Anavekar, Nandan S.

Abstract Background Patients with heart failure possess an increased risk for adverse outcomes with noncardiac surgery (1). While bariatric surgery is frequently performed in patients with obesity, there remains a limited understanding of the impact of bariatric surgery in obese patients with heart failure. Purpose The purpose of this study was to compare outcomes of bariatric surgery versus nonsurgical management in obese patients with heart failure. Methods We searched PubMed, EMBASE, and the Cochrane Library, through February 2024, for studies evaluating outcomes in obese patients with heart failure who underwent bariatric surgery compared to nonsurgical management. Outcomes assessed were postoperative atrial fibrillation, all-cause mortality, and hospital readmission. We used a fixed-effect model to calculate hazard ratios (HR) with 95% confidence intervals (CI) in R studio for outcomes assessed. In outcomes where significant heterogeneity was found (P< 0.05 and I2 > 60%), a random effects model was used. Results A total of 3 studies were identified, consisting of 260,186 patients. Compared to nonsurgical management, bariatric surgery was associated with a significant reduction in postoperative atrial fibrillation (HR 0.72; 95% CI: 0.62-0.84), all-cause mortality (HR 0.50; 95%CI 0.35-0.72), and hospital readmission (HR 0.73; 95% CI 0.69-0.78) in obese patients with heart failure. Conclusion Our study suggests that bariatric surgery significantly reduces post-operative atrial fibrillation, mortality, and hospital readmission among obese patients with heart failure.Our findings demonstrate that bariatric surgery should be considered as a viable intervention in obese patients with heart failure. Further studies are warranted to confirm our findings.Forest Plots of Outcomes Assessed

Aim: The association of echocardiographic findings and subsequent risk of left-sided native valve endocarditis (LS-NVE) is undefined. The aim of this study was to determine if transthoracic echocardiography (TTE) measurements are associated with the subsequent development of LS-NVE in patients without cardiac predisposing conditions. Methods: Institutional databases were evaluated for adults diagnosed with LS-NVE from 2008 to 2020. Patients with prosthetic valves, cardiovascular implantable electronic devices, intracardiac devices, injection drug use, and predisposing cardiac conditions were excluded. Only patients who had a TTE performed 6 months to 3 years before the development of LS-NVE were included as cases. Controls were patients within the same Mayo location with a TTE report and were matched in a 1:3 ratio according to age, gender, Charlson comorbidity index, and echocardiography date. Results: There were 148 cases and 431 matched controls. As compared to controls, infective endocarditis (IE) cases had a higher prevalence of diabetes mellitus (46.6% vs. 30.4%) and chronic kidney disease (46.6% vs. 28.1%) (P < 0.001). Left ventricular outflow tract velocity (P = 0.017), left ventricular ejection fraction (P = 0.018), and E:e’ ratio (P = 0.050) were associated with LS-NVE. Conclusions: Echocardiographic measurements were associated with subsequent LS-NVE development in this pilot study. A larger cohort of LS-NVE patients, however, is needed to validate these findings.

Coronary CT angiography (CCTA) is now endorsed by all major cardiology guidelines for the investigation of chest pain and assessment for coronary artery disease (CAD) in appropriately selected patients. CAD is a leading cause of morbidity and mortality. There is extensive literature to support CCTA diagnostic and prognostic value both for stable and acute symptoms. It enables rapid and cost-effective rule-out of CAD, and permits quantification and characterization of coronary plaque and associated significance. In this comprehensive review, we detail the road traveled as CCTA evolved to include quantitative assessment of plaque stenosis and extent, characterization of plaque characteristics including high-risk features, functional assessment including fractional flow reserve-CT (FFR-CT), and CT perfusion techniques. The state of current guideline recommendations and clinical applications are reviewed, as well as future directions in the rapidly advancing field of CT technology, including photon counting and applications of artificial intelligence (AI).

Background: Outcomes of device-detected AF remain unclear in individuals without a prior history of AF. Methods: A meta-analysis was conducted to evaluate outcomes in individuals with no prior history of AF who experienced device-detected AF. Outcomes assessed were clinical AF, thromboembolism and all-cause mortality. A fixed-effects model was used to calculate RRs with 95% CI. Results: Compared to individuals who did not experience device-detected AF, those who did had increased risks of clinical AF (RR 3.33, 95% CI [1.99–5.57]; p<0.0001) and thromboembolic events (RR 2.21; 95% CI [1.72–2.85]; p<0.0001). The risk of all-cause mortality was similar between both groups (RR 1.19; 95% CI [0.95–1.49]; p=0.13). Subgroup analysis revealed an increased risk of thromboembolic events among device-detected AF ≥24 hours (RR 12.34; 95% CI [2.70–56.36]). Conclusion: While there is an increased risk of clinical AF and thromboembolism in individuals with device-detected AF, mortality was insignificant.

Background: The impact of computer ECG interpretation (CEI) on medical professionals’ performance is understudied. This study aims to assess the interpretation proficiency of diverse medical professionals with and without access to CEI reports. Methods: Medical professionals from diverse backgrounds interpreted 60 12-lead ECGs with urgent and non-urgent findings. The interpretation process involved two interpretation phases: (i) 30 ECGs with clinical statements and (ii) the same 30 ECGs and clinical statements in random order along with a CEI report. Diagnostic performance was evaluated based on interpretation accuracy, time per ECG, and self-reported confidence (rated 0 [not confident], 1 [somewhat confident], or 2 [confident]). Results: Among 892 participants, there were 44 (4.9%) primary care physicians, 123 (13.8%) cardiology fellows-in-training, 259 (29.0%) resident physicians, 137 (15.4%) medical students, 56 (6.3%) advanced practice providers, 82 (9.2%) nurses, and 191 (21.4%) allied health professionals. The inclusion of the CEI significantly improved interpretation accuracy by 15.1% (95% CI, 14.3 to 16.0; P<0.001), reduced interpretation time by 52 seconds (95% CI, -56 to -48; P<0.001), and increased confidence by 0.06 (95% CI, 0.03 to 0.09; P=0.003) (Table 1) . Conclusions: CEI integration improves ECG interpretation accuracy, efficiency, and confidence across medical professionals. Nevertheless, even with CEI, significant gaps in ECG interpretation proficiency remain.

Background: Accurate ECG interpretation is vital, but variations in skills exist among healthcare professionals. This study aims to identify factors contributing to ECG interpretation proficiency. Methods: Survey data and ECG test scores from participants in the EDUCATE Trial were analyzed. The dependent variable was the test score for interpreting 30 12-lead ECGs. Independent variables included non-modifiable factors (physician status, clinical experience, patient care impact) and modifiable factors (weekly interpretations, training hours, expert supervision frequency). Bivariate and multivariate analyses generated the Comprehensive Model (all factors) and Actionable Model (modifiable factors only). Results: Among 1206 participants, there were 72 (6.0%) primary care physicians, 146 (12.1%) cardiology fellows-in-training, 353 (29.3%) resident physicians, 182 (15.1%) medical students, 84 (7.0%) advanced practice providers, 120 (9.9%) nurses, and 249 (20.7%) allied health professionals. Physicians accounted for 571 (47.3%) of participants, while 453 (37.6%) were non-physicians. Bivariate analysis showed associations between test scores and multiple variables (Table 1) . In the Comprehensive Model, scores were independently associated with weekly interpretations (9.9 score increase; 95% CI 7.9-11.8; P<0.001), physician status (9.0 score increase; 95% CI 7.2-10.8; P<0.001), and training hours (5.7 score increase; 95% CI 3.7-7.6; P<0.001). In the Actionable Model, scores were independently associated with weekly interpretations (12.0 score increase; 95% CI, 10.0-14.0; P<0.001) and training hours (4.7 score increase; 95% CI 2.6-6.7; P<0.001). The Comprehensive and Actionable Models accounted for 18.7% and 12.3% of the variance in test scores, respectively. Conclusions: Being a physician is a non-modifiable predictor, while training and regular practice are modifiable predictors of ECG interpretation performance.

Background: Gaps in ECG interpretation competency among medical professionals exist, with a need for practical, evidence-based, and accessible learning solutions. We conducted an international, prospective, randomized controlled trial to assess the effectiveness of web-based, self-directed ECG learning. Methods: A total of 1206 diverse medical learners and professionals underwent an initial test, followed by random assignment to one of four groups: (i) online question-bank (questions), (ii) online lectures (lectures), (iii) online, question-bank and lectures (hybrid), or (iv) no resources (control). After 4 months, a post-test was administered to evaluate the overall change in performance. Results: Of all participants, 863 (72%) completed the trial. After the 4-month follow-up, all three online, self-directed intervention groups (questions, lectures, and hybrid) showed significant improvement in overall performance (P<0.001), while the control group did not (P=0.544). The questions, lectures, and hybrid interventions demonstrated score improvements of +11.4% (95% CI, 9.1-13.7; P<0.001), +9.8% (95% CI, 7.8-11.9; P<0.001), and +11.0% (95% CI, 9.2-12.9; P<0.001) respectively, compared to +0.8% (95% CI, -1.2-2.8; P=0.544) for the control group. These improvements were consistent across medical professional groups (Figure 1) . Conclusions: Web-based, self-directed learning resources effectively improved ECG interpretation proficiency for diverse medical learners and professionals.

Background: ECG interpretation is crucial in medical practice, but professionals struggle with achieving and maintaining competency. Identifying proficiency gaps aids in designing educational interventions. Methods: Medical professionals from various disciplines interpreted 30 12-lead ECGs containing commonly taught urgent and non-urgent findings. Performance metrics evaluated were overall adjusted score (% of correctly identified findings using a point-value score based on clinical relevance), unadjusted score (% of correctly identified findings), interpretation time per ECG, and self-reported confidence (rated on an ordinal scale of 0 [not confident], 1 [somewhat confident], or 2 [confident]). Results: Among 1206 participants, there were 72 (6%) primary care physicians (PCPs), 146 (12%) cardiology fellows-in-training (FIT), 353 (29%) resident physicians, 182 (15%) medical students, 84 (7%) advanced practice providers (APPs), 120 (10%) nurses, 249 (21%) allied health professionals, 571 (47%) physicians, and 453 (38%) non-physicians. Participants had a mean adjusted score of 46.9% (± 15.9%), unadjusted score of 56.4% (± 17.2%), interpretation time of 142 seconds (± 67 seconds), and confidence of 0.83 (± 0.53) (Table 1) . Performance varied across groups; cardiology FIT had superior performance in all metrics. Physicians generally outperformed non-physicians, with higher overall adjusted score (52% vs. 43%; p<0.01), unadjusted score (62% vs. 52%; p<0.01), and confidence (0.91 vs. 0.80; p<0.01). Unadjusted score for PCPs was higher than nurses and APPs (58% vs. 47% and 51%; p<0.01) but lower than resident physicians (58% vs. 60%; p<0.01). Allied health professionals outperformed nurses and APPs and closely matched resident physicians and PCPs. Conclusions: Significant gaps in ECG interpretation proficiency exist, emphasizing the need for comprehensive, scalable, and accessible educational tools.