OBJECTIVE:To evaluate the midterm survival, clinical, and hemodynamic outcomes of the On-X mechanical mitral valve, based on the 5-year results of the Prospective Randomized On-X Anticoagulation Clinical Trial (PROACT). METHOD:PROACT Mitral was a multicenter study evaluating 401 patients who underwent mitral valve replacement (MVR) with either Standard or Conform-X On-X mitral valves, comparing low-dose and standard-dose warfarin. Here we report prespecified secondary outcomes of survival, New York Heart Association (NYHA) functional classification, and valve hemodynamics as assessed by core lab-adjudicated echocardiography at 1, 3, and 5 years in the pooled population. RESULTS:Actuarial survival was 99.7% at 1 year, 95.1% at 3 years, and 92.4% at 5 years, with no significant difference between the Standard and Conform-X cuffs. Hemodynamic analysis revealed a mean transvalvular pressure gradient (MG) of 4.6 ± 2.0 mm Hg at 1 year, with no interaction between valve size and patient body surface area. MG values were consistent over time. Quality of life improved with 96.6% of patients in NYHA class I or II at the latest available follow-up of 3 or 5 years. There were no significant differences in survival, clinical, or hemodynamic outcomes between valve sizes. CONCLUSIONS:The On-X mechanical mitral valve demonstrated favorable survival, stable hemodynamics, and enhanced quality of life up to 5 years postimplantation. Derived from high-quality, rigorous randomized trial data, these findings can guide decision making in young patients requiring MVR.

Objective: Prolonged mechanical ventilation after cardiac surgery significantly increases morbidity and mortality. The aim of this study is to establish the role of diaphragmatic pacing to decrease mechanical ventilation burden in high-risk patients undergoing cardiac surgery. Methods: This is a prospective, randomized trial of temporary diaphragmatic pacing electrode use in patients undergoing cardiac surgery (NCT04899856). Prognostic enrichment strategy was used to identify patients at higher risk of prolonged mechanical ventilation by having inclusion criteria of prior open cardiac surgery, left ventricular ejection fraction less than 30%, history of stroke, intra-aortic balloon pump, or history of chronic obstructive pulmonary disease. Two electrodes were placed in each hemidiaphragm intraoperatively. On arrival to the intensive care unit, patients were randomized to immediate diaphragmatic pacing or standard of care. Results: Forty patients received implants, with 19 in the treatment group and 21 in the standard of care group. Only 1 patient in the treatment group was on mechanical ventilation at 24 hours versus 4 patients in the standard of care group, resulting in a relative risk reduction of 71% being on mechanical ventilation at 24 hours postoperatively. Predictive enrichment strategy was used to identify patients most likely to respond to therapy of diaphragmatic pacing. In this analysis, median time on mechanical ventilation was 17.7 hours (interquartile range, 8.3-23.4) for the 15 patients in the standard of care group and 9.4 hours (interquartile range, 7.14-12.5) for the 13 patients in the treatment group, for an improvement of 8 hours with diaphragm pacing (P < .05). Conclusions: Temporary diaphragmatic pacing improved weaning from mechanical ventilation by 8 hours with a significant reduction of prolonged mechanical ventilation. Multicenter randomized trials confirming diaphragmatic pacing as an Enhanced Recovery After Surgery tool to decrease mechanical ventilation may reduce length of stay, postoperative infections, and additive costs.

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OBJECTIVE:To evaluate whether transcatheter or surgical aortic valve replacement (TAVR or SAVR) affects clinical and haemodynamic outcomes in symptomatic patients with moderately-severe aortic stenosis (AS).METHODS:Echocardiographic evidence of severe AS for enrolment in the Evolut Low Risk trial was based on site-reported measurements. For this post hoc analysis, core laboratory measurements identified patients with symptomatic moderately-severe AS (1.0<aortic valve area (AVA)<1.5 cm2, 3.0<peak velocity<4.0 m/s and 20≤mean gradient (MG) <40 mm Hg). Clinical outcomes were reported through 2 years.RESULTS:Moderately-severe AS was identified in 113 out of 1414 patients (8%). Baseline AVA was 1.1±0.1 cm2, peak velocity 3.7±0.2 m/s, MG 32.7±4.8 mm Hg and aortic valve calcium volume 588 (364, 815) mm3. Valve haemodynamics improved following TAVR (AVA 2.5±0.7 cm2, peak velocity 1.9±0.5 m/s and MG 8.4±4.8 mm Hg; p<0.001 for all) and SAVR (AVA 2.0±0.6 cm2, peak velocity 2.1±0.4 m/s and MG 10.0±3.4 mm Hg; p<0.001 for all). At 24 months, the rates of death or disabling stroke were similar (TAVR 7.7% vs SAVR 6.5%; p=0.82). Kansas City Cardiomyopathy Questionnaire overall summary score assessing quality of life improved from baseline to 30 days after TAVR (67.0±20.6 to 89.3±13.4; p<0.001) and SAVR (67.5±19.6 to 78.3±22.3; p=0.001).CONCLUSIONS:In symptomatic patients with moderately-severe AS, AVR appears to be beneficial. Determination of the clinical and haemodynamic profile of patients who can benefit from earlier isolated AVR needs further investigation in randomised clinical trials.

ObjectiveWe performed a post hoc analysis of the Evaluation of XIENCE versus Coronary Artery Bypass Surgery for Effectiveness of Left Main Revascularization (EXCEL) trial to determine the effect an on-versus off-pump strategy had on outcomes when compared with percutaneous coronary intervention.MethodsAll randomized patients in EXCEL (n = 1905) were included. The outcomes of interest were the primary end point composite of death from any cause, stroke, or myocardial infarction; the composite study end point or ischemia-driven revascularization; and the rate of death from any cause at 5 years. Event rates were based on Kaplan–Meier estimates in time-to-first-event analyses.ResultsPropensity matching resulted in groups of 1142 patients (571 each) for on-pump coronary artery bypass grafting versus percutaneous coronary intervention and 472 patients (236 each) for off-pump coronary artery bypass grafting versus percutaneous coronary intervention. In the on-pump coronary artery bypass grafting versus percutaneous coronary intervention matched groups, the composite end point was similar (18.0% vs 22.1%, P = .19) and the composite end point or ischemia-driven revascularization (23.3% vs 31.0%, P = .01) was lower, and mortality (7.6% vs 11.8%, P = .025) was lower in the on-pump coronary artery bypass grafting group at 5 years. In the off-pump coronary artery bypass grafting versus percutaneous coronary intervention matched groups, the composite end point (19.4% vs 22.2%, P = .47), composite end point or ischemia-driven revascularization (25.9% vs 34.2%, P = .07), and mortality (12.5% vs 14.2%, P = .59) were similar at 5 years.ConclusionsIn the EXCEL trial, on-pump coronary artery bypass grafting was associated with a decreased 5-year rate of the composite outcome of death, stroke, myocardial infarction, or ischemia-driven revascularization, and decreased mortality when compared with percutaneous coronary intervention, whereas outcomes of off-pump coronary artery bypass grafting were similar to percutaneous coronary intervention.

BACKGROUND:We investigated outcomes of coronary artery bypass grafting (CABG) with endoscopic vein harvest (EVH) vs open vein harvest (OVH) within the Evaluation of XIENCE Versus CABG (EXCEL) trial.METHODS:All patients in EXCEL randomized to CABG were included in this study. For this analysis, the primary end points were ischemia-driven revascularization (IDR) and graft stenosis or occlusion at 5 years. Additional end points were as follows: a composite of death from any cause, stroke, or myocardial infarction; bleeding; blood product transfusion; major arrhythmia; and infection requiring antibiotics. Event rates were based on Kaplan-Meier estimates in time-to-first-event analyses.RESULTS:Of the 957 patients randomized to CABG, 686 (71.7%) received at least 1 venous graft with 257 (37.5%) patients in the EVH group and 429 (62.5%) patients in the OVH group. At 5 years, IDR was higher (11.5% vs 6.7%; P = .047) in the EVH group. At 5 years, rates of graft stenosis or occlusion (9.7% vs 5.4%; P = .054) and the primary end point (17.4% vs 20.9%; P = .27) were similar. In-hospital bleeding (11.3% vs 13.8%; P = .35), in-hospital blood product transfusion (12.8% vs 13.1%; P = .94), and infection requiring antibiotics within 1 month (13.6% vs 16.8%; P = .27) were similar between EVH and OVH patients. Major arrhythmia in the hospital (19.8% vs 13.5%; P = .03) and within 1 month (21.8% vs 15.4%; P = .03) was higher in EVH patients.CONCLUSIONS:IDR at 5 years was higher in the EVH group. EVH and OVH patients had similar rates of graft stenosis or occlusion and the composite of death, stroke, or myocardial infarction at 5 years.

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BACKGROUND:Death in high- and intermediate-risk patients after self-expanding transcatheter (TAVR) and surgical aortic valve replacement (surgery) differed in mechanisms and timing. In both risk groups, 1-year all-cause mortality was lower in TAVR than in surgery patients. The differences in mechanism and timing of death in low-risk patients has not been studied. This report explores the mechanisms of death during 3 time periods; 0 to 30 days (early), 31 to 120 days (recovery), and 121 to 365 days (late). METHODS:We retrospectively examined the mechanisms and timing of death following TAVR or surgery in the randomized Evolut Low Risk Trial. Patients were enrolled between March 2016 and November 2018 from 86 designated TAVR centers. Mechanisms of death were categorized as due to technical reasons, failure to repair, complications linked to death, failure to recover or other. RESULTS:All-cause mortality at 1 year was 2.2% for TAVR and 2.8% for surgery, p = 0.44. Early deaths included 3 TAVR patients, all due to technical reasons, and 8 surgery patients (1 technical, 5 complications and 2 failed to recover). Recovery period deaths included 6 TAVR patients (4 complications, 1 failed to recover and 1 other), and 1 surgery patient from complications of valve endocarditis. Late period deaths included 6 TAVR patients and 9 surgery patients, primarily due to complications. CONCLUSIONS:In this low-risk study cohort, no patient died from failure to repair the valve; reduction in procedural complications in the TAVR and surgery groups remain opportunities for further improvement in outcomes. Clinical Trial Registrations (clinicaltrials.gov): NCT02701283 (Evolut Low Risk).

Increasing regionalization of cardiac surgery may lead to fragmentated care if readmissions do not occur to the index hospital where the initial surgery took place. The magnitude and adverse effects of readmissions to non-index hospitals after cardiac surgery are unknown. We sought to determine the prevalence and impact of readmissions to index versus non-index hospitals. In this multicenter, nationally representative sample of adults undergoing cardiac surgery, retrospective analyses were performed using the 2016 through 2018 Nationwide Readmissions Database (NRD). Descriptive analyses were performed to determine 30-day readmission characteristics, including timing, cost, and outcomes. Multivariate logistic regression was used to identify factors associated with index versus non-index readmissions. Additional regression models were used to identify differences in mortality, major complications, subsequent readmissions, and costs between readmissions to index versus non-index hospitals. From 53 million records in the NRD, a total of 448,351 patients were included in the study (mean [SD] age, 65 [12] years; 132,592 [29.6%] female). Index procedures included: isolated CABG (245,088 [54.7%]), isolated valve(s) (90,011 [20.1%]), CABG and valve (40,169 [9.0%]), aorta with or without CABG or valve (21,488 [4.8%]), heart transplant (2,255 [0.5%]), ventricular assist device (19,026 [4.2%]), and all others (30,314 [6.8%]). The overall 30-day readmission rate was 11.7%. Of the 52,329 first readmissions, 23.4% (13,705) were to non-index hospitals (Figure). Patients transferred to an index hospital during an initial non-index readmission were included in the index readmission category (orange in Figure). Factors known at the time of discharge from the index hospitalization that independently predicted a non-index readmission included: type of procedure, hospital location (rural vs. urban), and patient location (rural vs. urban). After risk adjustment, patients readmitted to non-index hospitals had 37.4% higher odds of mortality (OR, 1.37; 95% CI, 1.22-1.55), and 29.3% higher odds of having a major complication (OR, 1.29; 95% CI, 1.16-1.44). Subsequent readmissions and hospital costs were no different between groups. In this nationwide analysis, approximately one in four readmissions after cardiac surgery were to non-index hospitals. Non-index readmissions were associated with higher mortality and morbidity compared to index readmissions likely due to loss of continuity of care. Interventions targeted at reducing non-index readmissions and improving care coordination are warranted.

OBJECTIVES This study was to test the hypotheses that: 1) when using phase analysis, repetitive Wannabe re-entry produces a phase singularity point (i.e., a rotor); and 2) the location of the stable rotor is dose to the focal source. BACKGROUND Recent contact mapping studies in patients with persistent atrial fibrillation (AF) demonstrated that phase analysis produced a different mechanistic result than classical activation sequence analysis. Our studies in patients with persistent AF showed that focal sources sometimes produced repetitive Wannabe re-entry, that is, incomplete reentry. METHODS During open heart surgery, we recorded activation from both atria simultaneously using 510 to 512 electrodes in 12 patients with persistent AF. We performed activation sequence mapping and phase analyses on 4 s of mapped data. For each detected stable rotor (>2 full rotations [720 degrees] recurring at the same site), the corresponding activation patterns were examined from the activation sequence maps. RESULTS During AF, phase singularity points (rotors) were identified in both atria in all patients. However, stable phase singularity points were only present in 6 of 12 patients. The range of stable phase singularity points per patient was 0 to 6 (total 14). Stable phase singularity points were produced due to repetitive Wannabe re-entry generated from a focal source or by passive activation. A conduction block sometimes created a stable phase singularity point (n = 2). The average distance between a focal source and a stable rotor was 0.9 + 0.3 cm. CONCLUSIONS Repetitive Wannabe re-entry generated stable rotors adjacent to a focal source. No true re-entry occurred. (C) 2021 by the American College of Cardiology Foundation.

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BACKGROUNDProlonged mechanical ventilation (PMV) after cardiac surgery occurs in 12% of patients, and significantly increases morbidity and mortality. Diaphragm pacing (DP) decreases ventilation times by 64% in other patient groups. We investigated the feasibility and outcomes of DP in urgent cardiac surgeries to decrease ventilator burden during the COVID-19 pandemic.METHODS AND RESULTSThis pilot study is an open-label FDA (IDE# G170294) prospective trial of temporary DP electrode use in high risk cardiac surgery patients (ClinicalTrials.gov Identifier–NCT04309123). Prior to sternotomy closure, the pleural space is opened, two electrodes (Figure 1) are placed in each diaphragm muscle, and the wires are tunneled percutaneously. The electrodes record diaphragm burst electromyography (dEMG) continuously for the first 24 hours and then once daily (Figure 2). In PMV patients (MV>24 hours), DP is initiated to prevent diaphragm atrophy and ventilator induced diaphragm dysfunction. The primary outcome was incidence of serious device related adverse events. The secondary outcome was time on MV. From 4/2/20–6/25/20, 44 patients were consented, 32 were implanted, and 12 were not. PMV was required in 10 patients implanted and 4 not implanted. There were no serious adverse events related to DP electrode implantation, all stimulated patients had improved ventilation and diaphragm function, and all electrodes were removed successfully. Criteria that best predicted PMV were: IABP, history of TIA or CVA, COPD, LVEF < 20%, and prior open-heart surgery. Using these criteria, the median time on mechanical ventilation in the first 120 hours was 35.7% versus 80.0% for the stimulated and non-stimulated groups, respectively.CONCLUSIONTemporary DP electrode placement during cardiac surgery is feasible and safe. DP improved diaphragm function and ventilation, and increased the likelihood of extubation by 48 hours. These results provide a catalyst for a prospective randomized controlled trial to decrease the MV burden in an enhanced recovery after surgery (ERAS) protocol. Prolonged mechanical ventilation (PMV) after cardiac surgery occurs in 12% of patients, and significantly increases morbidity and mortality. Diaphragm pacing (DP) decreases ventilation times by 64% in other patient groups. We investigated the feasibility and outcomes of DP in urgent cardiac surgeries to decrease ventilator burden during the COVID-19 pandemic. This pilot study is an open-label FDA (IDE# G170294) prospective trial of temporary DP electrode use in high risk cardiac surgery patients (ClinicalTrials.gov Identifier–NCT04309123). Prior to sternotomy closure, the pleural space is opened, two electrodes (Figure 1) are placed in each diaphragm muscle, and the wires are tunneled percutaneously. The electrodes record diaphragm burst electromyography (dEMG) continuously for the first 24 hours and then once daily (Figure 2). In PMV patients (MV>24 hours), DP is initiated to prevent diaphragm atrophy and ventilator induced diaphragm dysfunction. The primary outcome was incidence of serious device related adverse events. The secondary outcome was time on MV. From 4/2/20–6/25/20, 44 patients were consented, 32 were implanted, and 12 were not. PMV was required in 10 patients implanted and 4 not implanted. There were no serious adverse events related to DP electrode implantation, all stimulated patients had improved ventilation and diaphragm function, and all electrodes were removed successfully. Criteria that best predicted PMV were: IABP, history of TIA or CVA, COPD, LVEF < 20%, and prior open-heart surgery. Using these criteria, the median time on mechanical ventilation in the first 120 hours was 35.7% versus 80.0% for the stimulated and non-stimulated groups, respectively. Temporary DP electrode placement during cardiac surgery is feasible and safe. DP improved diaphragm function and ventilation, and increased the likelihood of extubation by 48 hours. These results provide a catalyst for a prospective randomized controlled trial to decrease the MV burden in an enhanced recovery after surgery (ERAS) protocol.

HomeCirculation: Arrhythmia and ElectrophysiologyVol. 14, No. 3Machine Learning Algorithms for Prediction of Permanent Pacemaker Implantation After Transcatheter Aortic Valve Replacement Free AccessReview ArticlePDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyRedditDiggEmail Jump toSupplementary MaterialsFree AccessReview ArticlePDF/EPUBMachine Learning Algorithms for Prediction of Permanent Pacemaker Implantation After Transcatheter Aortic Valve Replacement Takahiro Tsushima, MD Sadeer Al-Kindi, MD Fahd Nadeem, MD Guilherme F. Attizzani, MD Yakov Elgudin, MD, PhD Alan Markowitz, MD Marco A. Costa, MD, PhD Daniel I. Simon, MD Mauricio S. Arruda, MD Judith A. Mackall, MD Sergio G. ThalMD Takahiro TsushimaTakahiro Tsushima https://orcid.org/0000-0003-0190-7555 Department of Medicine (T.T.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH. , Sadeer Al-KindiSadeer Al-Kindi https://orcid.org/0000-0002-1122-7695 Division of Cardiology, Department of Medicine (S.A.-K., F.N., G.F.A., M.A.C., D.I.S., M.S.A., J.A.M., S.G.T.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH. , Fahd NadeemFahd Nadeem https://orcid.org/0000-0001-9473-6243 Division of Cardiology, Department of Medicine (S.A.-K., F.N., G.F.A., M.A.C., D.I.S., M.S.A., J.A.M., S.G.T.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH. , Guilherme F. AttizzaniGuilherme F. Attizzani Division of Cardiology, Department of Medicine (S.A.-K., F.N., G.F.A., M.A.C., D.I.S., M.S.A., J.A.M., S.G.T.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH. , Yakov ElgudinYakov Elgudin Division of Cardiac Surgery, Department of Surgery (Y.E., A.M.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH. , Alan MarkowitzAlan Markowitz https://orcid.org/0000-0003-0101-5047 Division of Cardiac Surgery, Department of Surgery (Y.E., A.M.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH. , Marco A. CostaMarco A. Costa Division of Cardiology, Department of Medicine (S.A.-K., F.N., G.F.A., M.A.C., D.I.S., M.S.A., J.A.M., S.G.T.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH. , Daniel I. SimonDaniel I. Simon https://orcid.org/0000-0002-3386-7650 Division of Cardiology, Department of Medicine (S.A.-K., F.N., G.F.A., M.A.C., D.I.S., M.S.A., J.A.M., S.G.T.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH. , Mauricio S. ArrudaMauricio S. Arruda Division of Cardiology, Department of Medicine (S.A.-K., F.N., G.F.A., M.A.C., D.I.S., M.S.A., J.A.M., S.G.T.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH. , Judith A. MackallJudith A. Mackall https://orcid.org/0000-0003-4324-0226 Division of Cardiology, Department of Medicine (S.A.-K., F.N., G.F.A., M.A.C., D.I.S., M.S.A., J.A.M., S.G.T.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH. , Sergio G. ThalSergio G. Thal Correspondence to: Sergio G. Thal, MD, Electrophysiology, University Hospitals Cleveland Medical Center, Clinical Associate Professor, Department of Medicine, Case Western Reserve University, 11100 Euclid Ave Cleveland, OH 44106. Email E-mail Address: [email protected] Division of Cardiology, Department of Medicine (S.A.-K., F.N., G.F.A., M.A.C., D.I.S., M.S.A., J.A.M., S.G.T.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH. Originally published9 Mar 2021https://doi.org/10.1161/CIRCEP.120.008941Circulation: Arrhythmia and Electrophysiology. 2021;14:e008941Atrioventricular block requiring permanent pacemaker (PPM) implantation remains an important complication after transcatheter aortic valve replacement (TAVR), and the risk stratification is essential to identify the subset of patients requiring the new PPM implantation beforehand. However, an accurate risk prediction is not established yet. Recently, machine learning (ML) technique which is a scientific discipline focusing on pattern recognitions is utilized for developing prediction models in clinical medicine, and the previously reported ML-based models demonstrated significantly high predictive accuracy.1,2 The aim of this study is to evaluate the performance of ML-based algorithms for predicting post-TAVR PPM implantation.This is a single-center retrospective study of consecutive patients who underwent TAVR from March 10, 2011 to October 8, 2018 (derivation cohort, group A) and a prospective cohort of TAVR patients between October 9, 2018 and November 9, 2019 (validation cohort, group B), at University Hospitals Cleveland Medical Center. This study utilized data extracted from TAVR research registry that was approved by an institutional review board at University Hospitals Cleveland Medical Center. All patients provided signed informed consent for the data collection. Patients with preexisting cardiac implantable electronic device were excluded from this study. The detailed information of ML analysis was summarized in the Data Supplement. In patients with post-TAVR PPM implantation who had available data on right ventricular pacing burden (n=132), we also evaluated whether these ML models (trained on PPM need) can predict significant right ventricular burden (≥40%) at 1 month by combining training and testing datasets. We considered right ventricular pacing burden ≥40% at 1 month after cardiac implantable electronic device implantations to be significant based on prior literature.3 The data that support the findings of this study are available from the corresponding author upon reasonable request.A total of 888 patients were ultimately included in group A, and 272 patients were in group B. In group A, 184 patients (20.7%) required new PPM, and the major indications were complete heart block in 70.1% and new left bundle branch block with subsequent high-grade atrioventricular block in 23.4%. In group B, 38 patients (14.0%) required PPM similarly for complete heart block in 71.1% and new left bundle branch block in 26.3%, respectively. The baseline characteristics of patients were summarized in Table I in the Data Supplement. Both preprocedural right bundle branch block and atrioventricular block were significantly associated with the new PPM implantation in both groups.Regarding the ML-model performances, Figure shows the classifier accuracy in both groups, and Table II in the Data Supplement summarized other model parameters. In group A, the model accuracy ranged from 59% to 69%, with sequential minimal optimization, simple logistic regression (SLR), and locally weighted learner (LWL)–based models demonstrating highest results (69%, 68%, and 68%, respectively). In group B, the model accuracy ranged between 55% and 75%, with SLR, LWL, and sequential minimal optimization–based classifiers demonstrating the best performance (75%, 74%, and 73%, respectively). Both SLR and LWL-based models achieved the highest area under curve receiver operating characteristics (AUCROC), 0.82. In group B, we also evaluated the performance of our previously reported prediction model that was extracted with the conventional multivariate logistic regression analysis and it also showed a high diagnostic accuracy (AUCROC, 0.81).3 We also found both SLR and LWL ML models modestly predicted significant right ventricular pacing burden at 1 month (AUCROC, 0.62 and 0.66, accuracy 61% and 67%, respectively).Download figureDownload PowerPointFigure. Accuracy of various machine learning classifiers in derivation and validation cohort (group A and B). LWL indicates locally weighted learner; REP, reduced error pruning; and SMO, sequential minimal optimization.Two unpublished studies reported the performance ok ML models to predict post-TAVR PPM implantation.4,5 Agasthi et al4 used 964 patients, and Gradient Boosting classifier showed modest discrimination (AUCROC of 0.66). Truong et al5 also used 701 patients, and the Random Forest demonstrated high prediction (balanced accuracy, 79%; F1 score, 0.62; and AUCROC, 0.88). In comparison to these studies, we utilized larger patient sample (n=1390) and ML-based classifiers (n=14). The internally validated results further supported ML-based classifiers can predict the incidence of the post-TAVR PPM accurately. However, SLR is one of the classical methods, and most ML algorithms did not outperform conventional methods in our present study. The current ML-algorism is still an imperfect science and clinicians should use appropriate ML-classifiers based on each dataset characteristic.There are some limitations. First, this is a single- center retrospective study, and the prediction models were extracted from our older cohort. Second, the indication for post-TAVR PPM was not established clearly in the beginning of TAVR era, and the limited experience may cause unnecessary PPM implantations. However, such a phenomenon was only for the early cases in our institution and it should not affect the diagnostic accuracy of our ML models entirely. Finally, the difference between utilized TAVR valves and preprocedural risk of adult cardiac surgery might affect the outcome.In conclusion, ML algorithms can predict the risk of post-TAVR PPM implantation accurately and both SLR and LWL-based classifiers achieved high performance in this study. A prospective or multicenter external validation should be undertaken.Nonstandard Abbreviations and AcronymsAUCROCarea under curve receiver operating characteristicsLWLlocally weighted learnerMLmachine learningPPMpermanent pacemakerSLRsimple logistic regressionTAVRtranscatheter aortic valve replacementSources of FundingNone.Disclosures Dr Attizzani is a consultant and is on the advisory board of Medtronic. Dr Simon has received honoraria for work as a course director from Medtronic. Dr Mackall has received consulting honoraria from Abbott. The other authors report no conflicts.Footnotes*T. Tsushima and S. Al-Kindi contributed equally as first authorsThe Data Supplement is available at https://www.ahajournals.org/doi/suppl/10.1161/CIRCEP.120.008941.For Sources of Funding and Disclosures, see page 371.Correspondence to: Sergio G. Thal, MD, Electrophysiology, University Hospitals Cleveland Medical Center, Clinical Associate Professor, Department of Medicine, Case Western Reserve University, 11100 Euclid Ave Cleveland, OH 44106. Email sergio.[email protected]orgReferences1. Deo RC. Machine learning in medicine.Circulation. 2015; 132:1920–1930. doi: 10.1161/CIRCULATIONAHA.115.001593LinkGoogle Scholar2. Hernandez-Suarez DF, Kim Y, Villablanca P, Gupta T, Wiley J, Nieves-Rodriguez BG, Rodriguez-Maldonado J, Feliu Maldonado R, da Luz Sant'Ana I, Sanina C, et al.. Machine learning prediction models for in-hospital mortality after transcatheter aortic valve replacement.JACC Cardiovasc Interv. 2019; 12:1328–1338. doi: 10.1016/j.jcin.2019.06.013CrossrefMedlineGoogle Scholar3. Tsushima T, Nadeem F, Al-Kindi S, Clevenger JR, Bansal EJ, Wheat HL, Kalra A, Attizzani GF, Elgudin Y, Markowitz A, et al.. Risk prediction model for cardiac implantable electronic device implantation after transcatheter aortic valve replacement.JACC Clin Electrophysiol. 2020; 6:295–303. doi: 10.1016/j.jacep.2019.10.020CrossrefMedlineGoogle Scholar4. Agasthi P, Mookadam F, Venepally N, Girardo M, Buras M, Khetarpal BK, Mulpuru SK, Eleid M, Greason K, Beohar N, et al.. Abstract 15572: Machine learning helps predict permanent pacemaker requirement post transcatheter aortic valve replacement.Circulation. 2019; 140:A15572. doi: 10.1161/circ.140.suppl_1.15572LinkGoogle Scholar5. Truong VT, Wigle M, Bateman E, Pallerla A, Ngo TNM, Beyerbach D, Kereiakes D, Shreenivas S, Tretter J, Palmer C, et al.. Pacemaker imlantation following TAVR: using machine learning to optimize risk stratification.JACC. 2020; 75:1478–1478. doi: 10.1016/S0735-1097(20)32105-7CrossrefGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetails March 2021Vol 14, Issue 3Article InformationMetrics Download: 169 © 2021 American Heart Association, Inc.https://doi.org/10.1161/CIRCEP.120.008941PMID: 33685208 Originally publishedMarch 9, 2021 Keywordsmachine learningatrioventricular blockrisktranscatheter aortic valve replacementpatientspacemakerPDF download SubjectsAortic Valve Replacement/Transcatheter Aortic Valve ImplantationArrhythmiasPacemaker

To compare post‐procedural outcomes of trans‐catheter valve replacement (TAVR) among safety‐net (SNH) and non‐safety net hospitals (non‐SNH).

Background: Cardiac CTA is an indispensable imaging tool for TAVR procedure planning. Post-processing of the dual-energy CT utilizing dual-source and kV-switching approach enables an increase in the density of iodine and allows the reduction of iodine dose. We hypothesized that the use of a dual-layer Spectral Detector CT (SDCT) can enhance the signal of intravascular iodine contrast material, reduce iodine contrast material volume, and facilitate pre-TAVR planning. Methods: We tested this in a preclinical porcine animal model, with results suggesting that spectral imaging may be superior to conventional imaging even at 21-35% of the full contrast medium dose with regard to reader confidence, higher SNR and CNR at the level of the aortic annulus and root. We subsequently followed this up by a prospective human validation study of 24 patients undergoing TAVR. Results: We demonstrate that SNR and CNR with SDCT were significantly higher (highest in lower energy virtual mono-energetic images (VMI) (monoE 40 keV) compared to conventional images, with the spectral images preferred for procedure planning by an experienced TAVR operator and imaging specialist. This was associated with a reduction in inter-observer variability in TAVR sizing measurements in low dose contrast studies (33% of the full contrast dose) resulting in a higher rate of agreement on the choice of valve prosthesis size. Conclusion: Low contrast dose spectral images achieved similar SNR and CNR compared to full contrast dose conventional images. Taken together, our results suggest that the use of SDCT imaging may facilitate the routine use of low contrast dose as part of pre-TAVR imaging.

OBJECTIVES This study sought to compare outcomes following transcatheter aortic valve replacement when valve repositioning was performed (repositioned group) versus procedures without repositioning (nonrepositioned group). BACKGROUND The Evolut R and Evolut PRO valves were designed to allow repositioning during deployment, yet the effect of repositioning on clinical outcomes remains unclear. METHODS Patients implanted with the Evolut R or PRO valve from the SURTAVI (Surgical Replacement and Transcatheter Aortic Valve Implantation) trial continued access study and the Evolut Low Risk Trial between June 2016 and November 2018 were combined. Baseline multidetector computed tomography data were analyzed for the Evolut Low Risk Trial patients. The primary outcomes were the rate of all-cause mortality and the rate of disabling stroke 30 days. Secondary outcomes were per Valve Academic Research Consortium-2. RESULTS The Evolut R or PRO valve was implanted in 946 patients, and repositioning was performed in 318 (33.6%). Compared with patients in the nonrepositioned group, patients in the repositioned group had lower Society of Thoracic Surgeons score (2.3 +/- 1.3% vs. 2.6 +/- 1.4%; p < 0.001) and fewer prior percutaneous coronary interventions (11.9% vs. 19.7%; p = 0.003). There were no differences in baseline multidetector computed tomography parameters between groups. There were no differences in the primary outcome of death (0.3% vs. 0.3%; p = 0.99) or disabling stroke (0.3% vs. 0.5%; p = 0.71) at 30 days or 1 year (1.9% vs. 2.9%; p = 0.44; and 0.8% vs. 0.9%%; p = 0.79, respectively). CONCLUSIONS The utilization of the repositioning feature of the Evolut valves was safe, and no differences in death or disabling stroke were observed at 30 days or 1 year between groups. (C) 2020 by the American College of Cardiology Foundation.

OBJECTIVES The aim of this study was to develop and validate a risk prediction model for high-grade atrioventricutar block requiring cardiac implantable electronic device (CIED) implantation after transcatheter aortic valve replacement (TAVR). BACKGROUND High-grade atrioventricular block requiring CIED remains a significant sequelae following TAVR. Although several pre-operative characteristics have been associated with the risk of post-operative OED implantation, an accurate and validated risk prediction model is not established yet. METHODS This was a single center, retrospective study of consecutive patients who underwent TAVR from March 10, 2011, to October 8, 2018. This cohort sample was randomly divided into a derivation cohort (group A) and a validation cohort (group B). A scoring system for risk prediction of post-TAVR CIED implantation was devised using logistic regression estimates in group A and the calibration and validation were done in group B. RESULTS A total of 1,071 patients underwent TAVR during the study period. After excluding pre-existing OED, a total of 888 cases were analyzed (group A: 507 and group B: 381). Independent predictive variables were as follows: self-expanding valve (1 point), hypertension (1 point), pre-existing first-degree atrioventricular block (1 point), and right bundle branch block (2 points). The resulting score was calculated from the total points. The intemat validation in group B showed an ideal linear relationship in calibration plot (R-2 = 0.933) and a good predictive accuracy (area under the curve: 0.693; 95% confidence interval: 0.627 to 0.759). CONCLUSIONS This prediction model accurately predicts post-operative risk of OED implantation with simple preoperative parameters. (C) 2020 by the American College of Cardiology Foundation.

Introduction: Safety-net hospitals (SNH) treat a large population of un-insured and low income patients; several prior studies report worse outcome at these centers. Trans-catheter valve replacement (TAVR) is emerging as first-line therapy for aortic stenosis irrespective of surgical risk scores. However, results of TAVR performed at these centers is limited. Objective: To determine whether post-procedural outcomes of TAVR are comparable at safety-net (SNH) and non-safety net hospitals (non-SNH). Methods: We conducted a retrospective, cohort study with propensity-matched analysis. Complex survey data from the Agency for Healthcare Quality and Research containing weighted sample of all hospital admissions nationwide was utilized for this study. Adults undergoing TAVR at US hospitals participating in the National In-patient sample (NIS) database from January 2014 - December 2015 were included. A 1:1 propensity-matched cohort of patients operated at safety-net hospitals (SNH) and non-SNH institutions was analyzed. Propensity-matching was performed on the basis of sixteen demographic and clinical confounding co-variates. Main outcome studied was all-cause post-procedural mortality. Secondary outcomes compared were stroke, acute kidney injury and length of post-operative stay. Results: Between 2014 - 2015, 41410 patients (mean age 80 +/- 0.11 years, 46% female) underwent TAVR at 731 centers nationwide; 6996 (16.80 %) procedures were performed at safety net centers. SNH comprised 135/731 (18.4%) of all centers performing TAVR. SNH patients were more likely to be female (49 % vs 46 %, p <0.001); admitted emergently (31% vs 21%; p <0.001) and at the lowest quartile for household income (25% % vs 20 %; p <0.001). A large proportion of SNH patients were minorities (Blacks 5.9% vs 3.9%; Hispanic 7.2% vs 3.2%). Adjusted logistic regression was performed on 6995 propensity-matched patient pairs. Post-procedural mortality [OR 0.99 (0.98 - 1.007); p = 0.43], stroke [OR 1.009 (0.99-1.02); p = 0.08], and acute kidney injury [OR 0.99 (0.96 - 1.01); p = 0.5] were comparable in both cohorts. Overall length of stay was also similar (6.9 +/- 0.1 vs 7.1 +/- 0.2 days; p = 057). Conclusion: Post-procedural outcomes after TAVR at SNH are comparable to national outcomes. Our study provides preliminary evidence that wider adoption of TAVR may not adversely influence outcomes at SNH.

OBJECTIVES:We share our center's experience with the use of transcatheter valvular therapies in the setting of failed bioprostheses. BACKGROUND:As medicine continues to advance, the lifespan of individuals continues to increase, and current surgical valvular therapies begin to degrade prior to a person's end of life. It is important to evaluate the efficacy and durability of transcatheter valves within failed surgical bioprostheses. METHODS:Baseline characteristics, periprocedural complications, and long-term outcomes were collected and assessed in patients who received transcatheter valves for failing surgical aortic valve bioprostheses and mitral valve and ring bioprostheses from March 2011 to July 2018. RESULTS:From our cohort of 1048 patients, we identified 45 individuals (4.3%) who underwent transcatheter replacement of a failed bioprosthetic valve or ring. Mean age at presentation was 80.8 ± 10.7 years and 75.5 ± 9.3 years, mean STS score was 9.3 ± 5.1 and 13.3 ± 8.7, and mean time to failure was 12.0 ± 5.2 years and 7.3 ± 4.5 years for aortic and mitral positions, respectively. At 1 year, time to event analysis suggested a 16.4% mortality rate for aortic replacement and 12.8% mortality rate for mitral replacement. CONCLUSIONS:We demonstrate outcomes from one of the largest single-center United States based cohorts of transcatheter replacements of failed surgical bioprostheses. Our center has demonstrated that it is feasible to pursue the replacement of failed surgical bioprostheses in the aortic and mitral positions with transcatheter valves given appropriate patient selection.

Objectives. Urgent transcatheter aortic valve replacement [TAVR] is associated with worse short-term outcomes compared with elective TAVR; however, little is known about long-term outcomes or the safety of the minimalist strategy in this setting. This study investigated the short-term and long-term outcomes of urgent TAVR compared with elective TAVR under a minimalist strategy (transfemoral [TF] approach with conscious sedation and no transesophageal echocardiography guidance). Methods. After excluding 2 emergent patients requiring immediate procedures, a total of 474 consecutive patients underwent elective TF-TAVR (396 patients; 83.6%) or urgent TF-TAVR (78 patients:16.4%). Urgent TAVR was defined as a procedure performed in the same hospitalization in patients emergently admitted due to cardiac arrest. severe acute decompensated heart failure, acute coronary syndrome, or repeated syncopal episodes. Results. A minimalist approach was used in 77 patients (98.7%) undergoing urgent TAVR and in 392 patients (99.0%) undergoing elective TAVR (P=.59). Urgent TAVR had similar procedure-related complications, such as stroke, myocardial infarction, bleeding or vascular complications, and in-hospital mortality compared with elective TAVR (mortality, 1.3% vs 0.8%; P=.51] with no intraprocedural cross-over from conscious sedation to general anesthesia. However, 30-day and 1-year survival rates were reduced in patients undergoing urgent TAVR. After adjustment with baseline and procedural factors, urgent TAVR remained significantly predictive of 1-year mortality (adjusted hazard ratio, 2.26; 95% confidence interval, 1.16-4.23; P=.01). Conclusions. Urgent minimalist TAVR can be safely performed with favorable in-hospital outcomes, while increased 30-day and 1-year mortality rates suggest the importance of appropriate diagnosis and timely treatment of severe aortic stenosis.