Endoscopy最新文献

Healthcare is responsible for ~4.4% of global carbon dioxide (CO₂) emissions and endoscopy is the third largest contributor. This study aimed to quantify CO₂ use in colonoscopy and assess the impact of different valves and practices on emissions and costs.CO₂ use was measured using a mass flow meter. The study compared CO₂ flow using the standard gas/water valves, which continuously release CO₂, with non-leak valves, which only release CO₂ when depressed. It also assessed the impact of judicious use of CO₂. An unpaired student t test was used to calculate statistical significance.Without a colonoscope attached, CO₂ flow averaged 3.24 L/min. With the standard valve, flow dropped to 2.55 L/min, and with the non-leak valve, it was negligible. CO₂ emissions were measured intraprocedurally during 351 colonoscopies. Using a non-leak valve and/or judicious CO₂ application significantly reduced emissions compared with standard practice using a standard valve. This approach could reduce local emissions by >87%. Nationally, it would lead to emissions reductions of 106.5 metric tons of CO₂ per annum with cost savings of >£260 000.Judicious CO₂ application and use of a non-leak valve significantly reduced CO₂ emissions and costs in colonoscopy, contributing to the UK National Health Service goal of delivering a "net zero" service. We suggest turning off CO₂ when not needed, adopting non-leak valves, implementing this practice in other endoscopic procedures, and encouraging all endoscope manufacturers to develop similar valves.

Gastroparesis is predominantly caused by diabetes mellitus or vagal nerve injury post-surgery. About 30% of patients develop gastroparesis after esophagectomy with gastric pull-through. Standard treatments often fail, and endoscopic pyloromyotomy (G-POEM) has shown promising results. This study aimed to assess the efficacy and safety of G-POEM in patients with refractory gastroparesis after esophagectomy.A multicenter retrospective cohort study was conducted across 18 expert centers. Patients who underwent G-POEM for refractory gastroparesis following esophagectomy from August 2014 to December 2023 were included. Inclusion criteria were confirmed gastroparesis by scintigraphy, a mean Gastroparesis Cardinal Symptom Index (GCSI) of at least 1.0, and a minimum of 6 months of follow-up. The primary outcome was treatment success at 6 months, defined as a ≥50% decrease in the GCSI score.Of 113 G-POEM procedures, 108 patients (median age 65 years; 75% men) met the inclusion criteria. The primary indication for esophagectomy was adenocarcinoma (75.5%). At 6 months, 63.5% (95%CI 54.1%-72.0%) achieved clinical success, with the mean GCSI significantly decreased to 1.2 (95%CI 1.0-1.4) from 2.9 (95%CI 2.7-3.1) preprocedure. Minor adverse events occurred in 2.8% of cases. Long-term follow-up showed sustained efficacy with success rates of 54.9% and 66.1% at 12 and 24 months, respectively.G-POEM appears to be a safe and effective treatment for refractory gastroparesis in post-esophagectomy patients, achieving significant symptom relief in the majority of patients. Future prospective studies are necessary to further validate these findings and explore predictive factors for treatment success.

Withdrawal time has emerged as a critical quality measure in colonoscopy for colorectal cancer screening. Owing to the high variability in calculating withdrawal time, recent research has explored the use of artificial intelligence (AI) to standardize this process, but prospective validation is lacking.This prospective, superiority trial compared the accuracy of AI-assisted withdrawal time calculation with that of physicians during routine colonoscopy from December 2023 to March 2024. The gold standard was obtained via manual, frame-by-frame annotation of the examination video recordings. The AI also automatically generated an image report, which was qualitatively assessed by four endoscopists.126 patients were analyzed. The proposed AI system demonstrated a significantly lower mean absolute error (MAE) in estimating withdrawal time compared with physicians (2.2 vs. 4.2 minutes; P < 0.001). This was attributed to examinations containing endoscopic interventions, where the AI had significantly lower MAE compared with physicians (2.1 vs. 5.2; P < 0.001). The MAE was comparable in the absence of interventions (2.3 vs. 2.3; P = 0.52). High-quality image reports were generated by the AI system; 97% were assessed as showing satisfactory timeline representation and 81% achieved overall satisfaction.Our study demonstrated the superiority of an AI system in calculating withdrawal time during colonoscopy compared with physicians, providing significant improvements, especially in examinations involving interventions. This work demonstrates the promise of AI in streamlining clinical workflows.

Diagnosing Helicobacter pylori infection and premalignant gastric conditions typically requires ¹³C urea breath testing or histological assessment, which are often unavailable in remote areas. A rural-to-center artificial intelligence (AI) model was developed and implemented to automatically evaluate upper endoscopy images from routine clinical practice.Endoscopic images were collected from a rural hospital on Matsu Islands and a tertiary center across Taiwan Strait. During model development (2020-2022), AI algorithms were trained, validated, and tested to exclude low-quality and non-gastric images, segment gastric regions, and enhance mucosal features for detecting H. pylori infection and premalignant conditions. During model implementation (2023-2024), endoscopic images from a rural hospital were transmitted to the medical center for AI analyses, with results promptly returned.In the development phase, diagnostic accuracies were 92.8% (95%CI 88.9%-96.6%) for H. pylori, 88.6% (95%CI 87.2%-90.0%) for atrophic gastritis, and 88.0% (95%CI 86.5%-89.5%) for intestinal metaplasia. In the implementation phase, 3518 rural residents underwent ¹³C urea breath testing or pepsinogen testing; 421 with positive results underwent endoscopy. No significant differences were observed between AI-predicted and clinically observed prevalence: H. pylori (13.9% vs. 12.9%; P = 0.55), atrophic gastritis (15.7% vs. 11.9%; P = 0.34), and intestinal metaplasia (27.6% vs. 22.4%; P = 0.32). Implementation-phase diagnostic accuracies were 91.3% (95%CI 88.0%-94.6%), 79.9% (95%CI 72.1%-86.3%), and 63.4% (95%CI 54.7%-71.6%), respectively.AI enabled physicians in resource-limited settings to rapidly assess gastric health using routinely captured endoscopic images, bridging gaps in access and expertise.

Current post-polypectomy guidelines recommend a 3-year surveillance colonoscopy for individuals with polyps ≥10 mm as the sole high risk feature, although the necessity of such strict surveillance, particularly for polyps of 10-20 mm, remains uncertain. We aimed to compare post-colonoscopy colorectal cancer (PCCRC) risk between these individuals and those without polyps at baseline colonoscopy.Data of quality-assured baseline colonoscopies in the Dutch fecal immunochemical test (FIT)-based CRC screening program (2014-2020) were used. According to the guidelines prevailing at that time, a subset of individuals with ≥10-mm adenomas without high grade dysplasia or serrated polyps ≥10 mm without dysplasia were advised 5-year surveillance. For these individuals, PCCRC risk within 5 years was assessed and compared with the risk of polyp-free individuals using multilevel Cox regression analysis.Of all individuals with high risk polyps, 79% had polyps ≥10 mm and 46% had polyps 10-20 mm as the sole high risk feature. In total 21 522 individuals with ≥10-mm polyps and 69 688 individuals without polyps were included in comparative analyses. PCCRC incidence per 10 000 person-years of follow-up was 3.07 (95%CI 1.76-4.38) for individuals with ≥10-mm polyps and 5.02 (95%CI 4.08-5.97) for individuals without polyps. Risk of PCCRC was comparable between the two groups (hazard ratio 0.67, 95%CI 0.42-1.07).PCCRC risk 5 years after baseline colonoscopy for individuals with polyps ≥10 mm without other high risk features is not significantly different from individuals without polyps at baseline. Lengthening surveillance intervals would affect 79% of high risk individuals with ≥10-mm polyps as their sole high risk feature, and 46% if limited to those with polyps of 10-20 mm.