Cellular immune response to the anti-SARS-CoV-2 BNT162b2 mRNA vaccine in pediatric autoimmune inflammatory rheumatic disease patients and controls.

This paper aims to compare the cellular immune response to the SARS-CoV-2 BNT162b2 vaccine of pediatric patients with autoimmune inflammatory rheumatic disease (pAIIRD) and healthy controls. A prospective longitudinal study was conducted between April 2021 and December 2022 at the Tel Aviv Medical Center. Children <18 years, with pediatric-onset AIIRD and healthy controls, who have received at least two doses of the BNT162b2 vaccine, were included. Humoral response was evaluated by serum levels of anti-SARS-CoV-2 receptor-binding domain antibodies. Cellular response was evaluated by flow cytometry, measuring IFNγ and TNFα production by CD4+ T cells following stimulation with SARS-CoV-2 Spike peptide mix. The study included 20 pAIIRD patients and 11 controls. The mean age of participants was 12.6 ±â€…2.94 years, with 58.1% females. The cellular response to the BNT162b2 vaccine was statistically similar in both groups. However, the humoral response was statistically lower in pAIIRD compared with the healthy control group. There was no statistically significant correlation between the humoral response and cellular response. During the study period, 43.75% of AIIRD children and 72.7% of controls had a breakthrough COVID-19 infection (P = 0.48). Bivariate models examining the effect of the cellular response and presence of an AIIRD on breakthrough infections found no effect. Compared with healthy controls, pAIIRD demonstrated similar cellular responses. Patients showed reduced humoral response compared with healthy adolescents, but similar breakthrough infection rates. These findings may support the importance of the cellular response in protecting against COVID-19 infections.

Evaluation of Computer-Aided Detection During Colonoscopy in the Community (AI-SEE): A Multicenter Randomized Clinical Trial.

INTRODUCTION: There has been increasing interest in artificial intelligence in gastroenterology. To reduce miss rates during colonoscopy, there has been significant exploration in computer-aided detection (CADe) devices. In this study, we evaluate the use of CADe in colonoscopy in community-based, nonacademic practices. METHODS: Between September 28, 2020, and September 24, 2021, a randomized controlled trial (AI-SEE) was performed evaluating the impact of CADe on polyp detection in 4 community-based endoscopy centers in the United States Patients were block-randomized to undergoing colonoscopy with or without CADe (EndoVigilant). Primary outcomes measured were adenomas per colonoscopy and adenomas per extraction (the percentage of polyps removed that are adenomas). Secondary end points included serrated polyps per colonoscopy; nonadenomatous, nonserrated polyps per colonoscopy; adenoma and serrated polyp detection rates; and procedural time. RESULTS: A total of 769 patients were enrolled (387 with CADe), with similar patient demographics between the 2 groups. There was no significant difference in adenomas per colonoscopy in the CADe and non-CADe groups (0.73 vs 0.67, P = 0.496). Although the use of CADe did not improve identification of serrated polyps per colonoscopy (0.08 vs 0.08, P = 0.965), the use of CADe increased identification of nonadenomatous, nonserrated polyps per colonoscopy (0.90 vs 0.51, P < 0.0001), resulting in detection of fewer adenomas per extraction in the CADe group. The adenoma detection rate (35.9 vs 37.2%, P = 0.774) and serrated polyp detection rate (6.5 vs 6.3%, P = 1.000) were similar in the CADe and non-CADe groups. Mean withdrawal time was longer in the CADe group compared with the non-CADe group (11.7 vs 10.7 minutes, P = 0.003). However, when no polyps were identified, there was similar mean withdrawal time (9.1 vs 8.8 minutes, P = 0.288). There were no adverse events. DISCUSSION: The use of CADe did not result in a statistically significant difference in the number of adenomas detected. Additional studies are needed to better understand why some endoscopists derive substantial benefits from CADe and others do not. ClinicalTrials.gov number: NCT04555135.

Clinical evaluation of a real-time artificial intelligence-based polyp detection system: a US multi-center pilot study.

Artificial intelligence (AI) has increasingly been employed in multiple fields, and there has been significant interest in its use within gastrointestinal endoscopy. Computer-aided detection (CAD) can potentially improve polyp detection rates and decrease miss rates in colonoscopy. However, few clinical studies have evaluated real-time CAD during colonoscopy. In this study, we analyze the efficacy of a novel real-time CAD system during colonoscopy. This was a single-arm prospective study of patients undergoing colonoscopy with a real-time CAD system. This AI-based system had previously been trained using manually labeled colonoscopy videos to help detect neoplastic polyps (adenomas and serrated polyps). In this pilot study, 300 patients at two centers underwent elective colonoscopy with the CAD system. These results were compared to 300 historical controls consisting of consecutive colonoscopies performed by the participating endoscopists within 12 months prior to onset of the study without the aid of CAD. The primary outcome was the mean number of adenomas per colonoscopy. Use of real-time CAD trended towards increased adenoma detection (1.35 vs 1.07, p = 0.099) per colonoscopy though this did not achieve statistical significance. Compared to historical controls, use of CAD demonstrated a trend towards increased identification of serrated polyps (0.15 vs 0.07) and all neoplastic (adenomatous and serrated) polyps (1.50 vs 1.14) per procedure. There were significantly more non-neoplastic polyps detected with CAD (1.08 vs 0.57, p < 0.0001). There was no difference in ≥ 10 mm polyps identified between the two groups. A real-time CAD system can increase detection of adenomas and serrated polyps during colonoscopy in comparison to historical controls without CAD, though this was not statistically significant. As this pilot study is underpowered, given the findings we recommend pursuing a larger randomized controlled trial to further evaluate the benefits of CAD.