Agasthi, Pradyumna

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.

Background Brugada syndrome is an inherited cardiac channelopathy associated with major arrhythmic events (MAEs). The presence of a positive family history of sudden cardiac death (SCD) as a risk predictor of MAE remains controversial. We aimed to examine the association between family history of SCD and MAEs stratified by age of SCD with a systematic review and meta‐analysis. Methods and Results We searched the databases of MEDLINE and EMBASE from January 1992 to January 2020. Data from each study were combined using the random‐effects model. Fitted metaregression was performed to evaluate the association between the age of SCD in families and the risk of MAE. Twenty‐two studies from 2004 to 2019 were included in this meta‐analysis involving 3386 patients with Brugada syndrome. The overall family history of SCD was not associated with increased risk of MAE in Brugada syndrome (pooled odds ratio [OR], 1.11; 95% CI, 0.82–1.51; P =0.489, I 2 =45.0%). However, a history of SCD in family members of age younger than 40 years of age did increase the risk of MAE by ≈2‐fold (pooled OR, 2.03; 95% CI, 1.11–3.73; P =0.022, I 2 =0.0%). When stratified by the age of cut point at 50, 45, 40, and 35 years old, a history of SCD in younger family member was significantly associated with a higher risk of MAE (pooled OR, 0.49, 1.30, 1.51, and 2.97, respectively; P =0.046). Conclusions A history of SCD among family members of age younger than 40 years was associated with a higher risk of MAE.

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.

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.

Abstract Background Coronary artery disease (CAD) and atrial fibrillation (AF) are commonly associated. Co-treatment with multiple anti-thrombotic agents can increase the risk of bleeding. Purpose We sought to evaluate patient-centered outcomes in patients with AF on double therapy with direct oral anticoagulants (DOACs) compared to patients with standard triple therapy, [a vitamin K antagonist (VKA) plus dual antiplatelet therapy]. Methods We performed an extensive systematic review of the literature and meta-analysis of randomized controlled trials reporting outcomes of patients receiving double therapy with DOACs compared to triple therapy with VKAs in patients with AF undergoing percutaneous coronary intervention (PCI). Patient-centered outcomes were the International Society of Thrombosis and Hemostasis (ISTH) major or clinically relevant non-major bleeding (CRNB), all-cause mortality, major adverse cardiovascular events (MACE), myocardial infarction, stent thrombosis, and stroke. Results Four randomized controlled trials (9602 patients) met our inclusion criteria. Compared to VKAs, DOACs were associated with significantly lower ISTH major bleeding/ CRNB (RR - 0.75, 95% CI: 0.67-0.82, p &lt; 0.00001, I2 = 11%). There were no statistically significant differences in the efficacy outcomes, including myocardial infarction (RR- 0.99, 95% CI :0.79-1.25, p = 0.96, I2 = 0%), stent thrombosis (RR - 0.97, 95% CI: 0.6-1.55, p = 0.89, I2 = 0%), ischemic stroke (RR - 0.76, 95% CI: 0.5-1.15, p = 0.19, I2 = 0%), all-cause mortality (RR - 1.06, 95% CI: 0.85-1.31, p = 0.61, I2 = 0%) and MACE (RR - 1.06, 95% CI: 0.91-1.22, p = 0.97, I2 = 0%). Conclusion Compared with triple therapy with VKAS, double therapy with DOACs is associated with a reduced risk of bleeding and is as effective in patients with AF undergoing PCI. Abstract Figure.

Introduction: The right ventricle (RV) strain measured by speckle tracking (RVS) is a novel method of assessing RV function. We compared RVS to RV fractional area change (FAC%), tricuspid annular peak systolic excursion (TAPSE) and Doppler tissue imaging-derived peak systolic velocity (S’) in the assessment of right ventricular (RV) systolic function measured using cardiac magnetic resonance imaging (MRI). Methods: We enrolled consecutive patients who underwent cardiac MRI between Jan 2012- 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, S’ and FAC% were tested for accuracy to identify impaired RV EF (EF <45% & <30%) using receiver operator curves. Results: The study cohort included 500 patients with mean age 55 yr ± 18 and right ventricular systolic pressure 33.7 ± 13.6 mmHg. 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. Conclusion: Right ventricular strain is the most accurate echocardiographic method to detect impaired right ventricular systolic function when using MRI as the gold standard.