Citations

INTRODUCTION: It is assumed that screening risk factors for Barrett's esophagus (BE) and prevalent esophageal adenocarcinoma (EAC) are the same. METHODS: A matched case-control study comparing risk factors between EAC and BE was performed. RESULTS: In 1,356 patients (678 with EAC and 678 with BE), heartburn (52.7%), diabetes, hyperlipidemia, hypertension, nonalcoholic steatohepatitis, and metabolic syndrome were less common in EAC (52.7, 29.2, 45.7, 48.2, 12, and 28.5%, resp.) compared with BE (84.5, 37.6, 82.2, 64.6, 18.4, and 44.1%, P < 0.01). Mean alanine aminotransferase and HgA1c levels were also significantly lower in EAC compared with BE. DISCUSSION: Optimal strategies for screening for prevalent EAC may be different than that for BE.

INTRODUCTION: Readmission and death in cirrhosis are common, expensive, and difficult to predict. Our aim was to evaluate the abilities of multiple artificial intelligence (AI) techniques to predict clinical outcomes based on variables collected at admission, during hospitalization, and at discharge. METHODS: We used the multicenter North American Consortium for the Study of End-Stage Liver Disease (NACSELD) cohort of cirrhotic inpatients who are followed up through 90-days postdischarge for readmission and death. We used statistical methods to select variables that are significant for readmission and death and trained 3 AI models, including logistic regression (LR), kernel support vector machine (SVM), and random forest classifiers (RFC), to predict readmission and death. We used the area under the receiver operating characteristic curve (AUC) from 10-fold crossvalidation for evaluation to compare sexes. Data were compared with model for end-stage liver disease (MELD) at discharge. RESULTS: We included 2,170 patients (57 ± 11 years, MELD 18 ± 7, 61% men, 79% White, and 8% Hispanic). The 30-day and 90-day readmission rates were 28% and 47%, respectively, and 13% died at 90 days. Prediction for 30-day readmission resulted in 0.60 AUC for all patients with RFC, 0.57 AUC with LR for women-only subpopulation, and 0.61 AUC with LR for men-only subpopulation. For 90-day readmission, the highest AUC was achieved with kernel SVM and RFC (AUC = 0.62). We observed higher predictive value when training models with only women (AUC = 0.68 LR) vs men (AUC = 0.62 kernel SVM). Prediction for death resulted in 0.67 AUC for all patients, 0.72 for women-only subpopulation, and 0.69 for men-only subpopulation, all with LR. MELD-Na model AUC was similar to those from the AI models. DISCUSSION: Despite using multiple AI techniques, it is difficult to predict 30- and 90-day readmissions and death in cirrhosis. AI model accuracies were equivalent to models generated using only MELD-Na scores. Additional biomarkers are needed to improve our predictive capability (See also the visual abstract at http://links.lww.com/AJG/B710).

Objective The diagnosis of autoimmune pancreatitis (AIP) is challenging. Sonographic and cross-sectional imaging findings of AIP closely mimic pancreatic ductal adenocarcinoma (PDAC) and techniques for tissue sampling of AIP are suboptimal. These limitations often result in delayed or failed diagnosis, which negatively impact patient management and outcomes. This study aimed to create an endoscopic ultrasound (EUS)-based convolutional neural network (CNN) model trained to differentiate AIP from PDAC, chronic pancreatitis (CP) and normal pancreas (NP), with sufficient performance to analyse EUS video in real time. Design A database of still image and video data obtained from EUS examinations of cases of AIP, PDAC, CP and NP was used to develop a CNN. Occlusion heatmap analysis was used to identify sonographic features the CNN valued when differentiating AIP from PDAC. Results From 583 patients (146 AIP, 292 PDAC, 72 CP and 73 NP), a total of 1 174 461 unique EUS images were extracted. For video data, the CNN processed 955 EUS frames per second and was: 99% sensitive, 98% specific for distinguishing AIP from NP; 94% sensitive, 71% specific for distinguishing AIP from CP; 90% sensitive, 93% specific for distinguishing AIP from PDAC; and 90% sensitive, 85% specific for distinguishing AIP from all studied conditions (ie, PDAC, CP and NP). Conclusion The developed EUS-CNN model accurately differentiated AIP from PDAC and benign pancreatic conditions, thereby offering the capability of earlier and more accurate diagnosis. Use of this model offers the potential for more timely and appropriate patient care and improved outcome.

INTRODUCTION: Ablation of Barrett's esophagus (BE) is the preferred approach for the treatment of neoplasia without visible lesions. Limited data on cryoballoon ablation (CBA) suggest its potential clinical utility. We evaluated the safety and efficacy of CBA in a multicenter study of patients with neoplastic BE. METHODS: In a prospective clinical trial, 11 academic and community centers recruited consecutive patients with BE of 1–6 cm length and low-grade dysplasia, high-grade dysplasia (HGD), or intramucosal adenocarcinoma (ImCA) confirmed by central pathology. Patients with symptomatic pre-existing strictures or visible BE lesions had dilation or endoscopic mucosal resection (EMR), respectively, before enrollment. A nitrous oxide cryoballoon focal ablation system was used to treat all visible columnar mucosa in up to 5 sessions. Study end points included complete eradication of all dysplasia (CE-D) and intestinal metaplasia (CE-IM) at 1 year. RESULTS: One hundred twenty patients with BE with ImCA (20%), HGD (56%), or low-grade dysplasia (23%) were enrolled. In the intention-to-treat analysis, the CE-D and CE-IM rates were 76% and 72%, respectively. In the per-protocol analysis (94 patients), the CE-D and CE-IM rates were 97% and 91%, respectively. Postablation pain was mild and short lived. Fifteen subjects (12.5%) developed strictures requiring dilation. One patient (0.8%) with HGD progressed to ImCA, which was successfully treated with EMR. Another patient (0.8%) developed gastrointestinal bleeding associated with clopidogrel use. One patient (0.8%) had buried BE with HGD in 1 biopsy, not confirmed by subsequent EMR. DISCUSSION: In patients with neoplastic BE, CBA was safe and effective. Head-to-head comparisons between CBA and other ablation modalities are warranted (clinicaltrials.gov registration NCT02514525).