Role of global longitudinal strain in assessment of left ventricular systolic function in patients with heart failure with preserved ejection fraction

Left Ventricular and Atrial Deformation in Patients with Acute Decompensated Heart Failure: A Pilot Study

AIMS

The aims of this study were to compare global longitudinal strain of the left ventricle (LV-GLS) and reservoir strain of the left atrium (R-LAS) values between patients with acute decompensation of chronic heart failure (HF) and a control group.

METHODS

Sixteen patients admitted to our ward for acute decompensation of HF were enrolled in this study. Transthoracic echocardiography (TTE) with two-dimensional speckle-tracking analysis (2D ST) was performed in each patient. The patients were divided into two subgroups according to the value of left ventricular ejection fraction (EF) using a cut-off value of ≤40% to distinguish heart failure with reduced ejection fraction (HFrEF) from heart failure with preserved ejection fraction (HFpEF). The control group consisted of 16 individuals without a history of cardiovascular disease, each of whom underwent 2D ST analysis as well.

RESULTS

We found that LV-GLS and R-LAS were significantly lower in both the HFrEF and HFpEF subgroups in comparison with the control group (LV-GLS: -13.4 ± 4.7% vs. -19.7 ± 2.5%, p ˂ 0.05; R-LAS: +12.2 ± 6.9% vs. +40.3 ± 7.4%, p ˂ 0.05). Furthermore, there was a significant difference in LV-GLS (-9.6 ± 3.2% vs. -15.2 ± 4.3%, p ˂ 0.05) but not in R-LAS (+13.7 ± 8.6% vs. +11.4 ± 6.2%) between the HFrEF and HFpEF subgroups.

CONCLUSIONS

Our study demonstrated a significant difference in LV-GLS and R-LAS in all enrolled HF patients compared to the control group. There was also a significant difference in LV-GLS between the HFrEF and HFpEF subgroups.

Assessment of Myocardial Mechanics in Acute Rheumatic Fever Using Speckle-Tracking Echocardiography

BACKGROUND

This study aims to evaluate the role of speckle-tracking echocardiography to identify myocardial deformation in acute rheumatic fever.

METHODS

Twenty-seven patients and 27 healthy children were prospectively evaluated. The patient group was divided into 2 subgroups based on echocardiographic findings, with or without carditis. The left ventricular global longitudinal strain and strain rate, left ventricular global circumferential strain and strain rate, and right ventricular global lon-gitudinal strain and strain rate were assessed by speckle-tracking echocardiography.

RESULTS

In the acute phase of the disease, all values except the right ventricular global longitudinal strain were found to be significantly below the control group in the patient cohort. No significant difference was found between the patients grouped as carditis and non-carditis in the acute period. Comparison of the acute period with the post-treatment period revealed a significant increase in all strain values of the patients with carditis and significant increases observed in all values except left ventricular global longitudinal strain rate, left ventricular global circumferential strain rate, and right ventricular global longitudinal strain rate values in patients without carditis. Apart from the right ventricular global longitudinal strain rate, which was significantly lower in the non-carditis group compared to the control group, there was no significant difference in strain values between the patient and control groups following treatment.

CONCLUSION

In the present study, we found that all patients, including patients in whom no valvular involvement was detected by echocardiography in the acute phase of acute rheumatic fever, had a lower right and left ventricular strain and strain rate measurements and that these findings improved after treatment, suggesting that strain echocardiography may be a helpful diagnostic method, especially in patients without valvular involvement.

Detecting heart failure using novel bio-signals and a knowledge enhanced neural network

BACKGROUND

Clinical decisions about Heart Failure (HF) are frequently based on measurements of left ventricular ejection fraction (LVEF), relying mainly on echocardiography measurements for evaluating structural and functional abnormalities of heart disease. As echocardiography is not available in primary care, this means that HF cannot be detected on initial patient presentation. Instead, physicians in primary care must rely on a clinical diagnosis that can take weeks, even months of costly testing and clinical visits. As a result, the opportunity for early detection of HF is lost.

METHODS AND RESULTS

The standard 12-Lead ECG provides only limited diagnostic evidence for many common heart problems. ECG findings typically show low sensitivity for structural heart abnormalities and low specificity for function abnormalities, e.g., systolic dysfunction. As a result, structural and functional heart abnormalities are typically diagnosed by echocardiography in secondary care, effectively creating a diagnostic gap between primary and secondary care. This diagnostic gap was successfully reduced by an AI solution, the Cardio-HART™ (CHART), which uses Knowledge-enhanced Neural Networks to process novel bio-signals. Cardio-HART reached higher performance in prediction of HF when compared to the best ECG-based criteria: sensitivity increased from 53.5% to 82.8%, specificity from 85.1% to 86.9%, positive predictive value from 57.1% to 70.0%, the F-score from 56.4% to 72.2%, and area under curve from 0.79 to 0.91. The sensitivity of the HF-indicated findings is doubled by the AI compared to the best rule-based ECG-findings with a similar specificity level: from 38.6% to 71%.

CONCLUSION

Using an AI solution to process ECG and novel bio-signals, the CHART algorithms are able to predict structural, functional, and valve abnormalities, effectively reducing this diagnostic gap, thereby allowing for the early detection of most common heart diseases and HF in primary care.

The impact of medical therapy on left ventricular strain: Current state and future perspectives

The speckle tracking strain is becoming a frequently used marker of subclinical left ventricular systolic dysfunction. Despite the wide range of data concerning left ventricular strain variability in the general population and its changes in various pathologic conditions, the information about the impact of medical therapy on left ventricle strain is limited. This article provides an analysis of published studies of left ventricle strain changes in response to different agents and combinations of medical therapies used for hypertension and congestive heart failure.

Long-Term Cardiovascular Effects of COVID-19: Emerging Data Relevant to the Cardiovascular Clinician

Purpose of Review

COVID-19 is now a global pandemic and the illness affects multiple organ systems, including the cardiovascular system. Long-term cardiovascular consequences of COVID-19 are not yet fully characterized. This review seeks to consolidate available data on long-term cardiovascular complications of COVID-19 infection.

Recent Findings

Acute cardiovascular complications of COVID-19 infection include myocarditis, pericarditis, acute coronary syndrome, heart failure, pulmonary hypertension, right ventricular dysfunction, and arrhythmia. Long-term follow-up shows increased incidence of arrhythmia, heart failure, acute coronary syndrome, right ventricular dysfunction, myocardial fibrosis, hypertension, and diabetes mellitus. There is increased mortality in COVID-19 patients after hospital discharge, and initial myocardial injury is associated with increased mortality.

Summary

Emerging data demonstrates increased incidence of cardiovascular illness and structural changes in recovered COVID-19 patients. Future research will be important in understanding the clinical significance of these structural abnormalities, and to determine the effect of vaccines on preventing long-term cardiovascular complications.

Comparing cardiovascular magnetic resonance strain software packages by their abilities to discriminate outcomes in patients with heart failure with preserved ejection fraction

BACKGROUND

Cardiovascular magnetic resonance (CMR) myocardial strain analysis using feature tracking (FT) is an increasingly popular method to assess cardiac function. However, different software packages produce different strain values from the same images and there is little guidance regarding which software package would be the best to use. We explored a framework under which different software packages could be compared and used based on their abilities to differentiate disease from health and differentiate disease severity based on outcome.

METHOD

To illustrate this concept, we compared 4-chamber left ventricular (LV) peak longitudinal strain (GLS) analyzed from retrospective electrocardiogram gated cine imaging performed on 1.5 T CMR scanners using three CMR post-processing software packages in their abilities to discriminate a group of 45 patients with heart failure with preserved ejection fraction (HFpEF) from 26 controls without cardiovascular disease and to discriminate disease severity based on outcomes. The three different post-processing software used were SuiteHeart, cvi42, and DRA-Trufistrain.

RESULTS

All three software packages were able to distinguish HFpEF patients from controls. 4-chamber peak GLS by SuiteHeart was shown to be a better discriminator of adverse outcomes in HFpEF patients than 4-chamber GLS derived from cvi42 or DRA-Trufistrain.

CONCLUSION

We illustrated a framework to compare feature tracking GLS derived from different post-processing software packages. Publicly available imaging data sets with outcomes would be important to validate the growing number of CMR-FT software packages.

Heart Failure With Mid-range or Recovered Ejection Fraction: Differential Determinants of Transition

The recent definition of an intermediate clinical phenotype of heart failure (HF) based on an ejection fraction (EF) of between 40% and 49%, namely HF with mid-range EF (HFmrEF), has fuelled investigations into the clinical profile and prognosis of this patient group. HFmrEF shares common clinical features with other HF phenotypes, such as a high prevalence of ischaemic aetiology, as in HF with reduced EF (HFrEF), or hypertension and diabetes, as in HF with preserved EF (HFpEF), and benefits from the cornerstone drugs indicated for HFrEF. Among the HF phenotypes, HFmrEF is characterised by the highest rate of transition to either recovery or worsening of the severe systolic dysfunction profile that is the target of disease-modifying therapies, with opposite prognostic implications. This article focuses on the epidemiology, clinical characteristics and therapeutic approaches for HFmrEF, and discusses the major determinants of transition to HFpEF or HFrEF.

Left Ventricular Contraction Duration Is the Most Powerful Predictor of Cardiac Events in LQTS: A Systematic Review and Meta-Analysis

Background: Long-QT syndrome (LQTS) is primarily an electrical disorder characterized by a prolonged myocardial action potential. The delay in cardiac repolarization leads to electromechanical (EM) abnormalities, which adds a diagnostic value for LQTS. Prolonged left ventricular (LV) contraction was identified as a potential risk for arrhythmia. The aim of this meta-analysis was to assess the best predictor of all EM parameters for cardiac events (CEs) in LQTS patients. Methods: We systematically searched all electronic databases up to March 2020, to select studies that assessed the relationship between echocardiographic indices—contraction duration (CD), mechanical dispersion (MD), QRS onset to peak systolic strain (QAoC), and the EM window (EMW); and electrical indices— corrected QT interval (QT_C), QT_C dispersion, RR interval in relation to CEs in LQTS. This meta-analysis included a total of 1041 patients and 373 controls recruited from 12 studies. Results: The meta-analysis showed that LQTS patients had electrical and mechanical abnormalities as compared to controls—QT_C, WMD 72.8; QT_C dispersion, WMD 31.7; RR interval, WMD 91.5; CD, WMD 49.2; MD, WMD 15.9; QAoC, WMD 27.8; and EMW, WMD −62.4. These mechanical abnormalities were more profound in symptomatic compared to asymptomatic patients in whom disturbances were already manifest, compared to controls. A CD ≥430 ms had a summary sensitivity (SS) of 71%, specificity of 84%, and diagnostic odds ratio (DOR) >19.5 in predicting CEs. EMW and QT_C had a lower accuracy. Conclusions: LQTS is associated with pronounced EM abnormalities, particularly prolonged LV myocardial CD, which is profound in symptomatic patients. These findings highlight the significant role of EM indices like CD in managing LQTS patients.