Improving the Characterization of Stage A and B Heart Failure by Adding Global Longitudinal Strain

Artificial Intelligence Enabled Prediction of Heart Failure Risk from Single-lead Electrocardiograms

Importance

Despite the availability of disease-modifying therapies, scalable strategies for heart failure (HF) risk stratification remain elusive. Portable devices capable of recording single-lead electrocardiograms (ECGs) can enable large-scale community-based risk assessment.

Objective

To evaluate an artificial intelligence (AI) algorithm to predict HF risk from noisy single-lead ECGs.

Design

Multicohort study.

Setting

Retrospective cohort of individuals with outpatient ECGs in the integrated Yale New Haven Health System (YNHHS) and prospective population-based cohorts of UK Biobank (UKB) and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

Participants

Individuals without HF at baseline.

Exposures

AI-ECG-defined risk of left ventricular systolic dysfunction (LVSD).

Main Outcomes and Measures

Among individuals with ECGs, we isolated lead I ECGs and deployed a noise-adapted AI-ECG model trained to identify LVSD. We evaluated the association of the model probability with new-onset HF, defined as the first HF hospitalization. We compared the discrimination of AI-ECG against two risk scores for new-onset HF (PCP-HF and PREVENT equations) using Harrel's C-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI).

Results

There were 192,667 YNHHS patients (age 56 years [IQR, 41-69], 112,082 women [58%]), 42,141 UKB participants (65 years [59-71], 21,795 women [52%]), and 13,454 ELSA-Brasil participants (56 years [41-69], 7,348 women [55%]) with baseline ECGs. A total of 3,697 developed HF in YNHHS over 4.6 years (2.8-6.6), 46 in UKB over 3.1 years (2.1-4.5), and 31 in ELSA-Brasil over 4.2 years (3.7-4.5). A positive AI-ECG screen was associated with a 3- to 7-fold higher risk for HF, and each 0.1 increment in the model probability portended a 27-65% higher hazard across cohorts, independent of age, sex, comorbidities, and competing risk of death. AI-ECG's discrimination for new-onset HF was 0.725 in YNHHS, 0.792 in UKB, and 0.833 in ELSA-Brasil. Across cohorts, incorporating AI-ECG predictions in addition to PCP-HF and PREVENT equations resulted in improved Harrel's C-statistic (ΔPCP-HF=0.112-0.114; ΔPREVENT=0.080-0.101). AI-ECG had IDI of 0.094-0.238 and 0.090-0.192, and NRI of 15.8%-48.8% and 12.8%-36.3%, vs. PCP-HF and PREVENT, respectively.

Conclusions and Relevance

Across multinational cohorts, a noise-adapted AI model defined HF risk using lead I ECGs, suggesting a potential portable and wearable device-based HF risk-stratification strategy.

Screening for Heart Failure: Biomarkers to Detect Heightened Risk in the General Population

PURPOSE OF REVIEW

Heart failure (HF) represents a growing global burden of morbidity and mortality. Identifying individuals at risk for HF development is increasingly important, particularly given the advent of disease-modifying therapies for HF as well as its major risk factors such as obesity actalnd diabetes. We aim to review the key circulating biomarkers associated with future HF which may contribute to HF risk prediction.

RECENT FINDINGS

While current guidelines recommend the use of natriuretic peptides and cardiac troponins in HF risk stratification, there are a diverse array of other emerging protein, metabolic, transcriptomic, and genomic biomarkers of future HF development. These biomarkers not only lend insight into the underlying pathophysiology of HF, which spans inflammation to cardiac fibrosis, but also offer an opportunity to further refine HF risk in addition to established biomarkers. As evolving techniques in molecular biology enable an increased understanding of the complex biologic contributions to HF pathophysiology, there is an important opportunity to construct integrated clinical and multi-omic models to best capture HF risk. Moving forward, future studies should seek to understand the contributions of sex differences, underlying comorbidity burden, and HF subtypes to an individual's HF risk. Further studies are necessary to fully define the clinical utility of biomarker screening approaches to refine HF risk assessment, as well as to link risk assessment directly to preventive strategies for HF.

Global longitudinal strain manually measured from mid-myocardial lengths is a reliable alternative to speckle tracking global longitudinal strain

BACKGROUND

Global longitudinal strain (GLS) is a useful marker for the echocardiographic evaluation of left ventricular (LV) systolic dysfunction. Presently GLS is derived from speckle tracking of LV images, but speckle tracking software is not always available. We seek to determine if manually measured GLS (MM-GLS) by assessing mid-myocardial lengths can be a reliable alternative to speckle tracking GLS (ST-GLS).

METHODS

Transthoracic echocardiogram images of a tertiary hospital in Australia were retrospectively analyzed to study the relationships between ST-GLS, MM-GLS, and LV ejection fraction (LVEF). We further evaluated the impact of image quality and regional wall motion abnormalities on those relationships.

RESULTS

Echocardiography studies from 154 patients were included (female sex, 36%; mean age, 61.7 ± 14.8 years). The average LVEF was 51.3% ± 11.3% and the average ST-GLS was 16.7 ± 3.8. MM-GLS strongly correlated with ST-GLS (intraclass correlation coefficient, 0.986; P < 0.001) and with LVEF regardless of the presence of regional wall motion abnormalities. If using GLS cutoff of more than 18% as normal, 97.5% of studies with normal ST-GLS had normal MM-GLS. If using GLS cutoff as less than 16% as abnormal, 95.5% of studies with abnormal ST-GLS had abnormal MM-GLS. There was no case with ST-GLS > 18% and MM-GLS < 16%, nor were there any case in with ST-GLS < 16% and MM-GLS > 18%.

CONCLUSIONS

MM-GLS correlates strongly with ST-GLS. If ST-GLS cannot be accurately assessed, MM-GLS may be a useful alternative to provide GLS values in both clinical and research studies.

BEEAF2 Score: A New Risk Stratification Score for Patients With Stage B Heart Failure From the KUNIUMI Registry Chronic Cohort

BACKGROUND

Stage B heart failure (HF) refers to structural heart disease without signs or symptoms of HF, so that early intervention may delay or prevent the onset of overt HF. However, stage B HF is a very broad concept, and risk stratification of such patients can be challenging.

METHODS AND RESULTS

We conducted a prospective study of data for 1646 consecutive patients with HF from the KUNIUMI (Kobe University Heart Failure Registry in Awaji Medical Center) registry chronic cohort. The definition of HF stages was based on current guidelines for classification of 29 patients as stage A HF, 761 as stage B HF, 827 as stage C HF, and 29 patients as stage D HF. The primary end point was the time-to-first-event defined as cardiovascular death or HF hospitalization within 2.0 years of follow-up. A maximum of 6 adjustment factor points was assigned based on Cox proportional hazards analysis findings for the hazard ratio (HR) of independent risk factors for the primary end point: 1 point for anemia, estimated glomerular filtration rate <45 mL/min per 1.73 m2, brain natriuretic peptide ≥150 pg/mL, and average ratio of early transmitral flow velocity to early diastolic mitral annular velocity >14, and 2 points for clinical frailty scale >3. Patients with stage B HF were stratified into 3 groups, low risk (0-1 points), moderate risk (2-3 points), and high risk (4-6 points). Based on this scoring system (BEEAF2 [brain natriuretic peptide, estimated glomerular filtration rate, ratio of early transmitral flow velocity to early diastolic mitral annular velocity, anemia, and frailty]), the outcome was found to become worse in accordance with risk level. High-risk patients with stage B HF and patients with stage C HF showed similar outcomes.

CONCLUSIONS

Our scoring system offers an easy-to-use evaluation of risk stratification for patients with stage B HF.

Artificial intelligence-derived left ventricular strain in echocardiography in patients treated with chemotherapy

Global longitudinal strain (GLS) is an echocardiographic measure to detect chemotherapy-related cardiovascular dysfunction. However, its limited availability and the needed expertise may restrict its generalization. Artificial intelligence (AI)-based GLS might overcome these challenges. Our aims are to explore the agreements between AI-based GLS and conventional GLS, and to assess whether the agreements were influenced by expertise levels, cardiac remodeling and cardiovascular diseases/risks. Echocardiographic images in the apical four-chamber view of left ventricle were retrospectively analyzed based on AI-based GLS in patients treated with chemotherapy, and correlation between AI-based GLS (Caas Qardia, Pie Medical Imaging) and conventional GLS (Vivid E9/VividE95, GE Healthcare) were assessed. The agreement between unexperienced physicians ("GLS beginner") and experienced echocardiographer were also assessed. Among 94 patients (mean age 69 ± 12 years, 73% female), mean left ventricular ejection fraction was 64 ± 6%, 14% of patients had left ventricular hypertrophy, and 21% had left atrial enlargement. Mean GLS was - 15.9 ± 3.4% and - 19.0 ± 3.7% for the AI and conventional method, respectively. There was a moderate correlation between these methods (rho = 0.74; p < 0.01), and bias was - 3.1% (95% limits of agreement: -8.1 to 2.0). The reproducibility between GLS beginner and an experienced echocardiographer was numerically better in the AI method than the conventional method (inter-observer agreement = 0.82 vs. 0.68). The agreements were consistent across abnormal cardiac structure and function categories (p-for-interaction > 0.10). In patients treated with chemotherapy. AI-based GLS was moderately correlated with conventional GLS and provided a numerically better reproducibility compared with conventional GLS, regardless of different levels of expertise.

Racial Differences in Diabetic Cardiomyopathy: The ARISE-HF Trial

BACKGROUND

Diabetic cardiomyopathy (DbCM) increases risk of overt heart failure in individuals with diabetes mellitus. Racial and ethnic differences in DbCM remain unexplored.

OBJECTIVES

The authors sought to identify racial and ethnic differences among individuals with type 2 diabetes mellitus, structural heart disease, and impaired exercise capacity.

METHODS

The ARISE-HF (Aldolase Reductase Inhibitor for Stabilization of Exercise Capacity in Heart Failure) trial is assessing the efficacy of an aldose reductase inhibitor for exercise capacity preservation in 691 persons with DbCM. Baseline characteristics, echocardiographic parameters, and functional capacity were analyzed and stratified by race and ethnicity.

RESULTS

The mean age of the study participants was 67.4 years; 50% were women. Black and Hispanic patients had lower use of diabetes mellitus treatments. Black patients had poorer baseline ventricular function and more impaired global longitudinal strain. Overall, health status was preserved, based on Kansas City Cardiomyopathy Questionnaire scores, but reduced exercise capacity was present as evidenced by reduced Physical Activity Scale for the Elderly (PASE) scores. When stratified by race and ethnicity and compared with the entire cohort, Black patients had poorer health status, more reduced physical activity, and a greater impairment in exercise capacity during cardiopulmonary exercise testing, whereas Hispanic patients also displayed compromised cardiopulmonary exercise testing functional capacity. White patients demonstrated higher physical activity and functional capacity.

CONCLUSIONS

Racial and ethnic differences exist in baseline characteristics of persons affected by DbCM, with Black and Hispanic study participants demonstrating higher risk features. These insights inform the need to address differences in the population with DbCM. (Safety and Efficacy of AT-001 in Patients With Diabetic Cardiomyopathy [ARISE-HF]; NCT04083339).

A simplified approach to discriminate between healthy subjects and patients with heart failure using cardiac magnetic resonance myocardial deformation imaging

Aims

Left ventricular global longitudinal strain (LV-GLS) shows promise as a marker to detect early heart failure (HF). This study sought to (i) establish cardiac magnetic resonance imaging (CMR)-derived LV-GLS cut-offs to differentiate healthy from HF for both acquisition-based and post-processing techniques, (ii) assess agreement, and (iii) provide a method to convert LV-GLS between both techniques.

Methods and results

A secondary analysis of a prospective study enrolling healthy subjects (n = 19) and HF patients (n = 56) was conducted. LV-GLS was measured using fast strain-encoded imaging (fSENC) and feature tracking (FT). Receiver operating characteristic (ROC) analyses were performed to derive and evaluate LV-GLS cut-offs discriminating between healthy, HF with mild deformation impairment (DI), and HF with severe DI. Linear regression and Bland-Altman analyses assessed agreement. Cut-offs discriminating between healthy and HF were identified at -19.3% and -15.1% for fSENC and FT, respectively. Cut-offs of -15.8% (fSENC) and -10.8% (FT) further distinguished mild from severe DI. No significant differences in area under ROC curve were identified between fSENC and FT. Bland-Altman analysis revealed a bias of -4.01%, 95% CI -4.42, -3.50 for FT, considering fSENC as reference. Linear regression suggested a factor of 0.76 to rescale fSENC-derived LV-GLS to FT. Using this factor on fSENC-derived cut-offs yielded rescaled FT LV-GLS cut-offs of -14.7% (healthy vs. HF) and -12% (mild vs. severe DI).

Conclusion

LV-GLS distinguishes healthy from HF with high accuracy. Each measurement technique requires distinct cut-offs, but rescaling factors facilitate conversion. An FT-based LV-GLS ≥ -15% simplifies HF detection in clinical routine.

ELUCIDATE Trial: A Single-Center Randomized Controlled Study

BACKGROUND

Dapagliflozin, a sodium-glucose cotransporter 2 inhibitor, is an epochal oral antidiabetic drug that improves cardiorenal outcomes. However, the effect of early dapagliflozin intervention on left ventricular (LV) remodeling in patients with type 2 diabetes free from cardiovascular disease remains unclear.

METHODS AND RESULTS

The ELUCIDATE trial was a prospective, open-label, randomized, active-controlled study that enrolled 76 patients with asymptomatic type 2 diabetes with LV ejection fraction ≥50%, randomized to the dapagliflozin 10 mg/day add-on or standard-of-care group. Speckle-tracking echocardiography-based measurements of the cardiac global longitudinal strain were performed at baseline and 24 weeks after treatment initiation. Patients who received dapagliflozin had a greater reduction in LV dimension (1.68 mm [95% CI, 0.53-2.84]; P=0.005), LV end-systolic volume (5.51 mL [95% CI, 0.86-10.17]; P=0.021), and LV mass index (4.25 g/m2.7 [95% CI, 2.42-6.09]; P<0.0001) compared with standard of care in absolute mean differences. Dapagliflozin add-on therapy led to a significant LV global longitudinal strain increment (0.74% [95% CI, 1.00-0.49]; P<0.0001) and improved LV systolic and early diastolic strain rates (0.27/s [95% CI, 0.17-0.60]; and 0.11/s [95% CI, 0.06-0.16], respectively; both P<0.0001) but not in global circumferential strain. No significant changes were found in insulin resistance, NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels, or other biomarkers at 6 months after the dapagliflozin administration.

CONCLUSIONS

Dapagliflozin add-on therapy could lead to more favorable cardiac remodeling accompanied by enhanced cardiac mechanical function among patients with asymptomatic type 2 diabetes. Our findings provide evidence of the efficacy of dapagliflozin use for the primary prevention of diabetic cardiomyopathy.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT03871621.

Use of Clinical and Echocardiographic Evaluation to Assess the Risk of Heart Failure

BACKGROUND

Clinical and echocardiographic features predict incident heart failure (HF), but the optimal strategy for combining them is unclear.

OBJECTIVES

This study sought to define an effective means of using echocardiography in HF risk evaluation.

METHODS

The same clinical and echocardiographic evaluation was obtained in 2 groups with HF risk factors: a training group (n = 926, followed to 7 years) and a validation group (n = 355, followed to 10 years). Clinical risk was categorized as low, intermediate, and high using 4-year ARIC (Atherosclerosis Risk In Communities) HF risk score cutpoints of 9% and 33%. A risk stratification algorithm based on clinical risk and echocardiographic markers of stage B HF (SBHF) (abnormal global longitudinal strain [GLS], diastolic dysfunction, or left ventricular hypertrophy) was developed using a classification and regression tree analysis and was validated.

RESULTS

HF developed in 12% of the training group, including 9%, 18%, and 73% of low-, intermediate-, and high-risk patients. HF occurred in 8.6% of stage A HF and 19.4% of SBHF (P < 0.001), but stage A HF with clinical risk of ≥9% had similar outcome to SBHF. Abnormal GLS (HR: 2.92 [95% CI: 1.95-4.37]; P < 0.001) was the strongest independent predictor of HF. Normal GLS and diastolic function reclassified 61% of the intermediate-risk group into the low-risk group (HF incidence: 12%). In the validation group, 11% developed HF over 4.5 years; 4%, 17%, and 39% of low-, intermediate-, and high-risk groups. Similar results were obtained after exclusion of patients with known coronary artery disease. The echocardiographic parameters also provided significant incremental value to the ARIC score in predicting new HF admission (C-statistic: 0.78 [95% CI: 0.71-0.84] vs 0.83 [95% CI: 0.77-0.88]; P = 0.027).

CONCLUSIONS

Clinical risk assessment is adequate to classify low and high HF risk. Echocardiographic evaluation reclassifies 61% of intermediate-risk patients.

Glycemic Status and Myocardial Strain by Cardiac MRI in Patients With ST-Segment Elevation Myocardial Infarction

BACKGROUND

It is uncertain how various degree of glycemic status affect left ventricular (LV) myocardial strain in ST-segment elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention (PPCI).

PURPOSE

To investigate the relationship of glycemic status and myocardial strain in STEMI patients.

STUDY TYPE

Prospective cohort study.

POPULATION

282 STEMI patients with cardiac magnetic resonance imaging 5 ± 2 days post-PPCI. Patients were divided into three groups based on the level of glycated hemoglobin A1c (HbA1c) (group 1: HbA1c < 5.7%; group 2: 5.7% ≤ HbA1c < 6.5%; group 3: HbA1c ≥ 6.5%).

FIELD STRENGTH/SEQUENCE

3.0-T; late gadolinium enhancement, balanced steady-state free precession cine sequence, black blood fat-suppressed T2-weighted.

ASSESSMENT

LV function, myocardial strain, and infarct characteristics (infarct size, microvascular obstruction, and intramyocardial hemorrhage) were compared among the three groups by one-way analysis of variance (ANOVA) or Wilcoxon rank sum test. Intraobserver and interobserver reproducibility of LV myocardial strain was evaluated.

STATISTICAL TESTS

ANOVA or Wilcoxon rank sum test, Pearson chi-square or Fisher's exact test, Spearman's correlation analyses and multivariable linear regression analysis. A two-tailed P value <0.05 was considered statistically significant.

RESULTS

Infarct characteristics were similar among the three groups (P = 0.934, P = 0.097, P = 0.533, respectively). Patients with HbA1c ≥ 6.5% had decreased LV myocardial strain compared with HbA1c 5.7%-6.4%, as evidenced by global radial (GRS), global circumferential (GCS), and global longitudinal (GLS) strain. However, no significant differences in myocardial strain were observed between patients with HbA1c 5.7%-6.4% and HbA1c < 5.7% (P = 0.716; P = 0.294; P = 0.883, respectively). After adjustment for confounders, HbA1c as a continuous variable (beta coefficient [β] = -0.676; β = 0.172; β = 0.205, respectively) and HbA1c ≥ 6.5% (β = -3.682; β = 0.552; β = 0.681, respectively) were both independently associated with decreased GRS, GCS, and GLS.

DATA CONCLUSION

Patients with uncontrolled blood glucose (categorized in group HbA1c ≥ 6.5%) had worse myocardial strain. The level of HbA1c appeared to be independently associated with decreased myocardial strain in STEMI patients.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2.

Sex difference in the age-related decline of global longitudinal strain of left ventricle

Global longitudinal strain (GLS) is a valuable indicator of subclinical myocardial dysfunction. Whether the effect of aging on subclinical left ventricular dysfunction is sex-specific is not well documented. This study aimed to identify age-related changes in GLS according to sex in patients with a normal left ventricular ejection fraction (LVEF). In this cross-sectional, single-center cohort study in Korea, participants who underwent GLS measurement using 2D speckle-tracking echocardiography were retrospectively reviewed, and participants with normal LVEF (≥ 55%) without documented cardiovascular disease were included. Reduced GLS was defined as absolute values below 18%. Of 682 study participants (mean age, 58; female, 51.5%), 209 (30.6%) had reduced GLS. Females with reduced GLS were older than those with normal GLS (68 vs. 58 years, P < 0.001); with no difference of age in males (55 vs. 57 years; P = 0.265). Univariate analysis showed age to correlate significantly with reduced GLS only in female (r =  - 0.364; P < 0.001). In multivariable analysis, female > 66 years old had significantly higher risk of reduced GLS (Odds ratio 2.66; 95% CI 1.22-5.76; P = 0.014). In participants with normal LVEF, GLS decreased with age in females but not in males. Particularly, females aged 66 years and older had a significantly higher risk of reduced GLS. These findings suggest that GLS could be a valuable parameter for assessing subclinical cardiac dysfunction, especially in older females.

Echocardiographic Features Beyond Ejection Fraction and Associated Outcomes in Patients With Heart Failure With Mildly Reduced or Preserved Ejection Fraction

BACKGROUND

Heart failure (HF) guidelines recommend assessment of left ventricular ejection fraction (LVEF) to classify patients and guide therapy implementation. However, LVEF alone may be insufficient to adequately characterize patients with HF, especially those with mildly reduced or preserved LVEF. Recommendations on additional testing are lacking, and there are limited data on use of echocardiographic features beyond LVEF in patients with heart failure with mildly reduced or preserved LVEF.

METHODS

In patients with HF with mildly reduced or preserved LVEF identified in a large US health care system, the association of the following metrics with mortality was evaluated: LV global longitudinal strain (LV GLS>-16), left atrial volume index (>28 mL/m2), left ventricular hypertrophy (LVH), and E/e´>13 and e´<9. A multivariable model for mortality was constructed including age, sex, and key comorbidities followed by stepwise selection of echocardiographic features. Characteristics and outcomes of subgroups with normal versus abnormal LV GLS and LVEF were evaluated.

RESULTS

Among 2337 patients with complete echocardiographic data assessed between 2017 and 2020, the following features were associated with all-cause mortality on univariate analysis over 3 years of follow-up: E/e´+e´, LV GLS, left atrial volume index (all P<0.01). In the multivariable model (C-index=0.65), only abnormal LV GLS was independently associated with all-cause mortality (HR, 1.35 [95% CI, 1.11-1.63]; P=0.002). Among patients with LVEF>55%, 498/1255 (40%) demonstrated abnormal LV GLS. Regardless of specific LVEF, patients with abnormal LV GLS demonstrated a higher burden of multiple comorbidities and higher event rates compared with patients with normal LV GLS.

CONCLUSIONS

In a large, real-world HF with mildly reduced or preserved LVEF population, echocardiographic features, led by LV GLS, were associated with adverse outcomes irrespective of LVEF. A large proportion of patients demonstrate adverse myocardial function by LV GLS despite preserved LVEF and may represent a key cohort of interest for HF medical therapies and future clinical studies.

Metanephrine and normetanephrine associated with subclinical myocardial injuries in pheochromocytoma and paraganglioma

Objective

To analyze the correlation between metanephrine and normetanephrines (MNs) and subclinical myocardial injuries (SMI) diagnosed by low left ventricular global longitudinal strain (LV GLS) in patients with pheochromocytoma and paraganglioma (PPGL).

Methods

Seventy-six patients who underwent surgery for pheochromocytoma or paraganglioma from September 2017 to April 2022 were examined. All the patients enrolled had normal left ventricular ejection fraction (LVEF) and myocardial injury biomarkers including cardiac troponin I and B-natriuretic peptide. Univariate analysis and multivariate analysis were performed to evaluate the association of MNs and subclinical myocardial injury (SMI)(defined as LV GLS<18).

Results

LV GLS of 13(17.11%) PPGL patients was less than 18. The percentage of patients with elevation of single hormone (metanephrine, normetanephrine, 3-methoxytyramine) or any one of MNs was not significantly correlated with SMI (P=0.987, 0.666, 0.128 and 0.918, respectively). All MNs elevation was associated with SMI (OR: 11.27; 95% CI, 0.94—135.24; P= 0.056). After adjusting for age, All MNs elevation was significantly correlated with SMI (OR: 16.54; 95% CI, 1.22—223.62; P= 0.035).

Conclusion

MNs might be an important factor influencing myocardial function. All MNs elevation might indicate SMI. If all MNs elevated, LV GLS measurement was recommended for PPGL patients to detect SMI in the absence of decrease LVEF or other heart disease in clinical practice.