Heart Block After Discharge in Patients Undergoing TAVR With Latest-Generation Valves

Evaluation and Management of Heart Block After Transcatheter Aortic Valve Replacement

Transcatheter aortic valve replacement (TAVR) has developed substantially since its inception. Improvements in valve design, valve deployment technologies, preprocedural imaging and increased operator experience have led to a gradual decline in length of hospitalisation after TAVR. Despite these advances, the need for permanent pacemaker implantation for post-TAVR high-degree atrioventricular block (HAVB) has persisted and has well-established risk factors which can be used to identify patients who are at high risk and advise them accordingly. While most HAVB occurs within 48 hours of the procedure, there is a growing number of patients developing HAVB after initial hospitalisation for TAVR due to the trend for early discharge from hospital. Several observation and management strategies have been proposed. This article reviews major known risk factors for HAVB after TAVR, discusses trends in the timing of HAVB after TAVR and reviews some management strategies for observing transient HAVB after TAVR.

Impact of Bundle Branch Block on Permanent Pacemaker Implantation after Transcatheter Aortic Valve Implantation: A Meta-Analysis

Data regarding the impact of infra-Hisian conduction disturbances leading to permanent pacemaker implantation (PPI) after transcatheter aortic valve implantation (TAVI) remain limited. The aim of this study was to determine the impact of right and/or left bundle branch block (RBBB/LBBB) on post-TAVI PPI. We performed a systematic literature review to identify studies reporting on RBBB and/or LBBB status and post-TAVI PPI. Study design, patient characteristics, and the presence of branch block were analyzed. Odds ratios (ORs) with 95% CI were extracted. The final analysis included 36 studies, reporting about 55,851 patients. Data on LBBB were extracted from 33 studies. Among 51,026 patients included, 5503 showed pre-implant LBBB (11.9% (10.4%–13.8%)). The influence of LBBB on post-TAVI PPI was not significant OR 1.1474 (0.9025; 1.4588), p = 0.2618. Data on RBBB were extracted from 28 studies. Among 46,663 patients included, 31,603 showed pre-implant RBBB (9.2% (7.3%–11.6%)). The influence of RBBB on post-TAVI PPI was significant OR 4.8581 (4.1571; 5.6775), p < 0.0001. From this meta-analysis, the presence of RBBB increased the risk for post-TAVI PPI, independent of age or LVEF, while this finding was not confirmed for patients experimenting with LBBB. This result emphasizes the need for pre-operative evaluation strategies in patient selection for TAVI.

A Disruptive Technology: Determining Need for Permanent Pacing After TAVR

PURPOSE OF REVIEW

Transcatheter aortic valve replacement (TAVR) has changed the paradigm for management of severe aortic stenosis. Despite evolution of TAVR over the past 2 decades, conduction system disturbances remain a concern post-TAVR. In this review, we describe (1) permanent pacemaker (PP) implant rates associated with TAVR, (2) risk factors predicting need for PP therapy post-TAVR, (3) management of perioperative conduction abnormalities, and (4) novel areas of research.

RECENT FINDINGS

Conduction disturbances remain a common issue post-TAVR, in particular, left bundle branch block (LBBB). Though newer data describes resolution of a significant fraction of these disturbances over time, rates of pacemaker therapy remain high despite improvements in valve technology and procedural technique. Recent consensus statements and guideline documents are important first steps in standardizing an approach to post-TAVR conduction disturbances. New areas of research show promise in both prediction and treatment of conduction disturbances post-TAVR.

Temporal Trends in the Incidence and Outcomes of Pacemaker Implantation After Transcatheter Aortic Valve Replacement in the United States (2012-2017)

Background

Nationwide studies documenting temporal trends in permanent pacemaker implantation (PPMI) following transcatheter aortic valve replacement (TAVR) are limited.

Methods and Results

We selected patients who underwent TAVR between 2012 and 2017 in the National Readmission Database. The primary end point was the 6‐year trend in post‐TAVR PPMI at index hospitalization and at 30, 90, and 180 days after discharge. The secondary end point was the association between PPMI and in‐hospital mortality, stroke, cost, length of stay, and disposition. Among the 89 202 patients who underwent TAVR, 77 405 (86.8%) with no prior pacemaker or defibrillator were included. Patients who required PPMI had a higher prevalence of atrial fibrillation (43.6% versus 38.7%, P<0.001) and conduction abnormalities (28.4% versus 15.3%, P<0.001). The incidence of PPMI during index admission increased from 8.7% in 2012 to 13.2% in 2015, and then decreased to 9.6% in 2017. The incidence of inpatient PPMI within 30 days after discharge increased from 0.5% in 2012 to 1.25% in 2017 (P_trend<0.001). Inpatient PPMI beyond 30 days remained rare (<0.5%) during the study period. After risk adjustment, PPMI was not associated with in‐hospital mortality or stroke but was associated with increased nonhome discharge, longer hospitalization, and higher cost. The incremental expenditure associated with post‐TAVR PPMI during index admission increased from $9.6 million to $72.2 million between 2012 and 2017.

Conclusions

After an upward trend, rates of PPMI after TAVR in the United States stabilized at ~10% in 2016 to 2017, but there was a notable increase in PPMI within 30 days after the index admission. PPMI was not associated with increased in‐hospital morbidity or mortality but led to longer hospitalization, higher cost, and more nonhome discharges.

Predicting need for pacemaker implantation early and late after transcatheter aortic valve implantation

OBJECTIVES

To identify associations with either early or late permanent pacemaker (PPM) implantation after transcatheter aortic valve replacement (TAVR) in order to develop an easily interpretable management algorithm.

BACKGROUND

Injury to the conduction system after TAVR occasionally requires PPM. There is limited data on how to identify which patients will require PPM, particularly after discharge from index hospitalization after TAVR.

METHODS

All patients having undergone TAVR at the University of North Carolina through August 2019 were identified and records were manually reviewed. Multivariable analyses were performed to identify associations with post-TAVR PPM due to high-degree atrioventricular block (HAVB). Comparisons were made between patients with no PPM (n = 304) and PPM required, stratified into early (during index hospitalization, n = 32) and late (during subsequent hospitalization, n = 11) PPM cohorts.

RESULTS

Of the 347 patents included for analysis, 43 (12.4%) underwent post-TAVR PPM. In multivariable regression models, early PPM was associated with baseline bifascicular block (OR: 42.16; p < .001), requiring any pacing on first post-TAVR electrocardiogram (ECG) (OR: 31.55; p < .001), and valve oversizing >15% (OR: 3.61; p < .05). Late PPM was associated with baseline right bundle branch block (RBBB) (OR 12.62; p < .001) and history of atrial fibrillation/flutter (OR 4.83; p < .05).

CONCLUSIONS

Bifascicular block, any pacing on first post-TAVR ECG, and >15% valve oversizing are associated with early PPM, while RBBB and history of atrial fibrillation/flutter are associated with late PPM. We suggest a management strategy for post-TAVR surveillance and management of HAVB.

Prediction of temporary epicardial pacing wire use in cardiac surgery

BACKGROUND

Placement of temporary epicardial pacing wires (TEPW) at the end of open heart surgery cases is routine but can be associated with complications. Identification of patients who are high risk for requiring pacing would be beneficial on guiding selective TEPW placement. The purpose of this study was to identify predictors of temporary pacing immediately post cardiac surgery.

METHODS

A retrospective analysis of patients undergoing cardiac surgery from 2005 to 2016 at the Maritime Heart Center was conducted. Analysis was performed of patients who require pacing on arrival to the cardiovascular intensive care unit (CVICU) compared with those who were not paced. Multivariable logistic regression was used to determine each variable's risk adjusted likelihood of pacing for the entire cohort. Subgroup analysis was performed in the isolated procedures.

RESULTS

A total of 11 752 patient underwent surgery from the year 2005 to 2016. Two thousand and fifty-one (17.5%) required pacing on arrival to CVICU. Older age, female sex, preoperative renal failure, lower ejection fraction (EF), preoperative arrhythmia, preoperative use of calcium channel blockers, and longer cross-clamp times were risk factors for pacing. In the isolated coronary artery bypass grafting and aortic valve replacement groups, findings were similar to the overall cohort. Only age, obesity, and chronic obstructive pulmonary disease were risk factors for pacing in the isolated mitral valve (MV) repair group and only preoperative arrhythmia in the isolated MV replacement group.

CONCLUSION

We have identified risk factors for TEPW use following cardiac surgery and in isolated procedure subgroups. These risk factors may help guide selective TEPW placement.

Machine Learning in Cardiology-Ensuring Clinical Impact Lives Up to the Hype

Despite substantial advances in the study, treatment, and prevention of cardiovascular disease, numerous challenges relating to optimally screening, diagnosing, and managing patients remain. Simultaneous improvements in computing power, data storage, and data analytics have led to the development of new techniques to address these challenges. One powerful tool to this end is machine learning (ML), which aims to algorithmically identify and represent structure within data. Machine learning's ability to efficiently analyze large and highly complex data sets make it a desirable investigative approach in modern biomedical research. Despite this potential and enormous public and private sector investment, few prospective studies have demonstrated improved clinical outcomes from this technology. This is particularly true in cardiology, despite its emphasis on objective, data-driven results. This threatens to stifle ML's growth and use in mainstream medicine. We outline the current state of ML in cardiology and outline methods through which impactful and sustainable ML research can occur. Following these steps can ensure ML reaches its potential as a transformative technology in medicine.

Effect on 30-Day Readmissions after Early Versus Delayed Discharge after Uncomplicated Transcatheter Aortic Valve Implantation (from the Nationwide Readmissions Database)

Early discharge after transcatheter aortic valve implantation has been shown to be safe in single-center studies and trials, but outcomes in broader clinical practice are unknown. Using the National Readmission Databases (1/2014 to 9/2015), we compared 30-day readmission rates between early (<3 days) and late (≥3 days) discharges after uncomplicated endovascular TAVR in a propensity-matched cohort. We examined factors associated with failure of early discharge by testing for interactions of patient factors with discharge strategy. Among 4,955 hospitalizations for uncomplicated TAVR, 1,857 (37%) were discharged early with substantial site-level variability (range 0% to 87%; median odds ratio 3.69). In the propensity matched cohort (n = 3,346), there were similar rates of 30-day readmission by discharge strategy (early vs late: 10.3% vs 10.6%; stratified log-rank p = 0.555). There was a statistically significant interaction between discharge strategy and number of chronic conditions (p = 0.007), where readmission rates were lower in patients discharged early in those with 0 to 4 chronic conditions, but not in those with 5 to 10 or >10. In conclusion, in a large "real-world" cohort, early discharge after uncomplicated TAVR was not associated with a higher rate of 30-day rehospitalization, yet there was significant variability across US hospitals. No patient characteristics were associated with increased risk of readmission with early discharge.