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Introduction This narrative review focusing on critical care echocardiography (CCE) has been written by a group of experts in the field, with the aim of outlining the state of the art in CCE in the 10 years after its official recognition and definition. Results In the last 10 years, CCE has become an essential branch of critical care ultrasonography and has gained general acceptance. Its use, both as a diagnostic tool and for hemodynamic monitoring, has increased markedly, influencing contemporary cardiorespiratory management. Recent studies suggest that the use of CCE may have a positive impact on outcomes. CCE may be used in critically ill patients in many different clinical situations, both in their early evaluation of in the emergency department and during intensive care unit (ICU) admission and stay. CCE has also proven its utility in perioperative settings, as well as in the management of mechanical circulatory support. CCE may be performed with very simple diagnostic objectives. This application, referred to as basic CCE, does not require a high level of training. Advanced CCE, on the other hand, uses ultrasonography for full evaluation of cardiac function and hemodynamics, and requires extensive training, with formal certification now available. Indeed, recent years have seen the creation of worldwide certification in advanced CCE. While transthoracic CCE remains the most commonly used method, the transesophageal route has gained importance, particularly for intubated and ventilated patients. Conclusion CCE is now widely accepted by the critical care community as a valuable tool in the ICU and emergency department, and in perioperative settings.

Artificial intelligence (AI) has been developed for echocardiography 1 – 3 , although it has not yet been tested with blinding and randomization. Here we designed a blinded, randomized non-inferiority clinical trial (ClinicalTrials.gov ID: NCT05140642; no outside funding) of AI versus sonographer initial assessment of left ventricular ejection fraction (LVEF) to evaluate the impact of AI in the interpretation workflow. The primary end point was the change in the LVEF between initial AI or sonographer assessment and final cardiologist assessment, evaluated by the proportion of studies with substantial change (more than 5% change). From 3,769 echocardiographic studies screened, 274 studies were excluded owing to poor image quality. The proportion of studies substantially changed was 16.8% in the AI group and 27.2% in the sonographer group (difference of −10.4%, 95% confidence interval: −13.2% to −7.7%, P  < 0.001 for non-inferiority, P  < 0.001 for superiority). The mean absolute difference between final cardiologist assessment and independent previous cardiologist assessment was 6.29% in the AI group and 7.23% in the sonographer group (difference of −0.96%, 95% confidence interval: −1.34% to −0.54%, P  < 0.001 for superiority). The AI-guided workflow saved time for both sonographers and cardiologists, and cardiologists were not able to distinguish between the initial assessments by AI versus the sonographer (blinding index of 0.088). For patients undergoing echocardiographic quantification of cardiac function, initial assessment of LVEF by AI was non-inferior to assessment by sonographers. The impact of artificial intelligence in cardiac function assessment is evaluated by a blinded, randomized non-inferiority trial of artificial intelligence versus sonographer initial assessment of the left ventricular ejection fraction.

Multilevel obstruction of left-sided heart structures was originally characterized by Shone et al. The formulation of an appropriate operative strategy remains challenging and needs to be individualized for this complex subset of patients. Intraoperative transesophageal echocardiography (TEE) not only helps in delineating spatial anatomy but also reveals associated anomalies that help in decision-making regarding operative strategies for these patients. Here, we discuss five such cases of Shones anomaly presenting at varied age group with different associated anomaly in which intraoperative TEE played a pivotal role in the management.

Abstract Rationale Assessment of fluid responsiveness relies on dynamic echocardiographic parameters that have not yet been compared in large cohorts. Objectives To determine the diagnostic accuracy of dynamic parameters used to predict fluid responsiveness in ventilated patients with a circulatory failure of any cause. Methods In this multicenter prospective study, respiratory variations of superior vena cava diameter (∆SVC) measured using transesophageal echocardiography, of inferior vena cava diameter (∆IVC) measured using transthoracic echocardiography, of the maximal Doppler velocity in left ventricular outflow tract (∆VmaxAo) measured using either approach, and pulse pressure variations (∆PP) were recorded with the patient in the semirecumbent position. In each patient, a passive leg raise was performed and an increase of aortic velocity time integral greater than or equal to 10% defined fluid responsiveness. Measurements and Main Results Among 540 patients (379 men; age, 65 ± 13 yr; Simplified Acute Physiological Score II, 59 ± 18; Sequential Organ Failure Assessment, 10 ± 3), 229 exhibited fluid responsiveness (42%). ∆PP, ∆VmaxAo, ∆SVC, and ∆IVC could be measured in 78.5%, 78.0%, 99.6%, and 78.1% of cases, respectively. ∆SVC greater than or equal to 21%, ∆VmaxAo greater than or equal to 10%, and ∆IVC greater than or equal to 8% had a sensitivity of 61% (95% confidence interval, 57–66%), 79% (75–83%), and 55% (50–59%), respectively, and a specificity of 84% (81–87%), 64% (59–69%), and 70% (66–75%), respectively. The area under the receiver operating characteristic curve of ∆SVC was significantly greater than that of ∆IVC (P = 0.02) and ∆PP (P = 0.01). Conclusions ∆VmaxAo had the best sensitivity and ∆SVC the best specificity in predicting fluid responsiveness. ∆SVC had a greater diagnostic accuracy than ∆IVC and ∆PP, but its measurement requires transesophageal echocardiography.

Objectives: Myocardial perfusion scintigraphy (MPS) is a well-established method for diagnosing coronary artery disease and risk stratification of individuals with chest pain. However, while MPS has high sensitivity and specificity for the detection of significant coronary artery disease, it has some drawbacks due to several technical difficulties. We suggest that aortic stiffness indexes measured by echocardiography, which is a well-known marker of atherosclerotic burden, may improve the equivocal test results obtained in MPS. Materials and Methods: We prospectively enrolled 149 consecutive patients between the ages of 18 and 65 years without any previous cardiovascular disease with suspected coronary artery disease, who had undergone both SPECT MPS using Technetium-99m-sestamibi (99mTc MIBI) and transthoracic echocardiography between November 2013 and June 2014. Subjects were divided into three categories according to MPS results as normal, equivocal and ischemic groups. Results: Aortic stiffness index (ASI) and aortic distensibility (AD) of the normal and equivocal groups were similar, and the ischemic group had higher ASI values compared to the normal and equivocal groups. The equivocal group had statistically lower ASI and higher AD values compared to the ischemia group (p <0.001 and <0.001). Optimal threshold cut off point for ASI to differentiate normal MPS result from MPS with ischemia in any LV wall was calculated by ROC analysis. ASI value of 3.05 was found to be cut-off value with 98% sensitivity and 87% specificity to detect ischemia (AUC=0.953 with 95% CI: 0.906 to 0.981 and p <0,001). If ASI value of >3.05 was accepted as abnormal, the frequency of abnormal ASI in the normal, equivocal, and ischemia groups were 11%, 19%, and 98%, respectively. The equivocal group had similar number of patients with abnormal ASI compared to the normal group (p=0.262) while it had statistically a lower number of patients with abnormal ASI than the ischemia group (p<0.001) Conclusion: However, aortic stiffness and aortic AD indexes alone cannot diagnose coronary artery disease (CAD), but may help to discriminate patients with CAD from those without CAD whose MPS results are equivocal.

Success of atrioventricular septal defect repair is defined by post-operative atrioventricular valve function and presence of residual intracardiac shunting. We evaluated differences in interpretation of atrioventricular valve function and residual defects between transesophageal and transthoracic echocardiography in a contemporary cohort of infants undergoing atrioventricular septal defect repair. Among 106 patients, we identified an increase in left and right atrioventricular valve regurgitation, right atrioventricular valve inflow gradient, and increased detection rate of residual intracardiac shunting on transthoracic compared to transesophageal echocardiograms, although residual shunts identified only on transthoracic echocardiogram were not haemodynamically significant. Findings may help inform expectation of post-operative transthoracic echocardiogram findings based on intraoperative assessment.

Objective To assess left atrial (LA) structure and function in marathon runners using two‐dimensional speckle tracking echocardiography (2D‐STE) and real‐time three‐dimensional echocardiography (RT‐3DE). Methods This study enrolled 50 healthy volunteers (control group) and 132 marathon runners, and collected their general information. 2D‐STE and RT‐3DE were performed to obtain LA structural and functional parameters and left ventricular mass index (LVMI). According to the LVMI criteria for diagnosing left ventricular hypertrophy (LVH), all marathon runners were divided into an LVMI normal group and an LVH group. A comparative analysis was performed among the three groups. Multivariate logistic regression was used to analyze the association, and curve fitting was used to show the change trends. Results Compared with the control group, LA total ejection fraction (LATEF) and LA passive ejection fraction (LAPEF) were higher in the LVMI normal group (p < 0.05). Compared with the control group and the LVMI normal group, LA maximal volume index (LAVImax), LA presystolic volume index (LAVIpre), and LA stiffness index (LASI) were higher in the LVH group, whereas LA reservoir strain (LASr), LA conduit strain (LAScd), and LA contraction strain (LASct) were lower (p < 0.05). Multivariate logistic regression analysis showed that LAVImax, LAScd, and LASct were significantly associated with LVH in marathon runners. Curve fitting showed that LAVImax increased with the increase of LVMI, whereas LAScd and LASct decreased. Conclusion 2D‐STE and RT‐3DE can effectively assess LA structure and function in marathon runners. Marathon runners with normal LVMI exhibit normal LA structure and function, and even some functional enhancement, while those with LVH exhibit increased LA volume and decreased LA strain function. Two‐dimensional speckle tracking echocardiography and real‐time three‐dimensional echocardiography can effectively assess left atrial structure and function in marathon runners.