Relationship of ejection fraction and natriuretic peptide trajectories in heart failure with baseline reduced and mid-range ejection fraction

Usefulness of Heart Failure Categories Based on Left Ventricular Ejection Fraction

BACKGROUND

Heart failure guidelines have recently introduced a narrow category with mildly reduced left ventricular ejection fraction (LVEF) (heart failure with mildly reduced ejection fraction; LVEF 41%-49%) between the previous categories of reduced (heart failure with reduced ejection fraction; LVEF ≤40%) and preserved (heart failure with preserved ejection fraction; LVEF ≥50%) ejection fraction. Grouping of continuous measurements into narrow categories can be questioned if their variability is high.

METHODS AND RESULTS

We constructed a cohort of all 9716 new cases of chronic heart failure with an available LVEF in Stockholm, Sweden, from January 1, 2015, until December 31, 2020. All values of LVEF were collected over time, and patients were followed up until death, moving out of Stockholm, or end of study. Mixed models were used to quantify within-person variance in LVEF, and multistate Markov models, with death as an absorbing state, to quantify the stability of LVEF categories. LVEF values followed a normal distribution. The SD of the within-person variance in LVEF over time was 7.4%. The mean time spent in any LVEF category before transition to another category was on average <1 year for heart failure with mildly reduced ejection fraction. Probabilities of transitioning between categories during the first year were substantial; patients with heart failure with mildly reduced ejection fraction had a probability of <25% of remaining in that category 1 year later.

CONCLUSIONS

LVEF follows a normal distribution and has considerable variability over time, which may impose a risk for underuse of efficient treatment. The heart failure with mildly reduced ejection fraction category is especially inconstant. Assumptions of a patient's current LVEF should take this variability and the normal distribution of LVEF into account.

Left ventricular ejection fraction: clinical, pathophysiological, and technical limitations

Risk stratification of cardiovascular death and treatment strategies in patients with heart failure (HF), the optimal timing for valve replacement, and the selection of patients for implantable cardioverter defibrillators are based on an echocardiographic calculation of left ventricular ejection fraction (LVEF) in most guidelines. As a marker of systolic function, LVEF has important limitations being affected by loading conditions and cavity geometry, as well as image quality, thus impacting inter- and intra-observer measurement variability. LVEF is a product of shortening of the three components of myocardial fibres: longitudinal, circumferential, and oblique. It is therefore a marker of global ejection performance based on cavity volume changes, rather than directly reflecting myocardial contractile function, hence may be normal even when myofibril's systolic function is impaired. Sub-endocardial longitudinal fibers are the most sensitive layers to ischemia, so when dysfunctional, the circumferential fibers may compensate for it and maintain the overall LVEF. Likewise, in patients with HF, LVEF is used to stratify subgroups, an approach that has prognostic implications but without a direct relationship. HF is a dynamic disease that may worsen or improve over time according to the underlying pathology. Such dynamicity impacts LVEF and its use to guide treatment. The same applies to changes in LVEF following interventional procedures. In this review, we analyze the clinical, pathophysiological, and technical limitations of LVEF across a wide range of cardiovascular pathologies.

Noninvasive Electrical Mapping Compared with the Paced QRS Complex for Optimizing CRT Programmed Settings and Predicting Multidimensional Response

The aim was to test the hypothesis that left ventricular (LV) and right ventricular (RV) activation from body surface electrical mapping (CardioInsight 252-electrode vest, Medtronic) identifies optimal cardiac resynchronization therapy (CRT) pacing strategies and outcomes in 30 patients. The LV80, RV80, and BIV80 were defined as the times to 80% LV, RV, or biventricular electrical activation. Smaller differences in the LV80 and RV80 (|LV80-RV80|) with synchronized LV pacing predicted better LV function post-CRT (p = 0.0004) than the LV-paced QRS duration (p = 0.32). Likewise, a lower RV80 was associated with a better pre-CRT RV ejection fraction by CMR (r =  - 0.40, p = 0.04) and predicted post-CRT improvements in myocardial oxygen uptake (p = 0.01) better than the biventricular-paced QRS (p = 0.38), while a lower LV80 with BIV pacing predicted lower post-CRT B-type natriuretic peptide (BNP) (p = 0.02). RV pacing improved LV function with smaller |LV80-RV80| (p = 0.009). In conclusion, 3-D electrical mapping predicted favorable post-CRT outcomes and informed effective pacing strategies.

Prognostic implications of left ventricular ejection fraction trajectory changes in heart failure

Aims

The latest guidelines recommended to assess the trajectory of left ventricular ejection fraction (LVEF) in patients with heart failure (HF). However, there is limited data on the trajectory of LVEF in real-world settings. In this study, we investigated the frequency and prognostic implications of changes in LVEF trajectory.

Methods

Patients were divided into intensified LVEF, static LVEF, and worsening LVEF groups based on the transitions of HF types from baseline to follow-up. The intensified and worsening LVEF groups were further subdivided into mild (≤10% absolute changes of LVEF) and significant (>10% absolute changes of LVEF) increase or decrease groups according to the magnitude of change. The incidences and associations of changes in LVEF with patient outcomes were analyzed.

Results

Among the 2,429 patients in the study cohort, 38.3% of HF with reduced ejection fraction (HFrEF) and 37.6% of HF with mildly reduced ejection fraction (HFmrEF) showed an improvement in their LVEF. In contrast, a decline in LVEF was observed in 19.3% of HF patients with preserved ejection fraction (HFpEF) and 34.9% of those with HFmrEF. Cox regression analysis showed that the intensified LVEF group was associated with a lower risk of composite endpoints, while the worsening LVEF group yielded opposite findings. Subgroup analysis revealed that compared to those with mild changes in LVEF, baseline HFrEF patients with significant increase showed a lower risk of composite outcome, while baseline HFpEF patients were the opposite.

Conclusions

The trajectories of LVEF changes are strongly correlated with outcomes in patients with HF who had prior history of HF admission. The most significant prognostic implications observed in patients with significant LVEF changes. Trajectory LVEF and type of HF changes are useful tools recommended for prognostication.

Cardiac magnetic resonance defines mechanisms of sex-based differences in outcomes following cardiac resynchronization therapy

Background

Mechanisms of sex-based differences in outcomes following cardiac resynchronization therapy (CRT) are poorly understood.

Objective

To use cardiac magnetic resonance (CMR) to define mechanisms of sex-based differences in outcomes after CRT and describe distinct CMR-based phenotypes of CRT candidates based on sex and non-ischemic/ischemic cardiomyopathy type.

Materials and methods

In a prospective study, sex-based differences in three short-term CRT response measures [fractional change in left ventricular end-systolic volume index 6 months after CRT (LVESVI-FC), B-type natriuretic peptide (BNP) 6 months after CRT, change in peak VO₂ 6 months after CRT], and long-term survival were evaluated with respect to 39 baseline parameters from CMR, exercise testing, laboratory testing, electrocardiograms, comorbid conditions, and other sources. CMR was also used to quantify the degree of left-ventricular mechanical dyssynchrony by deriving the circumferential uniformity ratio estimate (CURE-SVD) parameter from displacement encoding with stimulated echoes (DENSE) strain imaging. Statistical methods included multivariable linear regression with evaluation of interaction effects associated with sex and cardiomyopathy type (ischemic and non-ischemic cardiomyopathy) and survival analysis.

Results

Among 200 patients, the 54 female patients (27%) pre-CRT had a smaller CMR-based LVEDVI (p = 0.04), more mechanical dyssynchrony based on the validated CMR CURE-SVD parameter (p = 0.04), a lower frequency of both late gadolinium enhancement (LGE) and ischemic cardiomyopathy (p < 0.0001), a greater RVEF (p = 0.02), and a greater frequency of LBBB (p = 0.01). After categorization of patients into four groups based on cardiomyopathy type (ischemic/non-ischemic cardiomyopathy) and sex, female patients with non-ischemic cardiomyopathy had the lowest CURE-SVD (p = 0.003), the lowest pre-CRT BNP levels (p = 0.01), the lowest post-CRT BNP levels (p = 0.05), and the most favorable LVESVI-FC (p = 0.001). Overall, female patients had better 3-year survival before adjustment for cardiomyopathy type (p = 0.007, HR = 0.45) and after adjustment for cardiomyopathy type (p = 0.009, HR = 0.67).

Conclusion

CMR identifies distinct phenotypes of female CRT patients with non-ischemic and ischemic cardiomyopathy relative to male patients stratified by cardiomyopathy type. The more favorable short-term response and long-term survival outcomes in female heart failure patients with CRT were associated with lower indexed CMR-based LV volumes, decreased presence of scar associated with prior myocardial infarction and ICM, and greater CMR-based dyssynchrony with the CURE-SVD.

Machine learning for multidimensional response and survival after cardiac resynchronization therapy using features from cardiac magnetic resonance

Background

Cardiac resynchronization therapy (CRT) response is complex, and better approaches are required to predict survival and need for advanced therapies.

Objective

The objective was to use machine learning to characterize multidimensional CRT response and its relationship with long-term survival.

Methods

Associations of 39 baseline features (including cardiac magnetic resonance [CMR] findings and clinical parameters such as glomerular filtration rate [GFR]) with a multidimensional CRT response vector (consisting of post-CRT left ventricular end-systolic volume index [LVESVI] fractional change, post-CRT B-type natriuretic peptide, and change in peak VO₂) were evaluated. Machine learning generated response clusters, and cross-validation assessed associations of clusters with 4-year survival.

Results

Among 200 patients (median age 67.4 years, 27.0% women) with CRT and CMR, associations with more than 1 response parameter were noted for the CMR CURE-SVD dyssynchrony parameter (associated with post-CRT brain natriuretic peptide [BNP] and LVESVI fractional change) and GFR (associated with peak VO₂ and post-CRT BNP). Machine learning defined 3 response clusters: cluster 1 (n = 123, 90.2% survival [best]), cluster 2 (n = 45, 60.0% survival [intermediate]), and cluster 3 (n = 32, 34.4% survival [worst]). Adding the 6-month response cluster to baseline features improved the area under the receiver operating characteristic curve for 4-year survival from 0.78 to 0.86 (P = .02). A web-based application was developed for cluster determination in future patients.

Conclusion

Machine learning characterizes distinct CRT response clusters influenced by CMR features, kidney function, and other factors. These clusters have a strong and additive influence on long-term survival relative to baseline features.