Predicting and measuring mortality risk after transcatheter aortic valve replacement

Predictors of All-Cause Mortality After Successful Transcatheter Aortic Valve Implantation in Patients With Atrial Fibrillation

Prevalent and incident atrial fibrillation are common in patients who undergo transcatheter aortic valve implantation and are associated with impaired postprocedural outcomes, including mortality. We determined predictors of long-term mortality in patients with atrial fibrillation after successful transcatheter aortic valve implantation. The EdoxabaN Versus standard of care and theIr effectS on clinical outcomes in pAtients havinG undergonE Transcatheter Aortic Valve Implantation-Atrial Fibrillation (ENVISAGE-TAVI AF) trial (NCT02943785) was a multicenter, prospective, randomized controlled trial in patients with prevalent or incident atrial fibrillation after successful transcatheter aortic valve implantation who received edoxaban or vitamin K antagonists. A Cox proportional hazard model was performed to identify predictors of all-cause mortality using a stepwise approach for multiple regression analysis. In addition, we assessed the performance of different risk scores and prediction models using ENVISAGE-TAVI AF data. Of 1,426 patients in ENVISAGE-TAVI AF, 178 (12.5%) died during the follow-up period (median 548 days). Our stepwise approach identified greater risk of mortality with older age, impaired renal function, nonparoxysmal atrial fibrillation, excessive alcohol use, New York Heart Association heart failure class III/IV, peripheral artery disease, and history of major bleeding or predisposition to bleeding. The present model (concordance statistic [c-statistic] 0.67) was a better discriminator than were other frequently used risk scores, such as the Society of Thoracic Surgeons score (c-statistic 0.56); Congestive heart failure, Hypertension, Age ≥75, Diabetes, Stroke, Vascular disease, Age 65 to 74 years, and Sex category (CHA2DS2-VASc) score (c-statistic 0.54); or Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly, and Drugs/alcohol concomitantly (HAS-BLED) score (c-statistic 0.58). In ENVISAGE-TAVI AF, several modifiable and nonmodifiable clinical characteristics were significantly associated with greater long-term all-cause mortality. Improved risk stratification to estimate the probability of mortality after successful transcatheter aortic valve implantation in patients with atrial fibrillation may improve long-term patient prognosis.

Recent developments in modeling, imaging, and monitoring of cardiovascular diseases using machine learning

Cardiovascular diseases are the leading cause of mortality, morbidity, and hospitalization around the world. Recent technological advances have facilitated analyzing, visualizing, and monitoring cardiovascular diseases using emerging computational fluid dynamics, blood flow imaging, and wearable sensing technologies. Yet, computational cost, limited spatiotemporal resolution, and obstacles for thorough data analysis have hindered the utility of such techniques to curb cardiovascular diseases. We herein discuss how leveraging machine learning techniques, and in particular deep learning methods, could overcome these limitations and offer promise for translation. We discuss the remarkable capacity of recently developed machine learning techniques to accelerate flow modeling, enhance the resolution while reduce the noise and scanning time of current blood flow imaging techniques, and accurate detection of cardiovascular diseases using a plethora of data collected by wearable sensors.

Prognostic relevance of mitral and tricuspid regurgitation after transcatheter aortic valve implantation: Impact of follow-up time point for decision-making

Background

In patients with aortic stenosis treated by transcatheter aortic valve implantation (TAVI), mitral and tricuspid regurgitation (MR and TR) at baseline and after TAVI are likely to be of prognostic relevance, and questions such as whether and when treatment further improves prognosis in these patients arise.

Aims

Against that background, the purpose of this study was to analyze a variety of clinical characteristics including MR and TR with respect to their potential value as predictors of 2-year mortality after TAVI.

Methods

A cohort of 445 typical TAVI patients was available for the study and clinical characteristics were evaluated baseline, 6 to 8 weeks as well as 6 months after TAVI.

Results

In 39% of the patients relevant (moderate or severe) MR and in 32% of the patients relevant (moderate or severe) TR could be detected at baseline. The rates were 27% for MR (p = 0.001, compared to baseline) and 35% for TR (p = n.s., compared to baseline) at the 6- to 8-week follow-up. After 6 months, relevant MR was observable in 28% (p = 0.036, compared to baseline) and relevant TR in 34% (p = n.s., compared to baseline) of the patients. As predictors of 2-year mortality, a multivariate analysis identified the following parameters for the different time points: sex, age, AS entity, atrial fibrillation, renal function, relevant TR, systolic pulmonary artery pressure (PAPsys), and 6-min walk distance at baseline; clinical frailty scale and PAPsys 6-8 weeks after TAVI and BNP and relevant MR 6 months after TAVI. There was a significantly worse 2-year survival in patients with relevant TR at baseline (68.4% vs. 82.6%, p < 0.001; whole population, n = 445) and in patients with relevant MR at 6 months (87.9% vs. 95.2%, p = 0.042; landmark analysis: n = 235).

Conclusion

This real-life study demonstrated the prognostic relevance of repeated evaluation of MR and TR before and after TAVI. Choosing the right time point for treatment is a remaining clinical challenge, which should be further addressed in randomized trials.

New-Onset Atrial Fibrillation After Transcatheter Aortic Valve Replacement: A Systematic Review and Meta-Analysis

OBJECTIVES

The authors aimed to identify risk factors and outcomes associated with new-onset atrial fibrillation (NOAF) after transcatheter aortic valve replacement (TAVR).

BACKGROUND

NOAF is a common complication after TAVR, although estimates of the precise occurrence are variable. This study sought to quantify the occurrence of NOAF after TAVR and to explore the outcomes and predictors associated with this complication.

METHODS

We searched Medline, EMBASE, and the Cochrane database from 2016 to 2020 for articles that reported NOAF after TAVR. We extracted data for studies published before 2016 from a previous systematic review. We pooled data using a random effects model.

RESULTS

We identified 179 studies with 241,712 total participants (55,271 participants with pre-existing atrial fibrillation (AF) were excluded) that reported NOAF from 2008 to 2020. The pooled occurrence of NOAF after TAVR was 9.9% (95% CI: 8.1%-12%). NOAF after TAVR was associated with a longer index hospitalization (mean difference = 2.66 days; 95% CI: 1.05-4.27), a higher risk of stroke in the first 30 days (risk ratio [RR]: 2.35; 95% CI: 2.12-2.61), 30-day mortality (RR: 1.76; 95% CI: 1.12-2.76), major or life-threatening bleeding (RR: 1.60; 95% CI: 1.39-1.84), and permanent pacemaker implantation (RR: 1.12; 95% CI: 1.05-1.18). Risk factors for the development of NOAF after TAVR included higher Society of Thoracic Surgeons score, transapical access, pulmonary hypertension, chronic kidney disease, peripheral vascular disease, and severe mitral regurgitation, suggesting that the risk for NOAF is highest in more comorbid TAVR patients.

CONCLUSIONS

NOAF is common after TAVR. Whether AF after TAVR is a causal factor or a marker of sicker patients remains unclear.