Quantification of physical activity with prospective activity tracking after transfemoral aortic valve replacement

BACKGROUND

Transcatheter aortic valve replacement (TAVR) is a well-established, safe and effective therapy for severe symptomatic aortic stenosis (AS). The aim of this study was to objectively quantify improvement of physical activity after TAVR, with consideration of different low-gradient AS subtypes.

METHODS AND RESULTS

All patients undergoing TAVR for severe AS were screened. Participants received a wearable activity tracker (Fitbit®) at hospital discharge following TAVR and 6 months thereafter. The difference of median daily steps was defined as surrogate outcome for physical activity. For analysis, patients were grouped into high-gradient (HG) AS (dPmean ≥40 mmHg), classical low-flow low-gradient (LFLG) AS (dPmean <40 mmHg, EF <50%), paradoxical LFLG-AS (dPmean <40 mmHg, EF ≥50%, SVi ≤35 ml/m2) and normal-flow low-gradient (NFLG) AS (dPmean <40 mmHg, EF ≥50%, SVi >35 ml/m2) according to mean transvalvular pressure gradient (dPmean), stroke volume index (SVi) and left-ventricular ejection fraction (LVEF).

RESULTS AND CONCLUSIONS

The analysis is based on 230 patients. The median daily step count was 4409 [IQR 2581-7487] after hospital discharge and 5326 [IQR 3045-8668] 6 months thereafter. Median difference of daily steps was ∆529 [IQR -702-2152]). Patients with HG-AS and paradoxical LFLG-AS showed a significant improvement of daily steps (∆951 [IQR -378-2323], p <0.001 and (∆1392 [IQR -609-4444], p = 0.02, respectively). Patients with classical LFLG-AS showed no statistically relevant improvement of daily steps (∆192 [IQR -687-770], p = 0.79). Patients with NFLG-AS showed a numerical decline in daily steps without statistical significance (∆-300 [IQR -1334-1406], p = 0.67). This first prospective study of this sample size shows significant improvement of physical activity after TAVR with an objective and reproducible method. This was mainly driven by an improvement in patients with HG-AS and paradoxical LFLG-AS.

TAVI for patients with normal-flow low-gradient compared to high-gradient aortic stenosis

BACKGROUND

Normal-flow (stroke volume index, SVi >35 ml/m²) low-gradient (dPmean <40 mmHg) aortic stenosis (NFLG-AS) is subject of scientific debate. Guidelines fail to give conclusive treatment recommendations. We hypothesized that NFLG patients are heterogenous, containing a subgroup similar to high-gradient aortic stenosis patients (dPmean ≥40 mmHg, HG-AS) concerning characteristics and outcomes.

METHODS

2326 patients undergoing transcatheter aortic valve replacement (TAVI) at our centre between 2013 and 2019 were analysed. 386 patients fulfilled criteria of NFLG-AS. Their median dPmean was 33 mmHg, which was used for grouping (204 patients with higher gradient NFLG-AS, 186 patients with lower gradient NFLG-AS). They were compared to 956 HG-AS patients.

RESULTS

Characteristics of lower gradient NFLG-AS patients differed from HG-AS patients in many aspects while higher gradient NFLG-AS and HG-AS patients were mostly similar, underscored by higher Society of Thoracic Surgeons scores in lower gradient NFLG-AS (lower gradient NFLG-AS, 3.9, HG-AS, 3.0, p = 0.03, higher gradient NFLG-AS, 3.0, p = 0.04). Procedural complications were comparable. Estimated 3-year all-cause mortality was higher in lower gradient NFLG-AS compared to HG-AS patients (hazard ratio 1.7, p < 0.01), whereas mortality of higher gradient NFLG-AS was similar to HG-AS patients (hazard ratio 1.2, p = 0.31). Cardiovascular mortality was highest among lower gradient NFLG-AS patients (21.6% vs. higher gradient NFLG-AS, 15.4%, vs. HG-AS, 11.1%, p < 0.01).

CONCLUSIONS

NFLG-AS patients are indeed heterogenous. NFLG-AS patients with higher gradients resemble HG-AS patients in clinical characteristics and outcomes and should not be treated differently. Lower gradient NFLG-AS patients have increased long-term mortality and the use of TAVI requires careful consideration.

Comparison of transcatheter aortic valve implantation outcomes between normal flow low gradient severe aortic stenosis and normal flow high gradient severe aortic stenosis

BACKGROUND

Normal flow low gradient severe aortic stenosis (NFLG-AS) with preserved ejection fraction is the most prevalent form of low gradient severe aortic stenosis. Despite the increased prevalence, the clinical outcomes and management strategy of NFLG-AS remain controversial. Therefore, our study aimed to evaluate transcatheter aortic valve implantation (TAVI) outcomes of patients with NFLG-AS compared with normal flow high gradient severe aortic stenosis (NFHG-AS).

METHODS

We performed a retrospective analysis of 394 patients who underwent TAVI between January 2011 to September 2020. Among 394 patients, 232 patients had NFLG-AS, and 162 patients had NFHG-AS. The primary outcomes included all-cause mortality and cardiovascular mortality. In addition, multiple secondary outcomes were evaluated, including stroke, myocardial infarction, duration of hospital stay, new-onset atrial fibrillation, temporary or permanent pacemaker requirement, major bleeding, blood transfusion, vascular complications, acute kidney injury, hemodialysis requirement, symptom improvement, and repeat hospitalizations due to any cardiac disease.

RESULTS

The cumulative six months incidence of all-cause mortality and cardiovascular mortality were similar between and NFLG-AS and NFHG-AS (4.32% vs. 5.17%, P = 0.71 and 2.47% vs. 2.59%, P = 0.94 respectively). There was no difference in the rates of stroke, myocardial infarction, duration of hospital stay, new-onset atrial fibrillation, temporary or permanent pacemaker requirement, major bleeding, blood transfusion, vascular complications, acute kidney injury, hemodialysis requirement, and symptom improvement between the two groups. However, patients with NFLG-AS compared to NFHG-AS had more frequent cardiac-related repeat hospitalizations (19.14% vs. 11.64%, P = 0.04%).

CONCLUSION

There was no significant difference in all-cause mortality and cardiovascular mortality between NFLG-AS and NGHG-AS six months post-TAVI. However, patients undergoing TAVI with NFLG-AS had significantly higher rates of cardiac-related repeat hospitalizations.

A Machine-Learning Framework to Identify Distinct Phenotypes of Aortic Stenosis Severity

OBJECTIVES

The authors explored the development and validation of machine-learning models for augmenting the echocardiographic grading of aortic stenosis (AS) severity.

BACKGROUND

In AS, symptoms and adverse events develop secondarily to valvular obstruction and left ventricular decompensation. The current echocardiographic grading of AS severity focuses on the valve and is limited by diagnostic uncertainty.

METHODS

Using echocardiography (ECHO) measurements (ECHO cohort, n = 1,052), we performed patient similarity analysis to derive high-severity and low-severity phenogroups of AS. We subsequently developed a supervised machine-learning classifier and validated its performance with independent markers of disease severity obtained using computed tomography (CT) (CT cohort, n = 752) and cardiovascular magnetic resonance (CMR) imaging (CMR cohort, n = 160). The classifier's prognostic value was further validated using clinical outcomes (aortic valve replacement [AVR] and death) observed in the ECHO and CMR cohorts.

RESULTS

In 1,964 patients from the 3 multi-institutional cohorts, 1,346 (68%) subjects had either nonsevere or discordant AS severity. Machine learning identified 1,117 (57%) patients as having high-severity and 847 (43%) as having low-severity AS. High-severity patients in CT and CMR cohorts had higher valve calcium scores and left ventricular mass and fibrosis, respectively than the low-severity group. In the ECHO cohort, progression to AVR and progression to death in patients who did not receive AVR was faster in the high-severity group. Compared with the conventional classification of disease severity, machine-learning-based severity classification improved discrimination (integrated discrimination improvement: 0.07; 95% confidence interval: 0.02 to 0.12) and reclassification (net reclassification improvement: 0.17; 95% confidence interval: 0.11 to 0.23) for the outcome of AVR at 5 years. For both ECHO and CMR cohorts, we observed prognostic value of the machine-learning classifications for subgroups with asymptomatic, nonsevere or discordant AS.

CONCLUSIONS

Machine learning can integrate ECHO measurements to augment the classification of disease severity in most patients with AS, with major potential to optimize the timing of AVR.

Discordant Echocardiographic Grading in Low Gradient Aortic Stenosis (DEGAS Study) From the Italian Society of Echocardiography and Cardiovascular Imaging Research Network: Rationale and Study Design

Background

Low-gradient aortic stenosis (LG-AS) is characterized by the combination of an aortic valve area compatible with severe stenosis and a low transvalvular mean gradient with low-flow state (i.e., indexed stroke volume <35 mL/m²) in the presence of reduced (classical low-flow AS) or preserved (paradoxical low-flow AS) ejection fraction. Furthermore, the occurrence of a normal-flow LG-AS is still advocated by many authors. Within this diagnostic complexity, the diagnosis of severe AS remains challenging.

Objective

The general objective of the Discordant Echocardiographic Grading in Low-gradient AS (DEGAS Study) study will be to assess the prevalence of true severe AS in this population and validate new parameters to improve the assessment and the clinical decision-making in patients with LG-AS.

Methods and Analyses

The DEGAS Study of the Italian Society of Echocardiography and Cardiovascular Imaging is a prospective, multicenter, observational diagnostic study that will enroll consecutively adult patients with LG-AS over 2 years. AS severity will be ideally confirmed by a multimodality approach, but only the quantification of calcium score by multidetector computed tomography will be mandatory. The primary clinical outcome variable will be 12-month all-cause mortality. The secondary outcome variables will be (i) 30-day mortality (for patients treated by Surgical aortic valve replacement or TAVR); (ii) 12-month cardiovascular mortality; (iii) 12-month new major cardiovascular events such as myocardial infarction, stroke, vascular complications, and rehospitalization for heart failure; and (iv) composite endpoint of cardiovascular mortality and hospitalization for heart failure. Data collection will take place through a web platform (REDCap), absolutely secure based on current standards concerning the ethical requirements and data integrity.