simultaneous pressure and flow measurements within the same vessel, but intra-coronary pressure measurement may be limited by hardware availability. In patients with non-obstructive coronary arteries, aortic pressure may serve as a surrogate for intra-coronary pressure to enable broader feasibility of WIA. We aimed to determine whether wave profiles derived from intra-aortic and intra-coronary pressure measurements are comparable when paired with intracoronary Doppler flow in patients with non-obstructive coronary artery disease. Methods: Patients undergoing invasive coronary physiology assessment of the left anterior descending artery were included. Intracoronary flow velocity and intra-coronary pressure were simultaneously recorded using a ComboWire (Philips Volcano) in the proximal LAD. Aortic pressure was concurrently measured via the guide catheter to allow comparison of pressure sources. In the intra-aortic pressure group, pressure and flow data were aligned using the R wave of the ECG trace. WIA was performed using conventional methods to quantify the dominant waves: forward compression wave (FCW), backward compression wave (BCW), and backward expansion wave (BEW). Agreement between wave intensity was assessed using Bland-Altman analysis and Pearson correlation. Results: A total of 14 paired waveforms were analyzed with a total of 42 coronary waves compared. Wave intensities calculated using intra-coronary versus intra-aortic pressure showed excellent agreement across all wave types. Mean bias between methods was −0.07 x 10 3 W×m -2 ×s -1 with limits of agreement from −0.63 to +0.49. The correlation between intra-coronary and intra-aortic wave intensities was strong (r = 0.997, p < 0.001), with minimal dispersion and consistent agreement across the full range of wave intensities ( Figure 1 ). Conclusions: In patients with non-obstructive coronary arteries, wave intensity analysis using guide-catheter aortic pressure yields results nearly identical to those obtained with intra-coronary pressure. These findings support the use of aortic pressure as a reliable surrogate for intra-coronary pressure in WIA for the calculation of microvascular coronary hemodynamics, reducing technical barriers and enabling broader clinical and research utilization.

Introduction: Identifying patients at risk for ischemic events after percutaneous coronary intervention (PCI) relies on traditional analysis of limited clinical and imaging variables. Machine learning (ML) has shown promise in effectively predicting cardiovascular risk in population studies. While existing ML models mainly predict mortality and incorporate clinical variables, there is a lack of tools that have utilized genetic data and that predict ischemic events. Aims: This study aims to develop and validate a ML model incorporating genotyping and clinical data to enhance prediction of ischemic outcomes for PCI patients utilizing large prospectively derived diverse datasets. Methods: Patients from the TAILOR-PCI trial (n=5302) were utilized for model development. 50% of the sample was utilized for Boruta feature selection and 50% for training and testing using cross validation. Features included demographics, medical history, medications, PCI characteristics, and genetic data (specifically, CYP2C19 *2, *3, *17 alleles). The primary endpoint was a composite of cardiovascular death, myocardial infarction, stroke, stent thrombosis, and severe recurrent ischemia at 12 months. Multiple ML classification algorithms, including Support Vector Machine (SVM) polynomial, Random Forest, Light gradient boost, XG Boost, among others, were benchmarked for their prediction performance on rare events. The top performing classifiers were externally validated on an independent dataset from the PRECISION PCI study (n=3,745). Results: Mean participant age of the training set was 64.2 ± 11.0 years, with 75.4% being male. During follow-up of 12 months, among 4,572 patients in the entire cohort 343 (7.5%) met the primary outcome. The SVM polynomial model demonstrated the highest area under the curve (AUC) of 0.67 for predicting the primary outcome with test dataset. The sensitivity, specificity, precision, and recall were 0.87, 0.28, 0.07, and 0.87 respectively (Figure). Peripheral arterial disease, body mass index, and age were among the top variables by feature importance. Conclusion: ML models incorporating both clinical and genetic data are feasible and highly promising in predicting major adverse cardiac events that may help guide use of anti-platelet drug therapy. The AUC values are reasonable given imbalances and misclassifications in datasets, and further model optimization with prospective utilization of the model will be paramount.

Background: Patients with normal resting left ventricular ejection fraction (LVEF) without either coronary artery disease (CAD) or a hypertensive response can paradoxically develop reduced LVEF during exercise stress echocardiography (ESE). The clinical phenotype and outcomes of these patients is unknown. Hypothesis: Patients who paradoxically develop reduced LVEF during exercise may represent a sub-phenotype of heart failure with preserved LVEF (HFpEF). Aims: To describe the baseline characteristics and clinical outcomes of this unique patient population. Methods: Among all ESE performed between January 2003 and December 2022, patients without a hypertensive response to exercise and without CAD by angiogram within 90 days of ESE, who had a resting LVEF ≥50% with a ≥5% LVEF decrease during ESE were identified. All-cause mortality, HF hospitalization, and atrial fibrillation (AF) outcomes were assessed. Kaplan-Meier and Cox regression methods were used to analyze time-to-event outcomes. Results: Among 213,643 stress echocardiograms performed, 134 patients met eligibility criteria (Table 1). The mean age of the population was 66±10 years, 76% were women, and 16% had AF at baseline. Mean LVEF was 58±4% at rest and 43±4% at peak stress. Stress electrocardiogram met criteria for ischemia in 14%. The 10-year all-cause mortality risk was 12.9% (95% CI 5.5-20.3) with 10 (37%) of 27 deaths due to cancer (Figure 1, Panel A). The 10-year estimated risk of HF hospitalization was 17.6% (95% CI 9.0-26.2) (Figure 1, Panel B). Among 112 patients without AF at baseline, the 10-year risk of developing AF was 23.4% (95% CI 13.4-33.4). Conclusions: Patients with exercise-induced reduced LVEF in the absence of obstructive CAD have a high incidence of HF hospitalizations and AF. Given the preponderance of women, risk for AF, HF hospitalizations, and cancer-related deaths, the possibility that this condition is an early sub-phenotype of HFpEF should be investigated.

ImportanceGreater splanchnic nerve ablation may improve hemodynamics in patients with heart failure and preserved ejection fraction (HFpEF).ObjectiveTo explore the feasibility and safety of endovascular right-sided splanchnic nerve ablation for volume management (SAVM).Design, Setting, and ParticipantsThis was a phase 2, double-blind, 1:1, sham-controlled, multicenter, randomized clinical trial conducted at 14 centers in the US and 1 center in the Republic of Georgia. Patients with HFpEF, left ventricular ejection fraction of 40% or greater, and invasively measured peak exercise pulmonary capillary wedge pressure (PCWP) of 25 mm Hg or greater were included. Study data were analyzed from May 2023 to June 2024.InterventionSAVM vs sham control procedure.Main Outcomes and MeasuresThe primary efficacy end point was a reduction in legs-up and exercise PCWP at 1 month. The primary safety end point was serious device- or procedure-related adverse events at 1 month. Secondary efficacy end points included HF hospitalizations, changes in exercise function and health status through 12 months, and baseline to 1-month change in resting, legs-up, and 20-W exercise PCWP.ResultsA total of 90 patients (median [range] age, 71 [47-90] years; 58 female [64.4%]) were randomized at 15 centers (44 SAVM vs 46 sham). There were no differences in adverse events between groups. The primary efficacy end point did not differ between SAVM or sham (mean between-group difference in PCWP, −0.03 mm Hg; 95% CI, −2.5 to 2.5 mm Hg; P = .95). There were also no differences in the secondary efficacy end points. There was no difference in the primary safety end point between the treatment (6.8% [3 of 44]) and sham (2.2% [1 of 46]) groups (difference, 4.6%; 95% CI, −6.1% to 15.4%; P = .36). There was no difference in the incidence of orthostatic hypotension between the treatment (11.4% [5 of 44]) and sham (6.5% [3 of 46]) groups (difference, 4.9%; 95% CI, −9.2% to 18.8%; P = .48).Conclusions and RelevanceResults show that SAVM was safe and technically feasible, but it did not reduce exercise PCWP at 1 month or improve clinical outcomes at 12 months in a broad population of patients with HFpEF.Trial RegistrationClinicalTrials.gov Identifier: NCT04592445