Background Despite the high prevalence and significant mortality associated with aortic stenosis (AS), data demonstrate low rates of referral to specialized heart valve teams. The objectives of this study were therefore to highlight contemporary referral patterns in patients with significant AS and identify potential barriers to referral. Methods Patients undergoing transthoracic echocardiography (TTE) in a large public health catchment had automatically generated text inserted into their TTE report and electronic medical record if the TTE met the American Society of Echocardiography criteria for moderate or severe AS. Text recommended referral to a heart valve team for further assessment or treatment. Patients were prospectively identified and followed. Structured telehealth was performed to clarify symptom status and perceived barriers to referral. Results Over 6 months, 343 patients with severe (n = 142) or moderate (n = 201) AS were identified. Despite significant AS alongside a referral prompt, only 86 (61%) patients with severe and 44 (22%) with moderate AS were referred for assessment. Patient and echocardiographic characteristics were similar between referred and nonreferred. Mortality was significantly higher in nonreferred patients with severe AS (19.6 vs. 2.3% referred, p < 0.001). Of the nonreferred patients who died, 5/11 (45%) had no compelling reason for lack of referral. Most nonreferred patients with severe AS reported progressive symptoms (75% New York Heart Association class II/III). Over half (51.2%) reported being managed with a “watchful waiting” strategy despite meeting a class I indication for aortic valve replacement, and nearly one-third (27.5%) were unaware of their diagnosis. Conclusions Despite automatically generated referral prompts in patients with severe AS, many patients without a compelling reason for lack of referral were not appropriately assessed and died.

Background: Despite its high prevalence, little is known about the effect of sex on the management and outcomes of aortic stenosis (AS). We sought to characterize the effect of sex on the clinical evaluation for and provision of aortic valve replacement (AVR), including surgical (SAVR) and transcatheter aortic valve replacement (TAVR), and the subsequent morbidity and mortality outcomes. Methods: A comprehensive chart review was conducted on all patients with a first diagnosis of severe aortic stenosis (AS) at Vancouver General and University of British Columbia hospitals from 2012 to 2022. Exact chi-square and Kruskal–Wallis tests were used to evaluate the variables of interest. Results: A total of 1794 studies met the inclusion criteria, comprising 782 females (44%) and 1012 males (56%). Females were significantly older than males at the time of the first diagnosis (79 versus 75 years, p < 0.001). Females were significantly less likely to be evaluated by the TAVR clinic or cardiac surgeon or to receive aortic valve intervention (p-value ≤ 0.001). Females were significantly more likely to be rejected for TAVR due to older age (OR 0.23 (0.07, 0.59)), comorbid conditions (OR 0.68 (0.47, 0.97)), and frailty (OR 0.23 (0.07, 0.59)). Females were significantly more likely to be rejected for SAVR on the basis of frailty (OR 0.66 (0.46, 0.94)). Females also had significantly higher rates of 1-year mortality, hospitalization, and heart failure hospitalization compared to males (p-values < 0.05). Conclusions: Our data suggest significant sex-based discrepancies in the management of AS. Females with severe AS are diagnosed later in life and are less likely to be evaluated for valve intervention. They are less likely to receive intervention due to older age, frailty, and multimorbid conditions. Further research is warranted for a more effective identification and follow up of aortic stenosis, as well as timely referral for AVR, where appropriate, especially for females.

We developed a machine learning model for efficient analysis of echocardiographic image quality in hospitalized patients. This study applied a machine learning model for automated transthoracic echo (TTE) image quality scoring in three inpatient groups. Our objectives were: (1) Assess the feasibility of a machine learning model for echo image quality analysis, (2) Establish the comprehensiveness of real-world TTE reporting by clinical group, and (3) Determine the relationship between machine learning image quality and comprehensiveness of TTE reporting. A machine learning model was developed and applied to TTEs from three matched cohorts for image quality of nine standard views. Case TTEs were comprehensive studies in mechanically ventilated patients between 01/01/2010 and 12/31/2015. For each case TTE, there were two matched spontaneously breathing controls (Control 1: Inpatients scanned in the lab and Control 2: Portable studies). We report the overall mean maximum and view specific quality scores for each TTE. The comprehensiveness of an echo report was calculated as the documented proportion of 12 standard parameters. An inverse probability weighted regression model was fit to determine the relationship between machine learning quality score and the completeness of a TTE report. 175 mechanically ventilated TTEs were included with 350 non-intubated samples (175 Control 1: Lab and 175 Control 2: Portable). In total, the machine learning model analyzed 14,086 echo video clips for quality. The overall accuracy of the model with regard to the expert ground truth for the view classification was 87.0%. The overall mean maximum quality score was lower for mechanically ventilated TTEs (0.55 [95% CI 0.54, 0.56]) versus 0.61 (95% CI 0.59, 0.62) for Control 1: Lab and 0.64 (95% CI 0.63, 0.66) for Control 2: Portable; p = 0.002. Furthermore, mechanically ventilated TTE reports were the least comprehensive, with fewer reported parameters. The regression model demonstrated the correlation of echo image quality and completeness of TTE reporting regardless of the clinical group. Mechanically ventilated TTEs were of inferior quality and clinical utility compared to spontaneously breathing controls and machine learning derived image quality correlates with completeness of TTE reporting regardless of the clinical group.

In the midst of the COVID-19 pandemic, unprecedented pressure has been added to healthcare systems around the globe. Imaging is a crucial component in the management of COVID-19 patients. Point-of-care ultrasound (POCUS) such as hand-carried ultrasound emerges in the COVID-19 era as a tool that can simplify the imaging process of COVID-19 patients, and potentially reduce the strain on healthcare providers and healthcare resources. The preliminary evidence available suggests an increasing role of POCUS in diagnosing, monitoring, and risk-stratifying COVID-19 patients. This scoping review aims to delineate the challenges in imaging COVID-19 patients, discuss the cardiopulmonary complications of COVID-19 and their respective sonographic findings, and summarize the current data and recommendations available. There is currently a critical gap in knowledge in the role of POCUS in the COVID-19 era. Nonetheless, it is crucial to summarize the current preliminary data available in order to help fill this gap in knowledge for future studies.

Patients admitted to the coronary care units (CCU's) often develop anaemia and receive blood transfusion (BT) therapy. However, no randomised controlled trials have been conducted to guide BT strategies in cardiac patients, and the haemoglobin threshold at which BT becomes necessary is unknown. We sought to prospectively examine the current practice of BT in 2 tertiary CCU's without a specific BT policy. From July 2009 to September 2011, physicians were asked to document the baseline characteristics of their patients, primary reason for BT, and probable site(s) of bleeding when BT was ordered. Information regarding duration of hospitalisation and in-hospital mortality was tracked. Our prospective cohort consisted of 60 patients (mean age 71.1±12.1 years, 37 male). The primary diagnoses for CCU admission were acute coronary syndrome in 38 (63.3%) patients, arrhythmia in 5 (8.3%) patients, and decompensated heart failure in 5 (8.3%) patients. The average systolic blood pressure was 105.6 ± 23.2 mmHg at the time of BT. Vasopressor and/or inotropic agents were being administered in 14 (23.3%) patients, and left ventricular assist devices were present in 7 (11.7%) patients at the time of BT. Cardiac catheterization (n=34, 56.7%) and coronary intervention (n=19, 31.7%) were common before BT. The use of ASA, clopidogrel and heparin within 24 hours prior to BT was 88.3%, 60.0% and 71.7% respectively. The most common site of blood loss was the gastrointestinal system (n=22, 36.7%), but the site of blood loss was unknown in up to 18.3% of patients. “Low haemoglobin” (38.3%) and “ongoing blood loss” (36.7%) were the leading reasons for BT, while only 11.7% of patients received BT for haemodynamic instability. The mean haemoglobin level at the time of BT was 79.4±10.9 g/L, while it was 78.1±8.4 g/L for patients with “low haemoglobin” as the indication for BT. The median length of hospitalization was 13 days, and in-hospital mortality was 15.0% amongst patients who received a BT. Patients receiving a BT in CCU often required left ventricular supportive therapy. “Low haemoglobin level”, not “haemodynamic instability”, was the most common reason for BT in CCU. The most common site of blood loss was the gastrointestinal system, but the site of blood loss was unknown in many patients. Patients who received BT had a high rate of mortality. The current study highlights the heterogeneous practice of BT and the need to establish evidence-based practice guidelines for BT in patients with cardiac diseases.