Normal Ranges of Global Left Ventricular Myocardial Work Indices in Adults: A Meta-Analysis.

BACKGROUND: Recent studies have demonstrated that left ventricular myocardial work (MW) is incremental in diagnosis and prognostication compared with left ventricular ejection fraction and myocardial strain. The authors performed a meta-analysis of normal ranges of noninvasive MW indices including global work index, global constructive work, global wasted work, and global work efficiency and determined confounders that may contribute to variance in reported values. METHODS: Four databases (PubMed, Scopus, Embase, and the Cochrane Library) were searched through January 2021 using the key terms "myocardial work," "global constructive work," "global wasted work," "global work index," and "global work efficiency." Studies were included if the articles reported LV MW using two-dimensional transthoracic echocardiography in healthy normal subjects, either in a control group or comprising the entire study cohort. The weighted mean was estimated by using the random-effect model with a 95% CI. Heterogeneity across included studies was assessed using the I2 test. Funnel plots and the Egger regression test were used to assess potential publication bias. RESULTS: The search yielded 476 articles. After abstract and full-text screening, we included 13 data sets with 1,665 patients for the meta-analysis. The reported normal mean values of global work index and global constructive work among the studies were 2,010 mm Hg% (95% CI, 1,907-2,113 mm Hg%) and 2,278 mm Hg% (95% CI, 2,186-2,369 mm Hg%), respectively. Mean global wasted work was 80 mm Hg% (95% CI, 73-87 mm Hg%), and mean global work efficiency was 96.0% (95% CI, 96%-96%). Furthermore, gender significantly contributed to variations in normal values of global work index, global wasted work, and global work efficiency. No evidence of significant publication bias was observed. CONCLUSIONS: In this meta-analysis, the authors provide echocardiographic reference ranges for noninvasive indices of MW. These normal values could serve as a reference for clinical and research use.

Application of machine learning in screening for congenital heart diseases using fetal echocardiography.

There is a growing body of literature supporting the utilization of machine learning (ML) to improve diagnosis and prognosis tools of cardiovascular disease. The current study was to investigate the impact that the ML framework may have on the sensitivity of predicting the presence or absence of congenital heart disease (CHD) using fetal echocardiography. A comprehensive fetal echocardiogram including 2D cardiac chamber quantification, valvar assessments, assessment of great vessel morphology, and Doppler-derived blood flow interrogation was recorded. The postnatal echocardiogram was used to ascertain the diagnosis of CHD. A random forest (RF) algorithm with a nested tenfold cross-validation was used to train models for assessing the presence of CHD. The study population was derived from a database of 3910 singleton fetuses with maternal age of 28.8 ± 5.2 years and gestational age at the time of fetal echocardiography of 22.0 weeks (IQR 21-24). The proportion of CHD was 14.1% for the studied cohort confirmed by post-natal echocardiograms. Our proposed RF-based framework provided a sensitivity of 0.85, a specificity of 0.88, a positive predictive value of 0.55 and a negative predictive value of 0.97 to detect the CHD with the mean of mean ROC curves of 0.94 and the mean of mean PR curves of 0.84. Additionally, six first features, including cardiac axis, peak velocity of blood flow across the pulmonic valve, cardiothoracic ratio, pulmonary valvar annulus diameter, right ventricular end-diastolic diameter, and aortic valvar annulus diameter, are essential features that play crucial roles in adding more predictive values to the model in detecting patients with CHD. ML using RF can provide increased sensitivity in prenatal CHD screening with very good performance. The incorporation of ML algorithms into fetal echocardiography may further standardize the assessment for CHD.

The clinical characteristics of coronary artery fistula anomalies in children and adults: A 24-year experience.

OBJECTIVES: The aim of our work is to investigate the clinical characteristics of coronary artery fistula (CAF) anomalies in South Vietnam. METHODS: This is a retrospective analysis of 119 patients with diagnosis of definite CAF between January 1992 and April 2016. The demographic, clinical, echocardiographic, and angiographic characteristics and management of CAF with short-term outcomes are described. RESULTS: The median age was 15 years (range, 1-79 years), with 49 male (41%) and 70 female (59%). There were 77 symptomatic patients (64.7%) and 91 patients (76.5%) who presented with a murmur. The electrocardiogram was abnormal in 45.4% and cardiac enlargement or increased pulmonary vasculature were seen in 76 patients (63.9%) on chest X-ray. The sensitivity of echocardiography for CAF diagnosis was 79%. The source of the fistula was most often from the RCA (54%), most commonly to right atrium (34.5%) or right ventricle (31.1%). In comparison with surgery, transcatheter closure had a shorter hospital length of stay (5.4 ± 3.8 days vs 12.6 ± 6.5 days, P = .02) and better postprocedural left ventricular ejection fraction (67.9 ± 8.1% vs 62.9 ± 6.0%, P = .03). CONCLUSION: The majority of fistula in this study originated from the RCA and terminated in the right atrium or the right ventricle. Transcatheter and surgical closure are both relatively safe and effective, with the potential for shortened length of hospital stay following transcatheter closure.