The prognostic value of artificial intelligence to predict cardiac amyloidosis in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement.

Aims: Cardiac amyloidosis (CA) is common in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Cardiac amyloidosis has poor outcomes, and its assessment in all TAVR patients is costly and challenging. Electrocardiogram (ECG) artificial intelligence (AI) algorithms that screen for CA may be useful to identify at-risk patients. Methods and results: In this retrospective analysis of our institutional National Cardiovascular Disease Registry (NCDR)-TAVR database, patients undergoing TAVR between January 2012 and December 2018 were included. Pre-TAVR CA probability was analysed by an ECG AI predictive model, with >50% risk defined as high probability for CA. Univariable and propensity score covariate adjustment analyses using Cox regression were performed to compare clinical outcomes between patients with high CA probability vs. those with low probability at 1-year follow-up after TAVR. Of 1426 patients who underwent TAVR (mean age 81.0 ± 8.5 years, 57.6% male), 349 (24.4%) had high CA probability on pre-procedure ECG. Only 17 (1.2%) had a clinical diagnosis of CA. After multivariable adjustment, high probability of CA by ECG AI algorithm was significantly associated with increased all-cause mortality [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.01-1.96, P = 0.046] and higher rates of major adverse cardiovascular events (transient ischaemic attack (TIA)/stroke, myocardial infarction, and heart failure hospitalizations] (HR 1.36, 95% CI 1.01-1.82, P = 0.041), driven primarily by heart failure hospitalizations (HR 1.58, 95% CI 1.13-2.20, P = 0.008) at 1-year follow-up. There were no significant differences in TIA/stroke or myocardial infarction. Conclusion: Artificial intelligence applied to pre-TAVR ECGs identifies a subgroup at higher risk of clinical events. These targeted patients may benefit from further diagnostic evaluation for CA.

Opportunistic screening for coronary artery calcium deposition using chest radiographs - a multi-objective models with multi-modal data fusion.

Background: To create an opportunistic screening strategy by multitask deep learning methods to stratify prediction for coronary artery calcium (CAC) and associated cardiovascular risk with frontal chest x-rays (CXR) and minimal data from electronic health records (EHR). Methods: In this retrospective study, 2,121 patients with available computed tomography (CT) scans and corresponding CXR images were collected internally (Mayo Enterprise) with calculated CAC scores binned into 3 categories (0, 1-99, and 100+) as ground truths for model training. Results from the internal training were tested on multiple external datasets (domestic (EUH) and foreign (VGHTPE)) with significant racial and ethnic differences and classification performance was compared. Findings: Classification performance between 0, 1-99, and 100+ CAC scores performed moderately on both the internal test and external datasets, reaching average f1-score of 0.66 for Mayo, 0.62 for EUH and 0.61 for VGHTPE. For the clinically relevant binary task of 0 vs 400+ CAC classification, the performance of our model on the internal test and external datasets reached an average AUCROC of 0.84. Interpretation: The fusion model trained on CXR performed better (0.84 average AUROC on internal and external dataset) than existing state-of-the-art models on predicting CAC scores only on internal (0.73 AUROC), with robust performance on external datasets. Thus, our proposed model may be used as a robust, first-pass opportunistic screening method for cardiovascular risk from regular chest radiographs. For community use, trained model and the inference code can be downloaded with an academic open-source license from https://github.com/jeong-jasonji/MTL_CAC_classification . Funding: The study was partially supported by National Institute of Health 1R01HL155410-01A1 award.

Deglutition Syncope: A Case Report and Review of the Literature.

Deglutition syncope (DS) is a rare, neurally-mediated syncopal syndrome arising from an aberrant vagotonic reflex during swallow-associated esophageal dilation. Its association with gastroesophageal disorders often prompts gastroenterology consultation. An 89-year-old man with recent dysphagia and otalgia was admitted after a syncopal episode occurred while eating. Esophageal imaging and endoscopy demonstrated no causative abnormalities. Maxillofacial imaging revealed chronic sinusitis and mastoiditis. Telemetry monitoring demonstrated high-grade atrioventricular block and pause associated with swallowing. His symptoms and swallow-associated arrhythmia resolved after dual chamber pacemaker implantation. DS is highly treatable once identified and multidisciplinary coordination is helpful in optimizing outcomes and avoiding superfluous testing.

Duodenal Aspirates for Small Intestine Bacterial Overgrowth: Yield, PPIs, and Outcomes after Treatment at a Tertiary Academic Medical Center.

Duodenal aspirates are not commonly collected, but they can be easily used in detection of small intestinal bacterial overgrowth (SIBO). Proton pump inhibitor (PPI) use has been proposed to contribute to the development of SIBO. We aimed to determine the yield of SIBO-positive cultures detected in duodenal aspirates, the relationship between SIBO and PPI use, and the clinical outcomes of patients identified by this method. In a retrospective study, we analyzed electronic medical records from 1263 consecutive patients undergoing upper endoscopy at a tertiary medical center. Aspirates were collected thought out the third and fourth portions of the duodenum, and cultures were considered to be positive for SIBO if they produced more than 100,000 cfu/mL. Culture analysis of duodenal aspirates identified SIBO in one-third of patients. A significantly higher percentage of patients with SIBO use PPIs than patients without SIBO, indicating a possible association. Similar proportions of patients with SIBO improved whether or not they received antibiotic treatment, calling into question the use of this expensive therapy for this disorder.