Chao, Chieh‐Ju

Introduction: Unsupervised machine learning (ML) can provide insight into a dataset without significant expert time for annotation and labeling, but was never used to assess the heterogeneous MitraClip population. Hypothesis: We hypothesized that unsupervised k-means ML could identify prognostically-distinct phenogroups in MitraClip patients without a priori knowledge of the dataset. Methods: Patients who underwent MitraClip (June 2014-September 2020) at Mayo Clinic sites were identified from the Mayo institutional NCDR database for baseline and follow-up data. Variables with ≥ 50% missing data were excluded. A k-means algorithm was used for clustering analysis. Input variables were grouped according to 4 distinct k-means determined clusters. Kaplan-Meier survival analysis was used to assess the survival of each cluster. Results: A total of 389 consecutive patients were included in the final analysis, and 95 unique variables were used. The mean age was 80.3±8.7 years; 256 (65.8%) were male. The mean STS MV Replace score was 9.1±5.7. Fifty-five (14.5%) patients died during the mean follow duration (185 days). Kaplan-Meier analysis showed significant survival differences among clusters (Figure 1). The cluster (cluster 2, n=120) with best survival performance (all-cause mortality 3.3%) had features of non-calcified mitral leaflets, nonischemic cardiomyopathy, and less than moderate tricuspid regurgitation. Cluster 3 (n=66) had the worst survival performance (all-cause mortality 27.3%) and opposite features than cluster 2. Conclusions: Unsupervised ML can identify distinct phenotype clusters with prognostic significance in MitraClip patients. Patients with non-calcified mitral leaflets, nonischemic cardiomyopathy, and less than moderate tricuspid regurgitation are intrinsically different from other MitraClip patients and should be considered the potential optimal candidates.

Background/Introduction: More than moderate tricuspid regurgitation (TR) at baseline is associated with worse outcome in MitraClip patients. The presence of iatrogenic ASD (iASD) may cause right-sided volume overload and lead to adverse events. However, the real effects of iASD are not well-investigated in these patients who are vulnerable to right-sided volume overload. Methods: Patients with more than moderate TR who underwent a successful MitraClip procedure in the period from June 2014 to September 2020 were identified from the Mayo institutional NCDR database. Follow-up transthoracic echocardiography (TTE) at about 1 year after the procedure was used to determine the presence of iASD, and speckle-tracking strain analysis was done. Patients were grouped according to the presence of iASD (iASD+ group vs. iASD- group) for statistical analysis. Results: A total of 141 consecutive patients were included for the final analysis (iASD+ group n=44 and iASD- group n=97). The mean age was 79.3 ± 8.8 years, and 72.3% were male. Follow-up echocardiography and speckle-tracking strain data did not show a significant difference in either left or right ventricular function in conventional echocardiographic parameters and strain. LA reservoir strain (13.7 ± 6.9 vs 11.5±7.5, P=0.0418) was the only parameter with significant difference among the two groups. Details are summarized in Table 1 . Conclusion: The presence of iASD can decompress the left atrium, but does not affect left or right ventricular strain function in MitraClip patients with more than moderate baseline TR.

Background: Pectus excavatum (PE) deformity involves posterior depression of the sternum and adjacent costal cartilages. The relationship of CT/MRI chest cardiac compression indices used as indications for surgical repair of PE with echocardiographic findings and with improvement in cardiac chamber compression and function post PE repair is unknown. Methods: We evaluated right atrial (RA) size, tricuspid annulus (TA size, right ventricular (RV) outflow tract size as well as RV 2D strain on intra-operative trans-esophageal echocardiography (TEE) immediately pre and post surgical PE repair. Inspiratory and expiratory Haller Index (HI) and cardiac compression indices (CCI) were measured on pre op CT/MR scans (Figure). Offline measurement of chamber dimensions on TEE images was performed and Speckle tracking strain measurements were made using Syngo US Workplace software (Siemens). P<0.05 was considered significant. Results: 60 patients, 73% male, 27% female, age 33.6±10.3 yrs underwent PE repair following CT/MRI from 2010-2014 (Figure). There was a strong correlation between expiratory CT/MRI chest AP diameter and pre-op RA size (panel A). Pre op RA and TA compression on TEE inversely correlated with pre op RV global longitudinal strain rate(RVGLSR) (panels B & C). CCI predicted improvement in RA size post PE repair (panels D & E). In addition pre op RA size on TEE correlated with improvement in RVGLSR post PE repair surgery (panel F). Conclusion: In patients with PE deformity, pre surgical CCI correlated with right-sided cardiac chamber compression on pre op TEE. Severity of chest and cardiac compression also predicted magnitude of improvement in right-sided chamber size and RV longitudinal deformation post PE repair. Our findings provide insight regarding the beneficial effects of PE surgery on right heart chamber compression and improvement in RV function and the important role of intraoperative TEE for patients undergoing PE repair surgery.

Introduction: Baseline thrombocytopenia (TP) is a common condition in patients with acute coronary syndrome (ACS) and acute ischemic stroke and has been shown to increase mortality. The effect of baseline TP on cerebrovascular events following initial ACS event is not well studied. Methods: We retrospectively reviewed all patients identified from the institutional NCDR Chest Pain registry database at Mayo Clinic Arizona from Oct 2015 to Sep 2018. Patients were classified into TP (platelet <150) and control (platelet > 150) groups for clinical outcome (stroke/TIA and bleeding events) analysis. P-value < 0.05 is considered significant. Results: Five hundred and thirty-six patients were included for final analysis. Patient demographics and clinical outcomes are shown in Table 1. The rates of dual antiplatelet therapy (DAPT) prescription at discharge (TP vs. control: 68.1% and 75.4%, P=0.197), stroke/TIA (1.3% vs. 2.4%, P=1.000) and recurrent myocardial infarction (11.1% vs. 11.2%, P=1.000) were similar between the two groups. The TP group has more bleeding events compared to control (Figure 1). Conclusions: In patients with ACS, baseline TP does not affect stroke/TIA events but is associated with higher bleeding rate. The results could not be explained by the DAPT or anticoagulation use alone. Further studies are needed to investigate the pathophysiologic correlation of thrombocytopenia, DAPT, and stroke in ACS patients.

Introduction: Ischemic stroke (IS) causes substantial morbidity and mortality in patients undergoing percutaneous coronary intervention (PCI) with a 5 yr incidence ~ 3%. We sought the test the accuracy of Machine learning (ML) algorithms in predicting IS in patients undergoing PCI. Methods: Mayo Clinic CathPCI registry data were retrospectively analyzed from Jan 2003 - June 2018 including 21,872 patients who underwent PCI. The cohort was randomly divided into a training sample (75%, n=16404) and a unique test sample (25%, n=5468) prior to model generation. The risk prediction model was generated utilizing a random forest algorithm (RF model) on 188 unique variables to predict the risk of IS at 6-month, 1, 2, and 5-year post PCI. Conventional risk factors for stroke were used for logistic regression. The receiver operating characteristic (ROC) curve and area under the curve for the RF and logistic regression models were compared for the test cohort. Results: The mean age was 66.9 ± 12.4 years, and 71% were male. Patient demographics and outcomes are shown in Table 1 . The ROC area under the curve for the RF model was superior compared to the logistic regression model in predicting IS at 6 months, 1,2 and 5 yrs for the test cohort ( Figure 1 .) Conclusions: The RF model accurately predicts short and long term risk of IS and outperforms logistic regression analysis in patients undergoing PCI.

AbstractThe use of 3D technology has significantly improved the diagnostic accuracy of echocardiography by overcoming the limitation of 2D echocardiography. Transillumination 3D image post processing technique enhances shadows and contrast of cardiac structures with a movable virtual light source improving further the clarity and detail provided by conventional 3D imaging. In this report, we present 3 cases, one of mobile atherosclerotic aortic root plaque, another of small thrombi on ICD lead, and a third case of bicuspid aortic valve perforation due to infective endocarditis in whom TEE 3D transillumination further improved the diagnostic quality of conventional 3D imaging and lead to accurate clinical diagnosis.

Background: Identifying patients at a high risk of mortality post percutaneous coronary intervention (PCI) is of vital clinical importance. We investigated the utility of machine learning algorithms to predict short and intermediate-term risk of all-cause mortality in patients undergoing PCI. Methods: Patient-level demographics, clinical, electrocardiographic ,echocardiographic and angiographic data from January 2006 to December 2017 were extracted from the Mayo Clinic CathPCI registry and clinical records. For patients with multiple PCI events, data collected at the time of the index PCI was used for analysis. Patients who underwent bailout coronary artery bypass graft surgery (CABG) prior to discharge were excluded. 306 variables were incorporated into random forest machine learning model (RF) to predict all-cause mortality at 6 months and 1 year after PCI. Ten-fold cross-validation repeated five times was used to optimize the hyperparameters and estimate its external performance. The National Cardiovascular Data Registry (NCDR) based logistic regression model was used for comparison. The area under receiver operator characteristic curves (AUC) was calculated to assess the ability of the models to predict all-cause mortality. Results: A total of 17356 unique patients were included for the final analysis after excluding 165 patients who underwent CABG surgery during the index hospitalization. The mean age was 66.9 ± 12.5 years;71% were male. Indications for PCI were ST-elevation myocardial infarction (9.4%), non-ST elevation myocardial infarction (12.9%), unstable angina (17.7%), and stable angina (52.8%) in the cohort. In-hospital, 6-month & 1 year mortality rates were 1.9%,4.2% & 5.8% respectively. The RF model was superior to the NCDR model in predicting inhospital, 6-month, 1 year mortality (p<0.0001) ( Figure 1 ). Conclusion: Machine learning is superior to NCDR model in predicting short and intermediate risk of all-cause mortality post PCI.

Background: Left atrial appendage occlusion (LAAO) devices have successfully provided an alternative therapeutic option in patients with atrial fibrillation and high bleeding risk. However, patients with thrombocytopenia (TP) were underrepresented in the milestone trials, and the optimal strategy of postprocedural antithrombotic therapy in this group of patients remains unclear. Methods: Patients were identified from the National Cardiac Database Registry - LAAO database at all three Mayo Clinic sites in the period from 1/2016-10/2019. Patients were further divided into TP (platelet &lt; 150 x 10^9/L) and control (platelet &gt; 150 x 10^9 /L) groups for clinical outcome analysis. Outcome endpoints include composite of bleeding (GI bleeding, hemorrhagic stroke, and other non-intracranial hemorrhage) and composite thrombotic events (device thrombus, ischemic stroke, TIA and undetermined stroke). Results: A total of 249 consecutive patients were included in the final analysis. The mean age was 76.7 ± 7.2 years, and 169 (67.9%) were male; 242 (97.2%) were white. The mean CHA2DS2-VASc score was 5.3 ±1.5, and the HAS-BLED score was 3.0 ± 1.1. TP at baseline was present in 74 (29.7%) patients. The median follow-up time was 6.8 months. The use of post-procedural antithrombotic regimens was similar between the two groups (Table 1). When comparing the TP group to control, there was no significant difference in composite bleeding events (10.8% vs. 8.0%, P = 0.069) and thrombotic events (2.7% vs. 2.3%, P= 0.170). Conclusions: The presence of baseline TP does not significantly increase post-procedural bleeding risk in atrial fibrillation/atrial flutter patients who underwent an LAAO occlusion procedure with the Watchman device (Boston Scientific). This group of patients can be treated with the same antithrombotic regimen as patients with normal platelet levels. Future studies are still warranted to determine the optimal antithrombotic regimen.

Background Carotid intima-media thickness (CIMT) is regarded as a controversial risk marker for cardiovascular disease (CVD). We aimed to evaluate the role of CIMT and carotid plaque progression as predictors for the progression of coronary plaque and compositions. Methods In the Garlic 4 study, asymptomatic patients with intermediate CVD risk (Framingham risk score 6–20%) were recruited for a serial carotid ultrasound, and coronary artery calcium score (CAC)/coronary computed tomography angiography (CCTA) studies for subclinical atherosclerosis at a baseline and 1 year. The association between progression of quantitatively measured coronary plaque compositions and the progression of CIMT/carotid plaque was analyzed. A P value <0.05 is considered as statistically significant. Results Forty-seven consecutive patients were included. The mean age was 58.5 ± 6.6 years, and 69.1 % were male. New carotid plaque appeared in 34.0 % (n = 16) of participants, and 55.3 % (n = 26) of subjects had coronary plaque progression. In multilinear regression analysis, adjusted by age, gender, and statin use, the development of new carotid plaque was significantly associated with an increase in noncalcified coronary plaque [β (SE) 2.0 (0.9); P = 0.025] and necrotic core plaque (1.7 (0.6); P = 0.009). In contrast, CIMT progression was not associated with the progression of coronary plaque, or coronary artery calcium (CAC) (P = NS). Conclusion Compared to CIMT, carotid plaque is a better indicator of coronary plaque progression. The appearance of a new carotid plaque is associated with significant progression of necrotic core and noncalcified plaque, which are high-risk coronary plaque components.

AbstractIntroductionThe right ventricle (RV) strain measured by speckle tracking (RVS) is an echocardiographic parameter used to assess RV function. We compared RVS to RV fractional area change (FAC%), tricuspid annular plane systolic excursion (TAPSE) and Doppler tissue imaging‐derived peak systolic velocity (Sʹ) in the assessment of right ventricular (RV) systolic function measured using cardiac magnetic resonance imaging (MRI).MethodsWe enrolled consecutive patients who underwent cardiac MRI between Jan 2012 and Dec 2017 and a transthoracic echocardiogram (TTE) within 1 month of the MRI with no interval event. Baseline clinical characteristics and MRI parameters were extracted from chart review. Echocardiographic parameters were measured prospectively. TTE parameters including RVS, TAPSE, Sʹ, and FAC% were tested for accuracy to identify impaired RV EF (EF < 45% & <30%) using receiver operator curves.ResultsThe study cohort included 500 patients with mean age 55 years ± 18 and peak tricuspid regurgitation velocity 2.7 ± 1.4 m/s. The area under ROC for RVS was 0.69 (95% CI 0.63–0.75) and 0.78 (95% CI 0.70–0.88) to predict RVEF < 45% & RVEF < 30%, respectively. The RV FAC% had second highest accuracy of predicting RVEF among all the TTE parameters tested in study.ConclusionRight ventricular strain is the most accurate echocardiographic method to detect impaired right ventricular systolic function when using MRI as the gold standard.