Lerman, Amir

Abstract Aims This study aims to identify whether adding peripheral microvascular dysfunction (PMED), a marker of atherosclerosis to established risk scores has an incremental prognostic value for major adverse cardiovascular events (MACE). Methods and results This is a retrospective study of patients who underwent measuring peripheral arterial tonometry from 2006 to 2020. The optimal cut-off value of the reactive hyperaemia index (RHI) that had maximal prognostic value associated with MACE was calculated. Peripheral microvascular endothelial dysfunction was defined as the RHI lower than the cut-off. Traditional cardiovascular risk factors such as age, sex, congestive heart failure, hypertension, diabetes, stroke, and vascular disease were determined to calculate the CHA2DS2-Vasc score. The outcome was MACE defined as myocardial infarction, heart failure hospitalization, cerebrovascular events, and all-cause mortality. A total of 1460 patients were enrolled (average age 51.4 ± 13.6, 64.1% female). The optimal cut-off value of the RHI was 1.83 in the overall population and in females and males was 1.61 and 1.8, respectively. The risk of MACE during 7 [interquartile range (IQR): 5,11] years of follow-up was 11.2%. Kaplan–Meier analysis showed that lower RHI is associated with worse MACE-free survival (P < 0.001). Multivariate Cox proportional hazard analysis, controlling for classic cardiovascular risk factors or risk scores such as CHA2DS2-Vasc and Framingham risk score revealed that PMED is an independent predictor of MACE. Conclusion Peripheral microvascular dysfunction predicts cardiovascular events. Non-invasive assessment of peripheral endothelial function may be useful in early detection and improving the stratification of high-risk patients for cardiovascular events. Lay summary Key findings

BACKGROUND: The financial burden linked to the diagnosis and treatment of patients with chest pain on the health care system is considerable. Angina and nonobstructive coronary artery disease (ANOCA) is common, associated with adverse cardiovascular events, and may lead to repeat testing or hospitalizations. Diagnostic certainty can be achieved in patients with ANOCA using coronary reactivity testing (CRT); however, its financial effect on the patient has not been studied. Our goal was to assess the effect of CRT on health care–related cost in patients with ANOCA. METHODS: Patients with ANOCA who underwent diagnostic coronary angiography (CAG) and CRT (CRT group) were matched to controls who had similar presentation but only underwent a CAG without CRT (CAG group). Standardized inflation-adjusted costs were collected and compared between the 2 groups on an annual basis for 2 years post the index date (CRT or CAG). RESULTS: Two hundred seven CRT and 207 CAG patients were included in the study with an average age of 52.3±11.5 years and 76% females. The total cost was significantly higher in the CAG group as compared with the CRT group ($37 804 [$26 933–$48 674] versus $13 679 [$9447–$17 910]; P <0.001). When costs are itemized and divided based on the Berenson-Eggers Type of Service categorization, the largest cost difference occurred in imaging (any type, including CAG; P <0.001), procedures (eg, percutaneous coronary intervention/coronary artery bypass grafting/thrombectomy) ( P =0.001), and test (eg, blood tests, EKG; P <0.001). CONCLUSIONS: In this retrospective observational study, assessment of CRT in patients with ANOCA was associated with significantly reduced annual total costs and health care utilization. Therefore, the study may support the integration of CRT into clinical practice.

Background: The majority of randomized controlled trials of revascularization decision-making excludes left main coronary artery disease (LMD). Therefore, contemporary clinical outcomes of patients with stable coronary artery disease and LMD with proven ischemia remain poorly understood. The aim of this study was to assess the long-term clinical outcomes of physiologically significant LMD according to the treatment strategies of revascularization versus revascularization deferral. Methods: In this international multicenter registry of stable LMD interrogated with the instantaneous wave-free ratio, patients with physiologically significant ischemia (instantaneous wave-free ratio ≤0.89) were analyzed according to the coronary revascularization (n=151) versus revascularization deferral (n=74). Propensity score matching was performed to adjust for baseline clinical characteristics. The primary end point was a composite of death, nonfatal myocardial infarction, and ischemia-driven target lesion revascularization of left main stem. The secondary end points were as follows: cardiac death or spontaneous LMD-related myocardial infarction; and ischemia-driven target lesion revascularization of left main stem. Results: At a median follow-up period of 2.8 years, the primary end point occurred in 11 patients (14.9%) in the revascularized group and 21 patients (28.4%) in the deferred group (hazard ratio, 0.42 [95% CI, 0.20–0.89]; P =0.023). For the secondary end points, cardiac death or LMD-related myocardial infarction occurred significantly less frequently in the revascularized group (0.0% versus 8.1%; P =0.004). The rate of ischemia-driven target lesion revascularization of left main stem was also significantly lower in the revascularized group (5.4% versus 17.6%; hazard ratio, 0.20 [95% CI, 0.056–0.70]; P =0.012). Conclusions: In patients who underwent revascularization for stable coronary artery disease and physiologically significant LMD determined by instantaneous wave-free ratio, the long-term clinical outcomes were significantly improved as compared with those in whom revascularization was deferred.

Introduction: We have previously shown that ECG-derived age (ECG-Age) predicts all-cause and cardiovascular (CV) mortality, reflecting physiologic age. We hypothesized that ECG-Age minus chronological age (Age-Gap) would be associated with coronary artery calcium (CAC) assessed by computer tomography. Methods: We developed a neural network model to predict ECG-Age using 12 lead ECGs from 399,750 training, 99,977 validation and 275,056 testing patients. We then applied the algorithm to 41,202 consecutive patients that from 1997-2020 underwent clinically indicated CAC and ECG within 1 year. Major modifiable CV risk factors were collected as part of preventive cardiology or general medical evaluations. Exclusion criteria were statin therapy, pacemakers, or history of coronary artery disease. Results: We included 41,202 subjects (68.5% males, 83.6% Caucasian), mean chronological age was 55.2±9.1 yrs and the ECG-Age was 56.01±9.3 yrs. The mean Age-Gap was -0.78±7 yrs, R 2 =0.78, p<0.0001. Mean CAC score was 140.2±532.3, and 21,483 (52%) had CAC >0. After adjustment for age and sex, those older by ECG (defined as having a positive Age-Gap) were more likely to have CAC>0 (OR 1.35, 95% CI 1.34-2.37 for those with >1 but <2 SD of a positive Age-Gap; and OR 1.80, 95% CI 1.34-2.37 for those with ≥2 SD of a positive Age-Gap), while those younger by ECG were less likely to have any CAC (OR 0.70, 95% CI 0.57-0.87 for those with >1 but <2 SD of a negative Age-Gap; and OR 0.75, 95% CI 0.67-0.84 for those with ≥2 SD of a negative Age-Gap), respectively. This association remained significant after multivariate adjustment, Fig. A and increased with CAC burden, Fig. B , all P for trend <0.01. Conclusions: The difference between physiologic AI-ECG age and chronologic age, something likely representing rate of biological aging, is associated with presence of CAC, further supporting the hypothesis that AI-ECG age can identify people more likely to have subclinical coronary atherosclerosis.

Introduction: The mechanistic link between early coronary artery disease (CAD) and atrial fibrillation (AF) continues to be explored. Clonal hematopoiesis of indeterminate potential (CHIP) is increasingly recognized as a risk factor for cardiovascular disease. We hypothesize CHIP further increases the risk for AF in early CAD. Methods: 184 participants underwent invasive coronary angiogram with endothelial function testing. Buffy coat was used for whole exosome sequencing to identify CHIP (variant allele frequency > 2% and minor allele frequency ≤ 0.1%). Early CAD was defined by the presence of coronary endothelial dysfunction (CED) in the absence of obstructive CAD. Invasive coronary angiography with endothelial function testing characterized CED as ≥ 20% increase in coronary artery diameter or ≤ 50% increase in coronary blood flow in response to acetylcholine. AF was identified by ICD-10 code or patient survey and confirmed by an independent investigator by chart review. Cox proportional hazard regression was adjusted for age, sex, and conventional cardiovascular comorbidities (hypertension, diabetes, and total cholesterol). Results: Of the 184 participants, we identified 23 cases with both early CAD and CHIP and 62 normal controls without CHIP or CAD. Case patients were significantly older (mean 60 ±9 vs 52 ±10 years, p = 0.004 years) and predominantly female (74% vs 81%, p = 0.506). AF was more likely among case participants when compared to normal controls (29% vs 10%, p = 0.036). Mean time to AF or last follow-up was 11 ±7 years. Case patients with both early CAD and CHIP were nearly 10 times more likely to develop AF when compared to normal controls in a Cox regression model adjusted for age, sex, and conventional cardiovascular comorbidities (HR 9.52, 95% CI 1.93 - 47.02, p = 0.006). The risk for AF was not significant if we defined cases by only the presence of CHIP (n = 30) or early CAD (n = 122). Conclusions: Patients with both CHIP and early CAD may have greater risk for developing AF beyond the presence of CHIP or CAD alone. Our findings suggest an added mechanistic role of CHIP that further increases the risk for AF in early CAD.

Introduction: Increasing evidence unravels the role of loneliness and social connection in cardiovascular diseases potentially mediating accelerated biological aging. The present study aims to explore the association between social connection and biological aging as determinate by artificial intelligence-enabled electrocardiography (ECG). Methods: This is an observational retrospective cohort of adults aged ≥18 seen at Mayo Clinic from 2019-2022 who completed the social determinants of health questionnaire and had a 12-lead ECG within one year of completing the questionnaire. Five questions were asked to understand each patient’s social connection . The answers were scored to assess their level of social connection from socially isolated (score of 0) to socially connected (score of 4). The biological age was predicted from ECGs using the previously developed convolutional neural network (AI-ECG age). Delta age (Δage) was defined as AI-ECG age minus chronological age, where positive values reflect an older than expected age. Results: We included 280,323 subjects (chronological age 59.7±16.4 years, 51% female). The average AI-ECG age was 59.5±13.5 year. Better social connection status correlated with lower delta age (β=-0.33 (95%CI, -0.38 and -0.28, p<0.001, adjusted to chronological age and sex). Conversely, individuals reporting the least social connection were an average of 2 years older than expected whereas those with the most social connection were 2 years younger than expected by AI-ECG (Figure 1). Conclusions: Social connection is strongly associated with slower biological aging compared to chronological aging, independent of the conventional cardiovascular risk factors. This observation underscores the need to address social connection as a healthcare determinant.

Introduction: The physiological changes associated with aging have deleterious effects on cardiovascular function. In addition, increasing evidence showed the effect of exercise on improving cardiovascular health and reducing the aging process. The present study sought to demonstrate the association between exercise and biological age, estimated by our previously reported method using artificial intelligence-enabled electrocardiography (ECG). Methods: This retrospective observational study enrolled adults aged ≥18 years who have been evaluated at Mayo Clinic between 2019-2022 and completed the exercise questionnaire. The total time spent in moderate to strenuous exercise was calculated by multiplying the number of days engaging in exercise per week by the average minutes per day. The biological age was determined by applying our previously developed convolutional neural network model on the 12-lead ECG records (AI-ECG). The ECG records were within one year of subjects’ visits (in case of multiple visits, the closest one to the questionnaire was chosen). Positive Age-Gap (AI-ECG minus chronological age) reflects a person identified as being older by AI-ECG compared to his/her chronological age. Results: A total of 268,002 subjects (51% female) were recruited (mean age 59.7±16.4 years). Of those, 25.7% were not engaged in any exercise. The median day of engaging in exercise was 3 (Interquartile range, 2,5) per week, and the average time of exercising was 31.3±30 minutes/day. Age-Gap diminished progressively with increased duration of moderate to strenuous exercise (Figure 1). Linear regression analysis revealed exercise is an independent predictor of Age-Gap, (β= -0.043, 95%CI, -0.045 and -0.041, p<0.001). Conclusions: Engaging in moderate to strenuous exercise is associated with slower biological aging relative to chronological age as determined by AI-enabled ECG.

Introduction: Peripheral microvascular endothelial dysfunction (PMED) is a marker and precursor of atherosclerosis and is associated with an increased risk of cardiovascular events. The present study aims to identify the best cut-off value of PMED, assessed by the reactive hyperemia index, in predicting major adverse cardiovascular events (MACE). Additionally, we investigate whether integrating PMED to CHA2DS2-Vasc score improves the predicting accuracy of cardiovascular disease. Methods: this is a retrospective study of patients who underwent reactive hyperemia peripheral arterial tonometry (PAT). The optimal cut-off value of reactive hyperemia index associated with MACE was calculated using the area under the receiver-operating curve and the maximum Youden index. Traditional cardiovascular risk factors such as age, sex, congestive heart failure, hypertension, diabetes, stroke, vascular disease were determined to calculate the CHA2DS2-VASc score. MACE was defined as myocardial infarction, heart failure hospitalization, and cerebrovascular events. Results: 1,690 patients were enrolled (average age 51.1±13.9, 64.1% female). The optimal cut-off value of the reactive hyperemia index was 2.0 in the overall population and females and 2.17 in males. The risk of MACE during 10 (Interquartile range: 4,16) years of follow-up was 15.3%. Multivariable logistic regression revealed that PMED as an independent predictor of MACE (PMED: OR, 3.6, 95% CI, 2.6-4.9, p<0.001) (Table1). Furthermore, integrating PMED to CHA2DS2-VASc significantly improved the predictive accuracy (area under the curve, 0.747 vs. 0.708, p<0.001). Conclusion: PMED is a strong predictor of cardiovascular events. Non-invasive assessment of peripheral endothelial function may be useful in early detection and improving the stratification of high-risk patients for cardiovascular events.