Electrocardiography-Based Artificial Intelligence Algorithm Aids in Prediction of Long-term Mortality After Cardiac Surgery.

OBJECTIVE: To assess whether an electrocardiography-based artificial intelligence (AI) algorithm developed to detect severe ventricular dysfunction (left ventricular ejection fraction [LVEF] of 35% or below) independently predicts long-term mortality after cardiac surgery among patients without severe ventricular dysfunction (LVEF>35%). METHODS: Patients who underwent valve or coronary bypass surgery at Mayo Clinic (1993-2019) and had documented LVEF above 35% on baseline electrocardiography were included. We compared patients with an abnormal vs a normal AI-enhanced electrocardiogram (AI-ECG) screen for LVEF of 35% or below on preoperative electrocardiography. The primary end point was all-cause mortality. RESULTS: A total of 20,627 patients were included, of whom 17,125 (83.0%) had a normal AI-ECG screen and 3502 (17.0%) had an abnormal AI-ECG screen. Patients with an abnormal AI-ECG screen were older and had more comorbidities. Probability of survival at 5 and 10 years was 86.2% and 68.2% in patients with a normal AI-ECG screen vs 71.4% and 45.1% in those with an abnormal screen (log-rank, P<.01). In the multivariate Cox survival analysis, the abnormal AI-ECG screen was independently associated with a higher all-cause mortality overall (hazard ratio [HR], 1.31; 95% CI, 1.24 to 1.37) and in subgroups of isolated valve surgery (HR, 1.30; 95% CI, 1.18 to 1.42), isolated coronary artery bypass grafting (HR, 1.29; 95% CI, 1.20 to 1.39), and combined coronary artery bypass grafting and valve surgery (HR, 1.19; 95% CI, 1.08 to 1.32). In a subgroup analysis, the association between abnormal AI-ECG screen and mortality was consistent in patients with LVEF of 35% to 55% and among those with LVEF above 55%. CONCLUSION: A novel electrocardiography-based AI algorithm that predicts severe ventricular dysfunction can predict long-term mortality among patients with LVEF above 35% undergoing valve and/or coronary bypass surgery.

Endosonographic examination of thyroid gland among patients with nonthyroid cancers.

OBJECTIVES: There is limited endosonographic literature regarding thyroid gland pathology, which is frequently visualized during upper endoscopic ultrasound (EUS). Our objective was to assess the prevalence of benign and malignant thyroid lesions encountered during routine upper EUS within a cancer center setting. MATERIALS AND METHODS: The data were prospectively collected and retrospectively analyzed. All upper EUS procedures performed between October 2012 and July 2014 were reviewed at a large referral cancer center. Data collected included patient demographics, preexisting thyroid conditions, thyroid gland dimensions, the presence or absence of thyroid lesions, and EUS morphology of lesions if present, and interventions performed to characterize thyroid lesions and pathology results when applicable. RESULTS: Two hundred and forty-five EUS procedures were reviewed. Of these, 100 cases reported a detailed endosonographic examination of the thyroid gland. Most of the thyroid glands were endosonographically visualized when the tip of the scope was at 18 cm from the incisors. Twelve cases showed thyroid lesions, out of which three previously undiagnosed thyroid cancers were visualized during EUS (two primary papillary thyroid cancers and one anaplastic thyroid cancer). Transesophageal EUS-guided fine needle aspiration of thyroid lesions was feasible when the lesion was in the inferior portion of the thyroid gland, and the tip of the scope was at 18 cm or more from the incisors. CONCLUSIONS: Routine EUS examination may detect unexpected thyroid lesions including malignant ones. We encourage endosonographers to screen the visualized portions of the thyroid gland during routine withdrawal of the echoendoscope.

Primary papillary thyroid carcinoma diagnosed by using endoscopic ultrasound with fine needle aspiration.

There is paucity in the literature on the use of endoscopic ultrasound (EUS) for evaluating the thyroid gland. We report the first case of primary papillary thyroid cancer diagnosed by using EUS and fine needle aspiration (FNA). A 66-year-old man underwent EUS for the evaluation of mediastinal lymphadenopathy. FNA of the lymph nodes showed benign findings. A hypoechoic mass was noted in the right lobe of the thyroid gland. Therefore, FNA was performed. The cytological results were consistent with primary papillary thyroid cancer.