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May 2024 – ICYMI

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Gastroenterology

January 2024

Hirano I, et al; ASCENT WORKING GROUP. Ascending to New Heights for Novel Therapeutics for Eosinophilic Esophagitis. Gastroenterology. 2024 Jan;166(1):1-10. doi: 10.1053/j.gastro.2023.09.004. Epub 2023 Sep 9. PMID: 37690772; PMCID: PMC10872872.

Åkerström JH, et al. Antireflux Surgery Versus Antireflux Medication and Risk of Esophageal Adenocarcinoma in Patients With Barrett’s Esophagus. Gastroenterology. 2024 Jan;166(1):132-138.e3. doi: 10.1053/j.gastro.2023.08.050. Epub 2023 Sep 9. PMID: 37690771.

Barnes EL, et al; AGA Clinical Guidelines Committee. AGA Clinical Practice Guideline on the Management of Pouchitis and Inflammatory Pouch Disorders. Gastroenterology. 2024 Jan;166(1):59-85. doi: 10.1053/j.gastro.2023.10.015. PMID: 38128971.

February 2024

Yoo HW, et al. Helicobacter pylori Treatment and Gastric Cancer Risk After Endoscopic Resection of Dysplasia: A Nationwide Cohort Study. Gastroenterology. 2024 Feb;166(2):313-322.e3. doi: 10.1053/j.gastro.2023.10.013. Epub 2023 Oct 18. PMID: 37863270.

Yang J, et al. High Soluble Fiber Promotes Colorectal Tumorigenesis Through Modulating Gut Microbiota and Metabolites in Mice. Gastroenterology. 2024 Feb;166(2):323-337.e7. doi: 10.1053/j.gastro.2023.10.012. Epub 2023 Oct 18. PMID: 37858797.

Young E, et al. Texture and Color Enhancement Imaging Improves Colonic Adenoma Detection: A Multicenter Randomized Controlled Trial. Gastroenterology. 2024 Feb;166(2):338-340.e3. doi: 10.1053/j.gastro.2023.10.008. Epub 2023 Oct 14. PMID: 37839498.

Clinical Gastroenterology and Hepatology

January 2024

Overbeek KA, et al; Dutch Familial Pancreatic Cancer Surveillance Study work group. Intraductal Papillary Mucinous Neoplasms in High-Risk Individuals: Incidence, Growth Rate, and Malignancy Risk. Clin Gastroenterol Hepatol. 2024 Jan;22(1):62-71.e7. doi: 10.1016/j.cgh.2023.03.035. Epub 2023 Apr 7. PMID: 37031711.

Reddy CA, et al. Achalasia is Strongly Associated With Eosinophilic Esophagitis and Other Allergic Disorders. Clin Gastroenterol Hepatol. 2024 Jan;22(1):34-41.e2. doi: 10.1016/j.cgh.2023.06.013. Epub 2023 Jun 28. PMID: 37391057; PMCID: PMC10753026.

Thiruvengadam NR, et al. The Clinical Impact and Cost-Effectiveness of Surveillance of Incidentally Detected Gastric Intestinal Metaplasia: A Microsimulation Analysis. Clin Gastroenterol Hepatol. 2024 Jan;22(1):51-61. doi: 10.1016/j.cgh.2023.05.028. Epub 2023 Jun 9. Erratum in: Clin Gastroenterol Hepatol. 2024 Jan 19;: PMID: 37302442.

February 2024

Goodoory VC, et al. Systematic Review and Meta-analysis: Efficacy of Mesalamine in Irritable Bowel Syndrome. Clin Gastroenterol Hepatol. 2024 Feb;22(2):243-251.e5. doi: 10.1016/j.cgh.2023.02.014. Epub 2023 Feb 27. PMID: 36858143.

Brenner DM, et al. Development and Current State of Digital Therapeutics for Irritable Bowel Syndrome. Clin Gastroenterol Hepatol. 2024 Feb;22(2):222-234. doi: 10.1016/j.cgh.2023.09.013. Epub 2023 Sep 22. PMID: 37743035.

Techniques and Innovations in Gastrointestinal Endoscopy

January 2024

Ramirez PR, et al. Gaps and Improvement Opportunities in Post-Colonoscopy Communication. Tech Innov Gastrointest Endosc. 2024 Jan;26(1):90-92. doi: 10.1016/j.tige.2023.10.001. Epub 2023 Oct 22.

Gonzaga ER, et al. Gastric Peroral Endoscopic Myotomy (G-POEM) for the Management of Gastroparesis. Tech Innov Gastrointest Endosc. 2024 Jan; 26(1): 46-55. doi: 10.1016/j.tige.2023.09.002. Epub 2023 Oct 13.

Wang D, et al. Sphincterotomy vs Sham Procedure for Pain Relief in Sphincter of Oddi Dysfunction: Systematic Review and Meta-analysis. Tech Innov Gastrointest Endosc. 2024 Jan;26(1): 30-37. doi: 10.1016/j.tige.2023.10.003. Epub 2023 Nov 8.

Gastro Hep Advances

January 2024

Adeniran E, et al. Intense and Sustained Alcohol Consumption Associated With Acute Pancreatitis Warrants Early Intervention. Gastro Hep Advances. 2024 Jan;3(1):61-63. doi: 10.1016/j.gastha.2023.08.017. Epub 2023 Sep 2.

Alkhouri N, et al. A Novel Prescription Digital Therapeutic Option for the Treatment of Metabolic Dysfunction-Associated Steatotic Liver Disease. Gastro Hep Advances. 2024 Jan;3(1): 9-16. doi: 10.1016/j.gastha.2023.08.019. Epub 2023 Oct 1.

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Artificial Intelligence in GI and Hepatology

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Dear colleagues,

Since our prior Perspectives piece on artificial intelligence (AI) in GI and Hepatology in 2022, the field has seen almost exponential growth. Expectations are high that AI will revolutionize our field and significantly improve patient care. But as the global discussion on AI has shown, there are real challenges with adoption, including issues with accuracy, reliability, and privacy.

In this issue, Dr. Nabil M. Mansour and Dr. Thomas R. McCarty explore the current and future impact of AI on gastroenterology, while Dr. Basile Njei and Yazan A. Al Ajlouni assess its role in hepatology. We hope these pieces will help your discussions in incorporating or researching AI for use in your own practices. We welcome your thoughts on this issue on X @AGA_GIHN.

Gyanprakash A. Ketwaroo, MD, MSc, is associate professor of medicine, Yale University, New Haven, Conn., and chief of endoscopy at West Haven (Conn.) VA Medical Center. He is an associate editor for GI & Hepatology News.

Artificial Intelligence in Gastrointestinal Endoscopy

BY THOMAS R. MCCARTY, MD, MPH; NABIL M. MANSOUR, MD

The last few decades have seen an exponential increase and interest in the role of artificial intelligence (AI) and adoption of deep learning algorithms within healthcare and patient care services. The field of gastroenterology and endoscopy has similarly seen a tremendous uptake in acceptance and implementation of AI for a variety of gastrointestinal conditions. The spectrum of AI-based applications includes detection or diagnostic-based as well as therapeutic assistance tools. From the first US Food and Drug Administration (FDA)-approved device that uses machine learning to assist clinicians in detecting lesions during colonoscopy, to other more innovative machine learning techniques for small bowel, esophageal, and hepatobiliary conditions, AI has dramatically changed the landscape of gastrointestinal endoscopy.

Approved applications for colorectal cancer

In an attempt to improve colorectal cancer screening and outcomes related to screening and surveillance, efforts have been focused on procedural performance metrics, quality indicators, and tools to aid in lesion detection and improve quality of care. One such tool has been computer-aided detection (CADe), with early randomized controlled trial (RCT) data showing significantly increased adenoma detection rate (ADR) and adenomas per colonoscopy (APC).^1-3

Ultimately, this data led to FDA approval of the CADe system GI Genius (Medtronic, Dublin, Ireland) in 2021.⁴ Additional systems have since been FDA approved or 510(k) cleared including Endoscreener (Wision AI, Shanghai, China), SKOUT (Iterative Health, Cambridge, Massachusetts), MAGENTIQ-COLO (MAGENTIQ-EYE LTD, Haifa, Israel), and CAD EYE (Fujifilm, Tokyo), all of which have shown increased ADR and/or increased APC and/or reduced adenoma miss rates in randomized trials.⁵

Yet despite the promise of improved quality and subsequent translation to better patient outcomes, there has been a noticeable disconnect between RCT data and more real-world literature.⁶ In a recent study, no improvement was seen in ADR after implementation of a CADe system for colorectal cancer screening — including both higher and lower-ADR performers. Looking at change over time after implementation, CADe had no positive effect in any group over time, divergent from early RCT data. In a more recent multicenter, community-based RCT study, again CADe did not result in a statistically significant difference in the number of adenomas detected.⁷ The differences between some of these more recent “real-world” studies vs the majority of data from RCTs raise important questions regarding the potential of bias (due to unblinding) in prospective trials, as well as the role of the human-AI interaction.

Importantly for RCT data, both cohorts in these studies met adequate ADR benchmarks, though it remains unclear whether a truly increased ADR necessitates better patient outcomes — is higher always better? In addition, an important consideration with evaluating any AI/CADe system is that they often undergo frequent updates, each promising improved accuracy, sensitivity, and specificity. This is an interesting dilemma and raises questions about the enduring relevance of studies conducted using an outdated version of a CADe system.

Additional unanswered questions regarding an ideal ADR for implementation, preferred patient populations for screening (especially for younger individuals), and the role and adoption of computer-aided polyp diagnosis/characterization (CADx) within the United States remain. Furthermore, questions regarding procedural withdrawal time, impact on sessile serrated lesion detection, cost-effectiveness, and preferred adoption strategies have begun to be explored, though require more data to better define a best practice approach. Ultimately, answers to some of these unknowns may explain the discordant results and help guide future implementation measures.

Innovative applications for alternative gastrointestinal conditions

Given the fervor and excitement, as well as the outcomes associated with AI-based colorectal screening, it is not surprising these techniques have been expanded to other gastrointestinal conditions. At this time, all of these are fledgling, mostly single-center tools, not yet ready for widespread adoption. Nonetheless, these represent a potentially important step forward for difficult-to-manage gastrointestinal diseases.

Machine learning CADe systems have been developed to help identify early Barrett’s neoplasia, depth and invasion of gastric cancer, as well as lesion detection in small bowel video capsule endoscopy.^8-10 Endoscopic retrograde cholangiopancreatography (ERCP)-based applications for cholangiocarcinoma and indeterminate stricture diagnosis have also been studied.¹¹ Additional AI-based algorithms have been employed for complex procedures such as endoscopic submucosal dissection (ESD) or peroral endoscopic myotomy (POEM) to delineate vessels, better define tissue planes for dissection, and visualize landmark structures.^12,13 Furthermore, AI-based scope guidance/manipulation, bleeding detection, landmark identification, and lesion detection have the potential to revolutionize endoscopic training and education. The impact that generative AI can potentially have on clinical practice is also an exciting prospect that warrants further investigation.

Artificial intelligence adoption in clinical practice

Clinical practice with regard to AI and colorectal cancer screening largely mirrors the disconnect in the current literature, with “believers” and “non-believers” as well as innovators and early adopters alongside laggards. In our own academic practices, we continue to struggle with the adoption and standardized implementation of AI-based colorectal cancer CADe systems, despite the RCT data showing positive results. It is likely that AI uptake will follow the technology predictions of Amara’s Law — i.e., individuals tend to overestimate the short-term impact of new technologies while underestimating long-term effects. In the end, more widespread adoption in community practice and larger scale real-world clinical outcomes studies are likely to determine the true impact of these exciting technologies. For other, less established AI-based tools, more data are currently required.

Conclusions

Ultimately, AI-based algorithms are likely here to stay, with continued improvement and evolution to occur based on provider feedback and patient care needs. Current tools, while not all-encompassing, have the potential to dramatically change the landscape of endoscopic training, diagnostic evaluation, and therapeutic care. It is critically important that relevant stakeholders, both endoscopists and patients, be involved in future applications and design to improve efficiency and quality outcomes overall.

Dr. McCarty is based in the Lynda K. and David M. Underwood Center for Digestive Disorders, Houston Methodist Hospital. Dr. Mansour is based in the section of gastroenterology, Baylor College of Medicine, Houston. Dr. McCarty reports no conflicts of interest. Dr. Mansour reports having been a consultant for Iterative Health.

References

1. Repici A, et al. Efficacy of real-time computer-aided detection of colorectal neoplasia in a randomized trial. Gastroenterology. 2020 Aug. doi: 10.1053/j.gastro.2020.04.062.

2. Repici A, et al. Artificial intelligence and colonoscopy experience: Lessons from two randomised trials. Gut. Apr 2022. doi: 10.1136/gutjnl-2021-324471.

3. Wallace MB, et al. Impact of artificial intelligence on miss rate of colorectal neoplasia. Gastroenterology 2022 Jul. doi: 10.1053/j.gastro.2022.03.007.

4. United States Food and Drug Administration (FDA). GI Genius FDA Approval [April 9, 2021]. Accessed January 5, 2022. Available at: www.accessdata.fda.gov/cdrh_docs/pdf21/K211951.pdf.

5. Maas MHJ, et al. A computer-aided polyp detection system in screening and surveillance colonoscopy: An international, multicentre, randomised, tandem trial. Lancet Digit Health. 2024 Mar. doi: 10.1016/S2589-7500(23)00242-X.

6. Ladabaum U, et al. Computer-aided detection of polyps does not improve colonoscopist performance in a pragmatic implementation trial. Gastroenterology. 2023 Mar. doi: 10.1053/j.gastro.2022.12.004.

7. Wei MT, et al. Evaluation of computer-aided detection during colonoscopy in the community (AI-SEE): A multicenter randomized clinical trial. Am J Gastroenterol. 2023 Oct. doi: 10.14309/ajg.0000000000002239.

8. de Groof J, et al. The Argos project: The development of a computer-aided detection system to improve detection of Barrett’s neoplasia on white light endoscopy. United European Gastroenterol J. 2019 May. doi: 10.1177/2050640619837443.

9. Kanesaka T, et al. Computer-aided diagnosis for identifying and delineating early gastric cancers in magnifying narrow-band imaging. Gastrointest Endosc. 2018 May. doi: 10.1016/j.gie.2017.11.029.

10. Sahafi A, et al. Edge artificial intelligence wireless video capsule endoscopy. Sci Rep. 2022 Aug. doi: 10.1038/s41598-022-17502-7.

11. Njei B, et al. Artificial intelligence in endoscopic imaging for detection of malignant biliary strictures and cholangiocarcinoma: A systematic review. Ann Gastroenterol. 2023 Mar-Apr. doi: 10.20524/aog.2023.0779.

12. Ebigbo A, et al. Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm. Gut. 2022 Dec. doi: 10.1136/gutjnl-2021-326470.

13. Cao J, et al. Intelligent surgical workflow recognition for endoscopic submucosal dissection with real-time animal study. Nat Commun. 2023 Oct. doi: 10.1038/s41467-023-42451-8.

The Promise and Challenges of AI in Hepatology

BY BASILE NJEI, MD, MPH, PHD; YAZAN A. AL-AJLOUNI, MPHIL

In the dynamic realm of medicine, artificial intelligence (AI) emerges as a transformative force, notably within hepatology. The discipline of hepatology, dedicated to liver and related organ diseases, is ripe for AI’s promise to revolutionize diagnostics and treatment, pushing toward a future of precision medicine. Yet, the path to fully realizing AI’s potential in hepatology is laced with data, ethical, and integration challenges.

The application of AI, particularly in histopathology, significantly enhances disease diagnosis and staging in hepatology. AI-driven approaches remedy traditional histopathological challenges, such as interpretative variability, providing more consistent and accurate disease analyses. This is especially evident in conditions like metabolic dysfunction-associated steatohepatitis (MASH) and hepatocellular carcinoma (HCC), where AI aids in identifying critical gene signatures, thereby refining therapy selection.

Similarly, deep learning (DL), a branch of AI, has attracted significant interest globally, particularly in image recognition. AI’s incorporation into medical imaging marks a significant advancement, enabling early detection of malignancies like HCC and improving diagnostics in steatotic liver disease through enhanced imaging analyses using convolutional neural networks (CNN). The abundance of imaging data alongside clinical outcomes has catalyzed AI’s integration into radiology, leading to the swift growth of radiomics as a novel domain in medical research.

AI has also been shown to identify nuanced alterations in electrocardiograms (EKGs) associated with liver conditions, potentially detecting the progression of liver diseases at an earlier stage than currently possible. By leveraging complex algorithms and machine learning, AI can analyze EKG patterns with a precision and depth unattainable through traditional manual interpretation. Given that liver diseases, such as cirrhosis or hepatitis, can induce subtle cardiac changes long before other clinical symptoms manifest, early detection through AI-enhanced EKG analysis could lead to timely interventions, potentially halting or reversing disease progression. This approach further enriches our understanding of the intricate interplay between liver function and cardiac health, highlighting the potential for AI to transform not just liver disease diagnostics but also to foster a more integrated approach to patient care.

Beyond diagnostics, the burgeoning field of generative AI introduces groundbreaking possibilities in treatment planning and patient education, particularly for chronic conditions like cirrhosis. Generative AI produces original content, including text, visuals, and music, by identifying and learning patterns from its training data. When it leverages large language models (LLMs), it entails training on vast collections of textual data and using AI models characterized by many parameters. A notable instance of generative AI employing LLMs is ChatGPT (General Pretrained Transformers). By simulating disease progression and treatment outcomes, generative AI can foster personalized treatment strategies and empower patients with knowledge about their health trajectories. Yet, realizing these potential demands requires overcoming data quality and interpretability challenges, and ensuring AI outputs are accessible and actionable for clinicians and patients.

Despite these advancements, leveraging AI in hepatology is not devoid of hurdles. The development and training of AI models require extensive and diverse datasets, raising concerns about data privacy and ethical use. Addressing these concerns is paramount for successfully integrating AI into clinical hepatology practice, necessitating transparent algorithmic processes and stringent ethical standards. Ethical considerations are central to AI’s integration into hepatology. Algorithmic biases, patient privacy, and the impact of AI-driven decisions underscore the need for cautious AI deployment. Developing transparent, understandable algorithms and establishing ethical guidelines for AI use are critical steps towards ethically leveraging AI in patient care.

In conclusion, AI’s integration into hepatology holds tremendous promise for advancing patient care through enhanced diagnostics, treatment planning, and patient education. Overcoming the associated challenges, including ethical concerns, data diversity, and algorithm interpretability, is crucial. As the hepatology community navigates this technological evolution, a balanced approach that marries technological advancements with ethical stewardship will be key to harnessing AI’s full potential, ensuring it serves the best interests of patients and propels the field of hepatology into the future.

We predict a trajectory of increased use and adoption of AI in hepatology. AI in hepatology is likely to meet the test of pervasiveness, improvement, and innovation. The adoption of AI in routine hepatology diagnosis and management will likely follow Amara’s law and the five stages of the hype cycle. We believe that we are still in the infant stages of adopting AI technology in hepatology, and this phase may last 5 years before there is a peak of inflated expectations. The trough of disillusionment and slopes of enlightenment may only be observed in the next decades.

Dr. Njei is based in the Section of Digestive Diseases, Yale School of Medicine, New Haven, Conn. Mr. Al-Ajlouni is a senior medical student at New York Medical College School of Medicine, Valhalla, N.Y. They have no conflicts of interest to declare.

Sources

Taylor-Weiner A, et al. A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASH. Hepatology. 2021 Jul. doi: 10.1002/hep.31750.

Zeng Q, et al. Artificial intelligence predicts immune and inflammatory gene signatures directly from hepatocellular carcinoma histology. J Hepatol. 2022 Jul. doi: 10.1016/j.jhep.2022.01.018.

Ahn JC, et al. Development of the AI-Cirrhosis-ECG Score: An Electrocardiogram-Based Deep Learning Model in Cirrhosis. Am J Gastroenterol. 2022 Mar. doi: 10.14309/ajg.0000000000001617.

Nduma BN, et al. The Application of Artificial Intelligence (AI)-Based Ultrasound for the Diagnosis of Fatty Liver Disease: A Systematic Review. Cureus. 2023 Dec 15. doi: 10.7759/cureus.50601.

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All rights reserved. This material may not be published, broadcast, copied, or otherwise reproduced or distributed without the prior written permission of Frontline Medical Communications Inc.</copyrightNotice> </rightsInfo> </provider> <abstract/> <metaDescription>Dear colleagues,Since our prior Perspectives piece on artificial intelligence (AI) in GI and Hepatology in 2022, the field has seen almost exponential growth. 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Mansour</description> <description role="drol:credit">Baylor College of Medicine</description> </link> <link> <itemClass qcode="ninat:picture"/> <altRep contenttype="image/jpeg">images/24012818.jpg</altRep> <description role="drol:caption">Dr. Basile Njei</description> <description role="drol:credit">Yale School of Medicine</description> </link> <link> <itemClass qcode="ninat:picture"/> <altRep contenttype="image/jpeg">images/24012817.jpg</altRep> <description role="drol:caption">Yazan A. Al-Ajlouni</description> <description role="drol:credit">New York Medical College</description> </link> </links> </header> <itemSet> <newsItem> <itemMeta> <itemRole>Main</itemRole> <itemClass>text</itemClass> <title>Artificial Intelligence in GI and Hepatology</title> <deck/> </itemMeta> <itemContent> Dear colleagues, Since <a href="https://gastro.org/news/innovation-in-gi-whats-the-next-big-thing/">our prior Perspectives piece</a> on artificial intelligence (AI) in GI and Hepatology in 2022, the field has seen almost exponential growth. Expectations are high that AI will revolutionize our field and significantly improve patient care. But as the global discussion on AI has shown, there are real challenges with adoption, including issues with accuracy, reliability, and privacy. In this issue, Dr. Nabil M. Mansour and Dr. Thomas R. McCarty explore the current and future impact of AI on gastroenterology, while Dr. Basile Njei and Yazan A. Al Ajlouni assess its role in hepatology. We hope these pieces will help your discussions in incorporating or researching AI for use in your own practices. We welcome your thoughts on this issue on X <a href="https://twitter.com/AGA_GIHN">@AGA_GIHN</a>. Gyanprakash A. Ketwaroo, MD, MSc, is associate professor of medicine, Yale University, New Haven, Conn., and chief of endoscopy at West Haven (Conn.) VA Medical Center. He is an associate editor for GI & Hepatology News. <h2>Artificial Intelligence in Gastrointestinal Endoscopy</h2> BY THOMAS R. MCCARTY, MD, MPH; NABIL M. MANSOUR, MD The last few decades have seen an exponential increase and interest in the role of artificial intelligence (AI) and adoption of deep learning algorithms within healthcare and patient care services. The field of gastroenterology and endoscopy has similarly seen a tremendous uptake in acceptance and implementation of AI for a variety of gastrointestinal conditions. The spectrum of AI-based applications includes detection or diagnostic-based as well as therapeutic assistance tools. From the first US Food and Drug Administration (FDA)-approved device that uses machine learning to assist clinicians in detecting lesions during colonoscopy, to other more innovative machine learning techniques for small bowel, esophageal, and hepatobiliary conditions, AI has dramatically changed the landscape of gastrointestinal endoscopy.[[{"fid":"300209","view_mode":"medstat_image_flush_left","fields":{"format":"medstat_image_flush_left","field_file_image_alt_text[und][0][value]":"Dr. Nabil M. Mansour, McNair General GI Clinic at Baylor College of Medicine in Houston","field_file_image_credit[und][0][value]":"Baylor College of Medicine","field_file_image_caption[und][0][value]":"Dr. Nabil M. Mansour"},"type":"media","attributes":{"class":"media-element file-medstat_image_flush_left"}}]] Approved applications for colorectal cancer In an attempt to improve colorectal cancer screening and outcomes related to screening and surveillance, efforts have been focused on procedural performance metrics, quality indicators, and tools to aid in lesion detection and improve quality of care. One such tool has been computer-aided detection (CADe), with early randomized controlled trial (RCT) data showing significantly increased adenoma detection rate (ADR) and adenomas per colonoscopy (APC).1-3 Ultimately, this data led to FDA approval of the CADe system GI Genius (Medtronic, Dublin, Ireland) in 2021.4 Additional systems have since been FDA approved or 510(k) cleared including Endoscreener (Wision AI, Shanghai, China), SKOUT (Iterative Health, Cambridge, Massachusetts), MAGENTIQ-COLO (MAGENTIQ-EYE LTD, Haifa, Israel), and CAD EYE (Fujifilm, Tokyo), all of which have shown increased ADR and/or increased APC and/or reduced adenoma miss rates in randomized trials.5 Yet despite the promise of improved quality and subsequent translation to better patient outcomes, there has been a noticeable disconnect between RCT data and more real-world literature.6 In a recent study, no improvement was seen in ADR after implementation of a CADe system for colorectal cancer screening — including both higher and lower-ADR performers. Looking at change over time after implementation, CADe had no positive effect in any group over time, divergent from early RCT data. In a more recent multicenter, community-based RCT study, again CADe did not result in a statistically significant difference in the number of adenomas detected.7 The differences between some of these more recent “real-world” studies vs the majority of data from RCTs raise important questions regarding the potential of bias (due to unblinding) in prospective trials, as well as the role of the human-AI interaction. Importantly for RCT data, both cohorts in these studies met adequate ADR benchmarks, though it remains unclear whether a truly increased ADR necessitates better patient outcomes — is higher always better? In addition, an important consideration with evaluating any AI/CADe system is that they often undergo frequent updates, each promising improved accuracy, sensitivity, and specificity. This is an interesting dilemma and raises questions about the enduring relevance of studies conducted using an outdated version of a CADe system. Additional unanswered questions regarding an ideal ADR for implementation, preferred patient populations for screening (especially for younger individuals), and the role and adoption of computer-aided polyp diagnosis/characterization (CADx) within the United States remain. Furthermore, questions regarding procedural withdrawal time, impact on sessile serrated lesion detection, cost-effectiveness, and preferred adoption strategies have begun to be explored, though require more data to better define a best practice approach. Ultimately, answers to some of these unknowns may explain the discordant results and help guide future implementation measures. Innovative applications for alternative gastrointestinal conditions Given the fervor and excitement, as well as the outcomes associated with AI-based colorectal screening, it is not surprising these techniques have been expanded to other gastrointestinal conditions. At this time, all of these are fledgling, mostly single-center tools, not yet ready for widespread adoption. Nonetheless, these represent a potentially important step forward for difficult-to-manage gastrointestinal diseases. Machine learning CADe systems have been developed to help identify early Barrett’s neoplasia, depth and invasion of gastric cancer, as well as lesion detection in small bowel video capsule endoscopy.8-10 Endoscopic retrograde cholangiopancreatography (ERCP)-based applications for cholangiocarcinoma and indeterminate stricture diagnosis have also been studied.11 Additional AI-based algorithms have been employed for complex procedures such as endoscopic submucosal dissection (ESD) or peroral endoscopic myotomy (POEM) to delineate vessels, better define tissue planes for dissection, and visualize landmark structures.12,13 Furthermore, AI-based scope guidance/manipulation, bleeding detection, landmark identification, and lesion detection have the potential to revolutionize endoscopic training and education. The impact that generative AI can potentially have on clinical practice is also an exciting prospect that warrants further investigation. Artificial intelligence adoption in clinical practice Clinical practice with regard to AI and colorectal cancer screening largely mirrors the disconnect in the current literature, with “believers” and “non-believers” as well as innovators and early adopters alongside laggards. In our own academic practices, we continue to struggle with the adoption and standardized implementation of AI-based colorectal cancer CADe systems, despite the RCT data showing positive results. It is likely that AI uptake will follow the technology predictions of Amara’s Law — i.e., individuals tend to overestimate the short-term impact of new technologies while underestimating long-term effects. In the end, more widespread adoption in community practice and larger scale real-world clinical outcomes studies are likely to determine the true impact of these exciting technologies. For other, less established AI-based tools, more data are currently required. Conclusions Ultimately, AI-based algorithms are likely here to stay, with continued improvement and evolution to occur based on provider feedback and patient care needs. Current tools, while not all-encompassing, have the potential to dramatically change the landscape of endoscopic training, diagnostic evaluation, and therapeutic care. It is critically important that relevant stakeholders, both endoscopists and patients, be involved in future applications and design to improve efficiency and quality outcomes overall. Dr. McCarty is based in the Lynda K. and David M. Underwood Center for Digestive Disorders, Houston Methodist Hospital. Dr. Mansour is based in the section of gastroenterology, Baylor College of Medicine, Houston. Dr. McCarty reports no conflicts of interest. Dr. Mansour reports having been a consultant for Iterative Health. <h2>References</h2> 1. Repici A, et al. Efficacy of real-time computer-aided detection of colorectal neoplasia in a randomized trial. Gastroenterology. 2020 Aug. doi: <a href="https://doi.org/10.1053/j.gastro.2020.04.062">10.1053/j.gastro.2020.04.062</a>. 2. Repici A, et al. Artificial intelligence and colonoscopy experience: Lessons from two randomised trials. Gut. Apr 2022. doi: <a href="https://gut.bmj.com/content/71/4/757">10.1136/gutjnl-2021-324471</a>. 3. Wallace MB, et al. Impact of artificial intelligence on miss rate of colorectal neoplasia. Gastroenterology 2022 Jul. doi: <a href="https://doi.org/10.1053/j.gastro.2022.03.007">10.1053/j.gastro.2022.03.007</a>. 4. United States Food and Drug Administration (FDA). GI Genius FDA Approval [April 9, 2021]. Accessed January 5, 2022. Available at: <a href="https://www.accessdata.fda.gov/cdrh_docs/pdf21/K211951.pdf">www.accessdata.fda.gov/cdrh_docs/pdf21/K211951.pdf</a>. 5. Maas MHJ, et al. A computer-aided polyp detection system in screening and surveillance colonoscopy: An international, multicentre, randomised, tandem trial. Lancet Digit Health. 2024 Mar. doi: <a href="https://www.thelancet.com/journals/landig/article/PIIS2589-7500(23)00242-X/fulltext">10.1016/S2589-7500(23)00242-X</a>. 6. Ladabaum U, et al. Computer-aided detection of polyps does not improve colonoscopist performance in a pragmatic implementation trial. Gastroenterology. 2023 Mar. doi: <a href="https://doi.org/10.1053/j.gastro.2022.12.004">10.1053/j.gastro.2022.12.004</a>. 7. Wei MT, et al. Evaluation of computer-aided detection during colonoscopy in the community (AI-SEE): A multicenter randomized clinical trial. Am J Gastroenterol. 2023 Oct. doi: <a href="https://journals.lww.com/ajg/abstract/2023/10000/evaluation_of_computer_aided_detection_during.28.aspx">10.14309/ajg.0000000000002239</a>. 8. de Groof J, et al. The Argos project: The development of a computer-aided detection system to improve detection of Barrett’s neoplasia on white light endoscopy. United European Gastroenterol J. 2019 May. doi: <a href="https://onlinelibrary.wiley.com/doi/10.1177/2050640619837443">10.1177/2050640619837443</a>. 9. Kanesaka T, et al. Computer-aided diagnosis for identifying and delineating early gastric cancers in magnifying narrow-band imaging. Gastrointest Endosc. 2018 May. doi: <a href="https://doi.org/10.1016/j.gie.2017.11.029">10.1016/j.gie.2017.11.029</a>. 10. Sahafi A, et al. Edge artificial intelligence wireless video capsule endoscopy. Sci Rep. 2022 Aug. doi: <a href="https://www.nature.com/articles/s41598-022-17502-7">10.1038/s41598-022-17502-7</a>. 11. Njei B, et al. Artificial intelligence in endoscopic imaging for detection of malignant biliary strictures and cholangiocarcinoma: A systematic review. Ann Gastroenterol. 2023 Mar-Apr. doi: <a href="https://doi.org/10.20524/aog.2023.0779">10.20524/aog.2023.0779</a>. 12. Ebigbo A, et al. Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm. Gut. 2022 Dec. doi: <a href="https://gut.bmj.com/content/71/12/2388">10.1136/gutjnl-2021-326470</a>. 13. Cao J, et al. Intelligent surgical workflow recognition for endoscopic submucosal dissection with real-time animal study. Nat Commun. 2023 Oct. doi: <a href="https://www.nature.com/articles/s41467-023-42451-8">10.1038/s41467-023-42451-8</a>. <h2>The Promise and Challenges of AI in Hepatology</h2> BY BASILE NJEI, MD, MPH, PHD; YAZAN A. AL-AJLOUNI, MPHIL In the dynamic realm of medicine, artificial intelligence (AI) emerges as a transformative force, notably within hepatology. The discipline of hepatology, dedicated to liver and related organ diseases, is ripe for AI’s promise to revolutionize diagnostics and treatment, pushing toward a future of precision medicine. Yet, the path to fully realizing AI’s potential in hepatology is laced with data, ethical, and integration challenges. The application of AI, particularly in histopathology, significantly enhances disease diagnosis and staging in hepatology. AI-driven approaches remedy traditional histopathological challenges, such as interpretative variability, providing more consistent and accurate disease analyses. This is especially evident in conditions like metabolic dysfunction-associated steatohepatitis (MASH) and hepatocellular carcinoma (HCC), where AI aids in identifying critical gene signatures, thereby refining therapy selection. [[{"fid":"301101","view_mode":"medstat_image_flush_right","fields":{"format":"medstat_image_flush_right","field_file_image_alt_text[und][0][value]":"Dr. Basile Njei, Section of Digestive Diseases, Yale School of Medicine, New Haven, Conn.","field_file_image_credit[und][0][value]":"Yale School of Medicine","field_file_image_caption[und][0][value]":"Dr. Basile Njei"},"type":"media","attributes":{"class":"media-element file-medstat_image_flush_right"}}]]Similarly, deep learning (DL), a branch of AI, has attracted significant interest globally, particularly in image recognition. AI’s incorporation into medical imaging marks a significant advancement, enabling early detection of malignancies like HCC and improving diagnostics in steatotic liver disease through enhanced imaging analyses using convolutional neural networks (CNN). The abundance of imaging data alongside clinical outcomes has catalyzed AI’s integration into radiology, leading to the swift growth of radiomics as a novel domain in medical research. AI has also been shown to identify nuanced alterations in electrocardiograms (EKGs) associated with liver conditions, potentially detecting the progression of liver diseases at an earlier stage than currently possible. By leveraging complex algorithms and machine learning, AI can analyze EKG patterns with a precision and depth unattainable through traditional manual interpretation. Given that liver diseases, such as cirrhosis or hepatitis, can induce subtle cardiac changes long before other clinical symptoms manifest, early detection through AI-enhanced EKG analysis could lead to timely interventions, potentially halting or reversing disease progression. This approach further enriches our understanding of the intricate interplay between liver function and cardiac health, highlighting the potential for AI to transform not just liver disease diagnostics but also to foster a more integrated approach to patient care. [[{"fid":"301100","view_mode":"medstat_image_flush_right","fields":{"format":"medstat_image_flush_right","field_file_image_alt_text[und][0][value]":"Yazan A. Al-Ajlouni, senior medical student at New York Medical College School of Medicine, Valhalla, N.Y.","field_file_image_credit[und][0][value]":"New York Medical College","field_file_image_caption[und][0][value]":"Yazan A. Al-Ajlouni"},"type":"media","attributes":{"class":"media-element file-medstat_image_flush_right"}}]]Beyond diagnostics, the burgeoning field of generative AI introduces groundbreaking possibilities in treatment planning and patient education, particularly for chronic conditions like cirrhosis. Generative AI produces original content, including text, visuals, and music, by identifying and learning patterns from its training data. When it leverages large language models (LLMs), it entails training on vast collections of textual data and using AI models characterized by many parameters. A notable instance of generative AI employing LLMs is ChatGPT (General Pretrained Transformers). By simulating disease progression and treatment outcomes, generative AI can foster personalized treatment strategies and empower patients with knowledge about their health trajectories. Yet, realizing these potential demands requires overcoming data quality and interpretability challenges, and ensuring AI outputs are accessible and actionable for clinicians and patients. Despite these advancements, leveraging AI in hepatology is not devoid of hurdles. The development and training of AI models require extensive and diverse datasets, raising concerns about data privacy and ethical use. Addressing these concerns is paramount for successfully integrating AI into clinical hepatology practice, necessitating transparent algorithmic processes and stringent ethical standards. Ethical considerations are central to AI’s integration into hepatology. Algorithmic biases, patient privacy, and the impact of AI-driven decisions underscore the need for cautious AI deployment. Developing transparent, understandable algorithms and establishing ethical guidelines for AI use are critical steps towards ethically leveraging AI in patient care. In conclusion, AI’s integration into hepatology holds tremendous promise for advancing patient care through enhanced diagnostics, treatment planning, and patient education. Overcoming the associated challenges, including ethical concerns, data diversity, and algorithm interpretability, is crucial. As the hepatology community navigates this technological evolution, a balanced approach that marries technological advancements with ethical stewardship will be key to harnessing AI’s full potential, ensuring it serves the best interests of patients and propels the field of hepatology into the future. We predict a trajectory of increased use and adoption of AI in hepatology. AI in hepatology is likely to meet the test of pervasiveness, improvement, and innovation. The adoption of AI in routine hepatology diagnosis and management will likely follow Amara’s law and the five stages of the hype cycle. We believe that we are still in the infant stages of adopting AI technology in hepatology, and this phase may last 5 years before there is a peak of inflated expectations. The trough of disillusionment and slopes of enlightenment may only be observed in the next decades. Dr. Njei is based in the Section of Digestive Diseases, Yale School of Medicine, New Haven, Conn. Mr. Al-Ajlouni is a senior medical student at New York Medical College School of Medicine, Valhalla, N.Y. They have no conflicts of interest to declare. <h2>Sources</h2> Taylor-Weiner A, et al. A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASH. Hepatology. 2021 Jul. doi: <a href="https://journals.lww.com/hep/toc/2021/07000">10.1002/hep.31750</a>. Zeng Q, et al. Artificial intelligence predicts immune and inflammatory gene signatures directly from hepatocellular carcinoma histology. J Hepatol. 2022 Jul. doi: <a href="https://doi.org/10.1016/j.jhep.2022.01.018">10.1016/j.jhep.2022.01.018</a>. Ahn JC, et al. Development of the AI-Cirrhosis-ECG Score: An Electrocardiogram-Based Deep Learning Model in Cirrhosis. Am J Gastroenterol. 2022 Mar. doi: <a href="https://journals.lww.com/ajg/toc/2022/03000">10.14309/ajg.0000000000001617</a>. Nduma BN, et al. The Application of Artificial Intelligence (AI)-Based Ultrasound for the Diagnosis of Fatty Liver Disease: A Systematic Review. Cureus. 2023 Dec 15. doi: <a href="https://www.cureus.com/articles/187909-the-application-of-artificial-intelligence-ai-based-ultrasound-for-the-diagnosis-of-fatty-liver-disease-a-systematic-review#!/">10.7759/cureus.50601</a>. </itemContent> </newsItem> <newsItem> <itemMeta> <itemRole>teaser</itemRole> <itemClass>text</itemClass> <title/> <deck/> </itemMeta> <itemContent> </itemContent> </newsItem> </itemSet></root>

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GLP-1s May Increase Post-Endoscopy Aspiration Pneumonia Risk

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Thu, 04/25/2024 - 13:21

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Carolyn Crist

The use of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) may lead to an increased risk for aspiration pneumonia after endoscopic procedures, according to a new large population-based study.

In June 2023, the American Society of Anesthesiologists (ASA) recommended holding GLP-1 RAs before an endoscopic or surgical procedure to reduce the risk for complications associated with anesthesia and delayed stomach emptying.

In response, the American Gastroenterological Association (AGA) published a rapid clinical practice update in November 2023 that found insufficient evidence to support patients stopping the medications before endoscopic procedures.

“It is known that GLP-1 RAs significantly reduce the motility of the stomach and small bowel. As more and more patients are being started on GLP-1 RAs at higher doses and longer half-life, the question became whether the current recommended fasting durations are enough to reasonably assume the stomach is empty prior to procedures that require sedation,” said senior author Ali Rezaie, MD, medical director of the GI Motility Program at Cedars-Sinai Medical Center in Los Angeles.

“We wanted to see if these medications in fact increased the chance of aspiration before the ASA suggestion went into effect,” he said. “However, this is not an easy task, as aspiration is a rare event and a large sample size is needed to confidently answer that question. That is why we evaluated nearly 1 million cases.”

The study was published online in Gastroenterology.

Analyzing GLP-1 RA Use

Dr. Rezaie and colleagues conducted a population-based, retrospective cohort study of the TriNetX dataset, which includes 114 million deidentified individual health records from 80 healthcare organizations. The research team analyzed nearly 1 million records for adult patients between ages 21 and 70 who underwent upper and lower endoscopies between January 2018 and December 2020.

The researchers defined GLP-1 RA users as those who had the medication for more than 6 months and two or more refills within 6 months before the procedure. They adjusted for 59 factors that could affect gut motility or aspiration risks, such as obesity, numerous chronic diseases, and dozens of medications. The primary outcome was aspiration pneumonia within a month after the procedure.

Among 963,184 patients who underwent endoscopy, 46,935 (4.9%) were considered GLP-1 RA users. Among those, 20,099 GLP-1 RA users met the inclusion criteria and had their results compared with non-GLP-1 RA users.

After propensity score matching for the 59 potential confounders, GLP-1 RA use had a higher incidence rate of aspiration pneumonia (0.83% vs 0.63%) and was associated with a significantly higher risk for aspiration pneumonia, with a hazard ratio (HR) of 1.33.

An even higher risk was seen among patients with propofol-assisted endoscopies (HR, 1.49) but not among those without propofol (HR, 1.31).

In a subgroup analysis based on endoscopy type, an elevated risk was observed among patients who underwent upper endoscopy (HR, 1.82) and combined upper and lower endoscopy (HR, 2.26) but not lower endoscopy (HR, 0.56).

“The results were not necessarily surprising given the mechanism of action of GLP-1 RAs. However, for the first time, this was shown with a clinically relevant outcome, such as aspiration pneumonia,” Dr. Rezaie said. “Aspiration during sedation can have devastating consequences, and the 0.2% difference in risk of aspiration can have a significant effect on healthcare as well.”

More than 20 million endoscopies are performed across the United States annually. Based on the assumption that about 3% of those patients are taking GLP-1 RAs, about 1200 aspiration cases per year can be prevented by raising awareness, he said.

Considering Next Steps

The varying risk profiles observed with separate sedation and endoscopy types point to a need for more tailored guidance in managing GLP-1 RA use before a procedure, the study authors wrote.

Although holding the medications before endoscopy may disrupt diabetes management, the potential increased risk for aspiration could justify a change in practice, particularly for upper endoscopy and propofol-associated procedures, they added.

At the same time, additional studies are needed to understand the optimal drug withholding windows before endoscopies and other procedures, they concluded.

“We will need more data on what is the optimal duration of holding GLP-1 RAs,” Dr. Rezaie said. “But given our data and current ASA guidance, stopping these medications prior to elective procedures is the safe thing to do.”

For now, AGA guidance remains the same as offered in the November 2023 update, suggesting an individual approach for each patient on a GLP-1 RA rather than a “blanket statement” on how to manage all patients taking these medications.

“Overall, I believe that this study is important, but we require more high-level data to inform clinical decision-making regarding patients using GLP-1 receptor agonists prior to gastrointestinal endoscopy,” said Andrew Y. Wang, MD, AGAF, chief of gastroenterology and hepatology and director of interventional endoscopy at the University of Virginia in Charlottesville.

Dr. Wang, who wasn’t involved with this study, coauthored the AGA rapid clinical practice update. He and colleagues advised continuing with a procedure as planned for patients on GLP-1 RAs who followed standard preprocedure fasting instructions and didn’t have nausea, vomiting, dyspepsia, or abdominal distention.

Among patients with symptoms that suggest retained gastric contents, rapid sequence intubation may be considered, though it may not be possible in ambulatory or office-based endoscopy settings, Dr. Wang and colleagues wrote. As another option in lieu of stopping GLP-1 RAs, patients can be placed on a liquid diet for 1 day before the procedure.

“While this study found a signal suggesting that patients using GLP-1 RAs had an increased risk of aspiration pneumonia within 1 month following upper endoscopy or combined upper and lower endoscopy, it does not inform us if having patients stop GLP-1 RAs before endoscopic procedures — especially for a single dose — will mitigate this potential risk,” Dr. Wang said.

“It was also interesting that these investigators found that patients taking GLP-1 RAs who underwent lower endoscopy alone were not at increased risk for aspiration pneumonia,” Dr. Wang noted.

The authors didn’t report a funding source and disclosed no potential conflicts. Dr. Wang reported no relevant disclosures.

A version of this article appeared on Medscape.com.

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The use of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) may lead to an increased risk for aspiration pneumonia after endoscopic procedures, according to a new large population-based study.

Analyzing GLP-1 RA Use

Considering Next Steps

The varying risk profiles observed with separate sedation and endoscopy types point to a need for more tailored guidance in managing GLP-1 RA use before a procedure, the study authors wrote.

A version of this article appeared on Medscape.com.

The use of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) may lead to an increased risk for aspiration pneumonia after endoscopic procedures, according to a new large population-based study.

Analyzing GLP-1 RA Use

Considering Next Steps

The varying risk profiles observed with separate sedation and endoscopy types point to a need for more tailored guidance in managing GLP-1 RA use before a procedure, the study authors wrote.

A version of this article appeared on Medscape.com.

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AGA Clinical Practice Update Describes High-Quality Upper Endoscopy

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Thu, 04/11/2024 - 09:07

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Will Pass

American Gastroenterological Association (AGA) has published a clinical practice update detailing best practices for performing a high-quality upper endoscopy exam.

The update, authored by Satish Nagula, MD, of Icahn School of Medicine at Mount Sinai, New York, NY, and colleagues, includes nine pieces of best practice advice that address procedure optimization, evaluation of suspected premalignancy, and postprocedure follow-up evaluation.

“Deﬁning what constitutes a high-quality esophagogastroduodenoscopy (EGD) poses somewhat of a challenge because the spectrum of indications and the breadth of benign and (pre)malignant disease pathology in the upper GI tract is very broad,” the update panelists wrote in Clinical Gastroenterology and Hepatology. “Standardizing the measures deﬁning a high-quality upper endoscopic examination is one of the ﬁrst steps for assessing quality.”

Preprocedure Recommendations

Dr. Nagula and colleagues first emphasized that EGD should be performed for an appropriate indication, citing a recent meta-analysis that found 21.7% of upper endoscopy procedures were performed for an inappropriate indication. Of note, diagnostic yields were 42% higher in procedures performed for an appropriate indication.

After ensuring an appropriate indication, the update also encourages clinicians to inform patients of the various benefits, risks, and alternatives of the procedure prior to providing consent.

Intraprocedure Recommendations

During the procedure, endoscopists should take several steps to ensure optimal visualization of tissues, according to the update.

First, a high-definition (HD) white-light endoscopy system should be employed.

“Although HD imaging is a standard feature of newer-generation endoscopes, legacy standard-deﬁnition scopes remain in use,” Dr. Nagula and colleagues noted. “Moreover, to provide true HD image resolution, each component of the system (eg, the endoscope video chip, the processor, the monitor, and transmission cables) must be HD compatible.”

This HD-compatible system should be coupled with image-enhancing technology to further improve lesion detection. In Barrett’s esophagus, the panelists noted, image enhancement can improve lesion detection as much as 20%.

They predicted that AI-assisted software may boost detection rates even higher: “Computer-aided detection and computer-aided diagnosis systems for upper endoscopy are still in the early phases of development but do show similar promise for improving the detection and characterization of upper GI tract neoplasia.”

Beyond selection of best available technologies, the update encourages more fundamental strategies to improve visualization, including mucosal cleansing and insufflation, with sufficient time spent inspecting the foregut mucosa via anterograde and retroflexed views.

Where appropriate, standardized biopsy protocols should be followed to evaluate and manage foregut conditions.

Postprocedure Recommendations

After the procedure, endoscopists should offer patients management recommendations based on the endoscopic findings and, if necessary, notify them that more recommendations may be forthcoming based on histopathology results, according to the update.

Similarly, endoscopists should follow established surveillance intervals for future procedures, with modifications made as needed, based on histopathology findings.

Document, Document, Document

Throughout the update, Dr. Nagula and colleagues repeatedly emphasize the importance of documentation, from preprocedural discussions with patients through planned surveillance schedules.

However, the recommendations are clear about “weighing the practical implications” of “onerous” documentation, particularly photodocumentation requirements. For instance, the authors note that “there are some scenarios in which more rigorous photodocumentation standards during upper endoscopy should be considered, such as patients with risk factors for neoplasia,” but at the very least “photodocumentation of any suspicious abnormalities, ideally with annotations, is strongly advised.”

Moving Toward Quality Standardization for Upper Endoscopy

“These best practice advice statements are intended to improve measurable clinical, patient-reported, and economic healthcare outcomes and are not meant to put an additional burden on endoscopists,” the panelists wrote. “Ideally, future research will set threshold indicators of adherence to these best practices that optimally are associated with these aforementioned objective outcomes.”

This update was commissioned and approved by AGA. The update panelists disclosed relationships with Covidien LP, Fujiﬁlm USA, Mahana Therapeutics, and others.

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American Gastroenterological Association (AGA) has published a clinical practice update detailing best practices for performing a high-quality upper endoscopy exam.

Preprocedure Recommendations

After ensuring an appropriate indication, the update also encourages clinicians to inform patients of the various benefits, risks, and alternatives of the procedure prior to providing consent.

Intraprocedure Recommendations

During the procedure, endoscopists should take several steps to ensure optimal visualization of tissues, according to the update.

Postprocedure Recommendations

Similarly, endoscopists should follow established surveillance intervals for future procedures, with modifications made as needed, based on histopathology findings.

Document, Document, Document

Throughout the update, Dr. Nagula and colleagues repeatedly emphasize the importance of documentation, from preprocedural discussions with patients through planned surveillance schedules.

Moving Toward Quality Standardization for Upper Endoscopy

This update was commissioned and approved by AGA. The update panelists disclosed relationships with Covidien LP, Fujiﬁlm USA, Mahana Therapeutics, and others.

American Gastroenterological Association (AGA) has published a clinical practice update detailing best practices for performing a high-quality upper endoscopy exam.

Preprocedure Recommendations

After ensuring an appropriate indication, the update also encourages clinicians to inform patients of the various benefits, risks, and alternatives of the procedure prior to providing consent.

Intraprocedure Recommendations

During the procedure, endoscopists should take several steps to ensure optimal visualization of tissues, according to the update.

Postprocedure Recommendations

Similarly, endoscopists should follow established surveillance intervals for future procedures, with modifications made as needed, based on histopathology findings.

Document, Document, Document

Throughout the update, Dr. Nagula and colleagues repeatedly emphasize the importance of documentation, from preprocedural discussions with patients through planned surveillance schedules.

Moving Toward Quality Standardization for Upper Endoscopy

This update was commissioned and approved by AGA. The update panelists disclosed relationships with Covidien LP, Fujiﬁlm USA, Mahana Therapeutics, and others.

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Power-Washing Moves Beyond Home Improvement, Into Gastroenterology

A Promising Approach, but Challenges Remain

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Wed, 04/10/2024 - 09:35

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Will Pass

Power-washing is no longer just for blasting grimy driveways and stripping flaky paint. It’s good for work inside the gut, too.

In a proof-of-concept study, a “novel systematically directed high-pressure liquid spray,” delivered via the ERBEJET flexible probe, showed promise for collecting cytology specimens from the stomachs of patients undergoing endoscopy for gastric cancer screening or surveillance, reported lead author Charles J. Lightdale, MD, of Columbia University Irving Medical Center, New York City, and colleagues.

“Systematic random biopsies (updated Sydney protocol) have been recommended to increase detection of gastric intestinal metaplasia (GIM) and dysplasia,” the investigators wrote in Techniques and Innovations in Gastrointestinal Endoscopy. “However, random biopsies can be laborious, time consuming, costly, and susceptible to sampling error owing to the large surface area of the stomach.”

Power-washing, in contrast, with the pressure dial turned to 10 bar, involves spraying the gut in a systematic fashion “using sweeping and painting motions” to dislodge cells from the mucosa. These specimens are then suctioned from the resultant pools of liquid, mixed 1:1 with 10% formalin, and shipped to the lab.

Boom! Cytology!

Just to be sure, however, the nine patients involved in the study also underwent standard-of-care biopsy collection from areas of interest, followed by random sampling according to the updated Sydney protocol. Two of the patients were power-washed again 12 months later for endoscopic surveillance.

Power-washing added 7-10 minutes to standard endoscopy time and generated 60-100 mL of liquid for collection. Post suction, a closer look at the gastric mucosa revealed “scattered superficial erosions,” while blood loss was deemed “minimal.” The procedure appeared well tolerated, with no aspiration or esophageal reflux during endoscopy, or adverse events reported by patients after 1 week of follow-up.

Cytopathology samples were deemed satisfactory and yielded “multiple strips and large clusters of cells.” These were sufficient to diagnose GIM in three patients and reactive glandular changes with inflammation in one patient, with findings confirmed on biopsy. In contrast, the power-washed cells from one patient were “highly suspicious” for dysplasia, but biopsies were negative.

Although the study was too small for a reliable comparison with the Sydney protocol, Dr. Lightdale and colleagues concluded that the power-wash approach deserves further investigation.

“Use of power-wash to obtain cytology has the potential to improve endoscopic screening and surveillance protocols for detecting GIM and dysplasia and to reduce morbidity and mortality from gastric cancer,” they wrote.

The investigators predicted that power-washing is likely safe in most patients, although it may be unsuitable for those with noncorrectable coagulopathies or in patients who cannot stop anticoagulants. Postsurgical patients, on the other hand, should tolerate the procedure just fine.

Patients with risk of gastric cancer “might be an important group” for evaluating the power-wash procedure, the investigators wrote, noting that combining the approach with artificial intelligence could one day yield even better results.

In the meantime, Dr. Lightdale and colleagues — like so many weekend warriors wielding a power-washer — are going to see if a different nozzle will take their work to the next level.

“We are actively studying a catheter with a broader stream and the potential to increase efficiency and decrease procedure time,” they wrote. “Another catheter design might allow for simultaneous spray and suction, so that cytology samples from specific regions of the stomach could be separately analyzed.”

This study was funded by Dalio Philanthropies, the Price Family Foundation, and the Frederic and Patricia Salerno Foundation. The investigators disclosed relationships with Boston Scientiﬁc, Interscope, Medtronic, and others.

Body

The optimal surveillance endoscopic modality for gastric intestinal metaplasia (GIM) is yet to be determined. Although the updated Sydney System, a comprehensive endoscopic biopsy protocol, has been advocated for GIM mapping, challenges are the heterogeneous distribution of GIM, suboptimal diagnostic accuracy of endoscopy to detect GIM, and the cost burden of multiple biopsies.

This study by Lightdale et al. demonstrated the technical feasibility and safety of obtaining cytology for the detection of gastric intestinal metaplasia by using a systemic endoscopy-guided high-pressure spray “power-wash” method. In this study, all cytophathology samples in nine subjects were deemed satisfactory for evaluation. All three subjects who were cytology positive for GIM on H&E stain and confirmed with positive immunohistochemistry (IHC) showed GIM on biopsy, and one subject had cells highly suspicious for dysplasia on cytology but biopsy was negative. Although all patients showed multiple superficial erosions after power-wash, bleeding was minimal and no adverse events related to power-wash were observed.

Applying cytology for detection of GIM appears promising as the way of collecting samples from the large surface area of the stomach. As clinicians, however, we are still left with some challenges. Even if cells collected are suspicious for dysplasia/neoplasia by this power-wash method, it would not be useful unless we precisely localize the area as we can not provide a focal curative endoscopic treatment. It is critical to increase the yield of localization of cytology sampling. Further research is also needed to standardize the cytopathologic diagnostic criteria of GIM and cost-effectiveness of the cytology-based approach compared to the current gold-standard biopsy protocol for the diagnosis of GIM.

Yutaka Tomizawa, MD, MSc, is a therapeutic endoscopist and clinical associate professor of medicine, Division of Gastroenterology, University of Washington, Seattle. He has no conflicts related to this report.

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A Promising Approach, but Challenges Remain

Power-washing is no longer just for blasting grimy driveways and stripping flaky paint. It’s good for work inside the gut, too.

Boom! Cytology!

Power-washing is no longer just for blasting grimy driveways and stripping flaky paint. It’s good for work inside the gut, too.

Boom! Cytology!

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Computer-Aided Colonoscopy Falls Short in Real-World Practice

Jury is still out on CADe

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Colonoscopy with computer-aided detection (CADe) fails to improve adenoma detection rate (ADR) in real-world, nonrandomized trials, according to investigators.

Although CADe did not increase burden of colonoscopy in the real-world, these real-world detection rates casts doubt on the generalizability of positive findings from randomized trials, reported lead author Harsh K. Patel, MD, of the University of Kansas Medical Center, Kansas City, Missouri, and colleagues.

CADe-assisted colonoscopy has gained increasing attention for its potential to improve ADR, particularly with the recent publication of a meta-analysis involving 20 randomized controlled trials (RCTs), Dr. Patel and colleagues wrote in Clinical Gastroenterology and Hepatology. “However, results of RCTs are not necessarily reproducible in clinical practice.”

RCTs evaluating this technology are susceptible to various issues with validity, they noted, such as psychological bias stemming from lack of blinding to the possibility that CADe could reduce operator attention, paradoxically “deskilling” endoscopists.

The present meta-analysis aimed to overcome these potential shortfalls by analyzing nonrandomized data from eight studies involving 9,782 patients.

“The lack of a highly controlled setting reduces the psychological pressure of the endoscopists to demonstrate a possible beneﬁt of CADe (i.e., the operator bias) and allows endoscopists to use CADe according to their preferences and attitudes which we usually experience in a real-world clinical practice,” the investigators wrote. “On the other hand, noncontrolled factors may affect the outcome of the study, especially when considering that an equivalent distribution of prevalence of disease is required for a fair assessment of the effectiveness of the intervention.”

This approach revealed less favorable outcomes than those reported by RCTs.

CADe-assisted ADR was not significantly different from ADR for standard colonoscopy (44% vs 38%; risk ratio, 1.11; 95% CI, 0.97-1.28), nor was mean number of adenomas detected per colonoscopy (0.93 vs 0.79; mean difference, 0.14; 95% CI, -0.04-0.32).

“Our study provides a contrasting perspective to those results previously known from the randomized studies,” the investigators wrote.

While detection benefits were not identified, burden of CADe-assisted colonoscopy was not elevated either.

Mean nonneoplastic lesions per colonoscopy was similar between modalities (0.52 vs 0.47; mean difference, 0.14; 95% CI, -0.07-0.34), as was withdrawal time (14.3 vs 13.4 minutes; mean difference, 0.8 minutes; 95% CI, -0.18-1.90).

Dr. Patel and colleagues described “a high level of heterogeneity that was qualitatively and quantitatively distinct from the heterogeneity discovered in the prior meta-analysis of RCTs.” Unlike the RCT meta-analysis, which had no studies with an ADR outcome favoring the control arm, the present meta-analysis found that one third of the included studies favored the control arm.

“This qualitative difference generates a much higher degree of ambiguity, as it does not apply only to the magnitude of the effect of CADe, but it puts in question the actual existence of any CADe-related beneﬁt,” they wrote. “An important point to make is that the analysis of adenoma and serrated lesions per colonoscopy supported the qualitative heterogeneity, favoring the control arm over the CADe arm, in the direction of the effect.”

Dr. Patel and colleagues suggested that the concurrent lack of benefit and lack of harm associated with CADe in the present meta-analysis is “interesting,” and may point to underutilization or a lack of effect of CADe.

“To address the uncertainties in the current literature, we recommend conducting additional randomized studies in a more pragmatic setting,” they concluded.

This meta-analysis was supported by the European Commission and AIRC. The investigators disclosed relationships with NEC, Satisfy, Odin, and others.

Body

The advent of AI in colonoscopy through computer-aided detection (CADe) systems has been promising, with over 20 randomized controlled trials (RCTs) affirming its benefits. However, this enthusiasm has been tempered by several recent nonrandomized studies indicating no real-world advantage, as discussed in Patel et al.’s systematic review and meta-analysis in Clinical Gastroenterology and Hepatology.

[[{"fid":"300209","view_mode":"medstat_image_flush_left","fields":{"format":"medstat_image_flush_left","field_file_image_alt_text[und][0][value]":"Dr. Nabil M. Mansour, McNair General GI Clinic at Baylor College of Medicine in Houston","field_file_image_credit[und][0][value]":"Baylor College of Medicine","field_file_image_caption[und][0][value]":"Dr. Nabil M. Mansour"},"type":"media","field_deltas":{"2":{"format":"medstat_image_flush_left","field_file_image_alt_text[und][0][value]":"Dr. Nabil M. Mansour, McNair General GI Clinic at Baylor College of Medicine in Houston","field_file_image_credit[und][0][value]":"Baylor College of Medicine","field_file_image_caption[und][0][value]":"Dr. Nabil M. Mansour"}},"attributes":{"alt":"Dr. Nabil M. Mansour, McNair General GI Clinic at Baylor College of Medicine in Houston","class":"media-element file-medstat-image-flush-left","data-delta":"2"}}]]The stark differences in the results of RCTs and nonrandomized studies with CADe are interesting and thought-provoking, highlighting issues like potential RCT bias (due to lack of blinding) and the critical role of the human-AI interaction. It may be that some endoscopists derive a benefit from CADe while others do not, and further studies looking into the performance of individual endoscopists with and without CADe may be helpful. The meta-analysis also reveals varying outcomes based on study design — prospective or retrospective — and the nature of the control arm, be it concurrent or historical.

In addition, a critical consideration with evaluating any AI/CADe system is they often undergo frequent updates, each promising improved accuracy, sensitivity, and specificity. This is an interesting dilemma and raises questions about the enduring relevance of studies conducted using outdated versions of CADe.

In my opinion, the jury is still out on the effectiveness of CADe for colonoscopy in a real-world setting. The definitive assessment of CADe’s real-world value necessitates larger, well-structured trials that mirror actual clinical environments and span extended periods of time, taking care to minimize biases that may have influenced the results of current published studies.

Nabil M. Mansour, MD, is assistant professor of medicine in the Section of Gastroenterology, Baylor College of Medicine, Houston. He has served as a consultant for Iterative Health.

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Nabil M. Mansour, MD, is assistant professor of medicine in the Section of Gastroenterology, Baylor College of Medicine, Houston. He has served as a consultant for Iterative Health.

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Nabil M. Mansour, MD, is assistant professor of medicine in the Section of Gastroenterology, Baylor College of Medicine, Houston. He has served as a consultant for Iterative Health.

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Jury is still out on CADe

Colonoscopy with computer-aided detection (CADe) fails to improve adenoma detection rate (ADR) in real-world, nonrandomized trials, according to investigators.

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AGA Guides Usage of GLP-1 Receptor Agonists Before Endoscopy

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The American Gastroenterological Association (AGA) has issued a rapid clinical practice update on the use of glucagon-like peptide 1 (GLP-1) receptor agonists prior to endoscopy.

The update was partly prompted by consensus-based perioperative guidance issued by the American Society of Anesthesiologists in June 2023, which advises withholding GLP-1 receptor agonists before endoscopy. This recommendation has caused some anesthesia providers to cancel or postpone endoscopic procedures, or even elect general endotracheal intubation over standard sedation.

“Many facilities and medical centers are now struggling to revise preprocedural protocols for patients taking this class of medications despite the lack of high-level evidence regarding how to proceed,” the panelists wrote in Clinical Gastroenterology and Hepatology. “Important questions include whether these preprocedural changes are necessary, if they truly mitigate periprocedural aspiration, or if the delays instituted by following this guidance might further compound the major problem currently faced nationwide: that of large numbers of patients awaiting endoscopic procedures because of delays from the COVID-19 pandemic, reduction in the recommended age threshold to start colorectal cancer screening in 2018, and workforce challenges.”

The rapid clinical practice update, commissioned and approved by the AGA, includes background on the relationship between GLP-1 receptor agonists and endoscopic procedures, followed by clinical strategies for patients taking these medications.

Lead panelist Jana G. Al Hashash, MD, MSc, AGAF, of Mayo Clinic, Jacksonville, Florida, and colleagues began by noting that GLP-1 receptor agonists have been associated with increased gastric residue in patients with diabetes, and among nondiabetic patients, increased gastric retention of solids but not liquids. Delayed gastric emptying and increased residual gastric contents may be more common among patients on GLP-1 agonists who have vomiting, nausea, dyspepsia, or abdominal bloating, they added.

The above findings “imply an increased risk of aspiration in patients receiving GLP-1 receptor agonist medications who present for procedures that require sedation,” the panelists wrote, but more data is needed to support this hypothesis.

Yet the implications for endoscopic risk are still unclear.

Residual liquid in the stomach, at least, is “less of an issue,” according to the update, since “it is easily removed during an esophagogastroduodenoscopy, and this is the first maneuver performed by endoscopists on entering the stomach.”

While residual solids in the stomach could theoretically increase risk of aspiration, other patients with gastroparesis, such as those taking opioids, are not routinely given “special dietary precautions or medication adjustments” prior to endoscopy, Dr. Al Hashash and colleagues wrote. Even patients with severe gastroparesis who are undergoing gastric peroral endoscopic myotomy (which depends upon an empty stomach), are only required to stop ingesting solid foods the day before the procedure, they noted.

“It is appropriate that the ASA’s perioperative suggestions for patients on GLP-1 [receptor agonists] are labeled ‘consensus-based guidance on perioperative management,’ because there is clearly insufﬁcient published evidence for a robust systematic review and guideline,” they wrote. “As such, the ASA’s suggestions are expert opinions, which may inform but should not replace clinical judgment.”

The panelists therefore called for an individualized approach when managing GLP-1 receptor agonists prior to endoscopy, particularly in patients with diabetes, for whom withholding these medications “might provide more risk than benefit.”

Withholding GLP-1 receptor agonists may be safe and reasonable for patients taking them solely for weight loss, but “this should not be considered mandatory or evidence-based,” as it remains unclear whether withholding one dose is enough to restore normal gastric motility.

“Generally, in patients on GLP-1 receptor agonists who have followed standard perioperative procedures (typically an 8-hour solid-food fast and a 2-hour liquid fast) and who do not have symptoms of nausea, vomiting, dyspepsia, or abdominal distention, we advise proceeding with upper and/or lower endoscopy,” the panelists concluded.

The rapid clinical practice update was commissioned and approved by the AGA. The update panelists disclosed relationships with Apollo Endosurgery, Medtronic, Boston Scientific, and others.

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AI-Identified Vascular Healing Can Predict Clinical Relapse in Ulcerative Colitis

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Becky McCall

STOCKHOLM — An artificial intelligence (AI)–assisted image-enhanced endoscopy system accurately assessed vascular healing and predicted long-term clinical relapse in patients with ulcerative colitis (UC), according to data from the study of a novel investigational tool.

Clinical relapse was predicted in 3% of patients identified as having vascular healing in all segments compared with 23.9% in those with vascular activity (ie, one or more segments were active), reported Yasuharu Maeda, MD, gastroenterologist from Showa University Northern Yokohama Hospital, Digestive Disease Center, Yokohama, Japan.

In patients with a Mayo Endoscopic Score (MES) ≤ 1, the clinical relapse rate was 3% and 18.6% in the vascular healing and vascular active groups, respectively, he said.

Endoscopic remission is a crucial treat-to-target goal in patients with UC, and image-enhanced endoscopy is spreading in routine practice as a way to detect inflammation and to predict outcomes, Dr. Maeda said.

“Image-enhanced vascular findings lead to a stronger correlation with histological activities and long-term prognosis compared with white light endoscopy assessment,” he explained. “It also means that assessment can be done on-site without biopsy, pathologist effort, and associated costs; however, specialist training is required to achieve a high accuracy in outputs.”

Dr. Maeda presented the data (Abstract OP16) at the annual congress of the European Crohn’s and Colitis Organisation.

Stratifying the Relapse Risk

Dr. Maeda and colleagues developed a novel AI-based narrow-band imaging system, training it by using 8853 images from 167 patients with UC.

The AI system, EndoBRAIN-UC (Cybernet System Corp, Tokyo), is in use and currently adapted for only one endoscope, the Endocyto CFH290EC (Olympus EMEA, Tokyo), but for the purpose of this study, it was trained on images from five different scopes.

“By combining narrow-band imaging and AI, we developed a system where we can differentiate between vascular activity and vascular healing. This allows us to predict relapse,” Dr. Maeda said.

In an open-label, prospective cohort study, they tested the system with the aim of assessing the efficacy of AI-identified vascular healing to stratify the relapse risk in 100 patients showing clinical remission of UC (ie, partial MES ≤ 1).

Patient characteristics were similar between both groups with an average disease duration of 10 years.

In the vascular healing group (n = 33), the average age was 52 years, 20% were men, 58% had extensive colitis, and 52% had a MES score of 0.

In the vascular active group (n = 67), the average age was 56 years, 32% were men, 61% had extensive colitis, and 25% had a MES score of 0.

Colonoscopy was performed using the AI system to identify mucosa as healing or active for six colorectal segments of each patient. The MES and histologic assessment for these segments were also recorded. Patients were then followed for up to 12 months and assessed for clinical relapse.

The clinical relapse rate was higher in the vascular active group than in the vascular healing group as identified by AI.

“We only evaluated the diagnostic output of the AI but obtained white light endoscopies and biopsies for contrast studies,” Dr. Maeda noted.

They also looked at whether the endoscopist’s level of experience (ie, trainee or expert) was important but found that clinical relapse predictive values were independent of the endoscopist’s experience.

Still in the Early Stages

AI-assisted colonoscopy work is still at an early stage , said session co-moderator, Monika Ferlitsch, MD, head of Internal Medicine Department II, gastroenterology and hepatology, Evangelical Hospital, in Vienna, Austria.

We now have initial results, but “I suspect it will take 10-20 years for implementation into routine clinical practice,” she said.

The best outcome for our patients is to be able to predict response to therapy and recurrence rates, “and we see this is possible now with AI. But of course, we need more clinical data to support it,” Dr. Ferlitsch said.

Dr. Maeda and Dr. Ferlitsch have declared no financial disclosures.

A version of this article appeared on Medscape.com.

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Stratifying the Relapse Risk

Dr. Maeda and colleagues developed a novel AI-based narrow-band imaging system, training it by using 8853 images from 167 patients with UC.

Still in the Early Stages

A version of this article appeared on Medscape.com.

Stratifying the Relapse Risk

Dr. Maeda and colleagues developed a novel AI-based narrow-band imaging system, training it by using 8853 images from 167 patients with UC.

Still in the Early Stages

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The Gamer Who Became a GI Hospitalist and Dedicated Endoscopist

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Jennifer Lubell

Reflecting on his career in gastroenterology, Andy Tau, MD, (@DrBloodandGuts on X) claims the discipline chose him, in many ways.

“I love gaming, which my mom said would never pay off. Then one day she nearly died from a peptic ulcer, and endoscopy saved her,” said Dr. Tau, a GI hospitalist who practices with Austin Gastroenterology in Austin, Texas. One of his specialties is endoscopic hemostasis.

Endoscopy functions similarly to a game because the interface between the operator and the patient is a controller and a video screen, he explained. “Movements in my hands translate directly onto the screen. Obviously, endoscopy is serious business, but the tactile feel was very familiar and satisfying to me.”

Advocating for the GI hospitalist and the versatile role they play in hospital medicine, is another passion of his. “The dedicated GI hospitalist indirectly improves the efficiency of an outpatient practice, while directly improving inpatient outcomes, collegiality, and even one’s own skills as an endoscopist,” Dr. Tau wrote in an opinion piece in GI & Hepatology News .

He expounded more on this topic and others in an interview, recalling what he learned from one mentor about maintaining a sense of humor at the bedside.

Q: You’ve said that GI hospitalists are the future of patient care. Can you explain why you feel this way?

Dr. Tau: From a quality perspective, even though it’s hard to put into one word, the care of acute GI pathology and endoscopy can be seen as a specialty in and of itself. These skills include hemostasis, enteral access, percutaneous endoscopic gastrostomy (PEG), balloon-assisted enteroscopy, luminal stenting, advanced tissue closure, and endoscopic retrograde cholangiopancreatography. The greater availability of a GI hospitalist, as opposed to an outpatient GI doctor rounding at the ends of days, likely shortens admissions and improves the logistics of scheduling inpatient cases.

From a financial perspective, the landscape of GI practice is changing because of GI physician shortages relative to increased demand for outpatient procedures. Namely, the outpatient gastroenterologists simply have too much on their plate and inefficiencies abound when they have to juggle inpatient and outpatient work. Thus, two tracks are forming, especially in large busy hospitals. This is the same evolution of the pure outpatient internist and inpatient internist 20 years ago.

Q: What attributes does a GI hospitalist bring to the table?

Dr. Tau: A GI hospitalist is one who can multitask through interruptions, manage end-of-life issues, craves therapeutic endoscopy (even if that’s hemostasis), and can keep more erratic hours based on the number of consults that come in. She/he tends to want immediate gratification and doesn’t mind the lack of continuity of care. Lastly, the GI hospitalist has to be brave and yet careful as the patients are sicker and thus complications may be higher and certainly less well tolerated.

Q: Are there enough of them going into practice right now?

Dr. Tau: Not really! The demand seems to outstrip supply based on what I see. There is a definite financial lure as the market rate for them rises (because more GIs are leaving the hospital for pure outpatient practice), but burnout can be an issue. Interestingly, fellows are typically highly trained and familiar with inpatient work, but once in practice, most choose the outpatient track. I think it’s a combination of work-life balance, inefficiency of inpatient endoscopy, and perhaps the strain of daily, erratic consultation.

Q: You received the 2021 Travis County Medical Society (TCMS) Young Physician of the Year. What achievements led to this honor?

Dr. Tau: I am not sure I am deserving of that award, but I think it was related to personal risk and some long hours as a GI hospitalist during the COVID pandemic. I may have the unfortunate distinction of performing more procedures on COVID patients than any other physician in the city. My hospital was the largest COVID-designated site in the city. There were countless PEG tubes in COVID survivors and a lot of bleeders for some reason. A critical care physician on the front lines and health director of the city of Austin received Physician of the Year, deservedly.

Q: What teacher or mentor had the greatest impact on you?

Dr. Tau: David Y. Graham, MD, MACG, got me into GI as a medical student and taught me to never tolerate any loose ends when it came to patient care as a resident. He trained me at every level — from medical school, residency, and through my fellowship. His advice is often delivered sly and dry, but his humor-laden truths continue to ring true throughout my life. One story: my whole family tested positive for Helicobacter pylori after my mother survived peptic ulcer hemorrhage. I was the only one who tested negative! I asked Dr Graham about it and he quipped, “You’re lucky! It’s because your mother didn’t love (and kiss) you as much!”

Even to this moment I laugh about that. I share that with my patients when they ask about how they contracted H. pylori.

Lightning Round

Favorite junk food?

McDonalds fries

Favorite movie genre?

Psychological thriller

Cat person or dog person?

Dog

What was your favorite Halloween costume?

Ninja turtle

Favorite sport:

Football (played in college)

Introvert or extrovert?

Extrovert unless sleep deprived.

Favorite holiday:

Thanksgiving

The book you read over and over:

Swiss Family Robinson

Favorite travel destination:

Hawaii

Optimist or pessimist?

A happy pessimist.

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Reflecting on his career in gastroenterology, Andy Tau, MD, (@DrBloodandGuts on X) claims the discipline chose him, in many ways.

Q: You’ve said that GI hospitalists are the future of patient care. Can you explain why you feel this way?

Q: What attributes does a GI hospitalist bring to the table?

Q: Are there enough of them going into practice right now?

Q: You received the 2021 Travis County Medical Society (TCMS) Young Physician of the Year. What achievements led to this honor?

Q: What teacher or mentor had the greatest impact on you?

Even to this moment I laugh about that. I share that with my patients when they ask about how they contracted H. pylori.

Lightning Round

Favorite junk food?

McDonalds fries

Favorite movie genre?

Psychological thriller

Cat person or dog person?

Dog

What was your favorite Halloween costume?

Ninja turtle

Favorite sport:

Football (played in college)

Introvert or extrovert?

Extrovert unless sleep deprived.

Favorite holiday:

Thanksgiving

The book you read over and over:

Swiss Family Robinson

Favorite travel destination:

Hawaii

Optimist or pessimist?

A happy pessimist.

Reflecting on his career in gastroenterology, Andy Tau, MD, (@DrBloodandGuts on X) claims the discipline chose him, in many ways.

Q: You’ve said that GI hospitalists are the future of patient care. Can you explain why you feel this way?

Q: What attributes does a GI hospitalist bring to the table?

Q: Are there enough of them going into practice right now?

Q: You received the 2021 Travis County Medical Society (TCMS) Young Physician of the Year. What achievements led to this honor?

Q: What teacher or mentor had the greatest impact on you?

Even to this moment I laugh about that. I share that with my patients when they ask about how they contracted H. pylori.

Lightning Round

Favorite junk food?

McDonalds fries

Favorite movie genre?

Psychological thriller

Cat person or dog person?

Dog

What was your favorite Halloween costume?

Ninja turtle

Favorite sport:

Football (played in college)

Introvert or extrovert?

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FDA Emphasizes Alternative Device Sterilization Strategies

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Thu, 02/29/2024 - 12:07

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Heidi Splete

The US Food and Drug Administration has expanded its guidance on medical device sterilization to include vaporized hydrogen peroxide, according to an agency press release issued on January 8.

The update is intended to promote wider use of vaporized hydrogen peroxide (VHP) as a viable alternative to ethylene oxide (EtO). The FDA guidance on sterile devices has been revised to include VHP.

The acceptance of VHP as an Established Category A method of sterilization is another step toward the FDA’s larger goal of reducing EtO, according to the release.

Sterilization is essential for certain medical devices, but the use of EtO, currently the most common method, involves the release of emissions that are potentially harmful to health, and the FDA seeks to identify safe and effective alternatives to reduce risk to the environment and communities where device sterilization occurs. Current Established Category A sterilization methods include moist heat, dry heat, EtO, and radiation.

“Vaporized hydrogen peroxide’s addition as an established sterilization method helps us build a more resilient supply chain for sterilized devices that can help prevent medical device shortages,” Suzanne Schwartz, MD, director of the Office of Strategic Partnerships and Technology Innovation in the FDA’s Center for Devices and Radiological Health, said in the press release. “As innovations in sterilization advance, the FDA will continue to seek additional modalities that deliver safe and effective sterilization methods that best protect public health,” she said.

The FDA has supported the development of EtO alternatives since 2019, and remains committed to reducing EtO emissions and also to avoiding potential device shortages, according to the release.

“Ethylene oxide is highly flammable and carcinogenic and poses exposure-related safety concerns for reprocessing staff, as well as environmental risks,” said Venkataraman R. Muthusamy, MD, AGAF, of the University of California, Los Angeles, in an interview. “These risks have led some states or regions to ban or limit its use, but despite these risks, it is currently the most commonly used sterilization technique for medical devices in the United States,” he said. Therefore, coming up with alternatives has been a high priority for the FDA, he added.

VHP has several advantages over EtO, Dr. Muthusamy said. VHP breaks down safely into water and oxygen, with low residual levels after exposure, and has no known oxidation or discoloration effects. In addition, VHP has a low temperature, and should theoretically be safe to use with endoscopes, although data are lacking, he said.

Dr. Muthusamy said that he was not yet too familiar with VHP as a technique, in part because most accessories in GI are single-use.

Primary issues to expanding the use of vaporized hydrogen peroxide as a sterilizing agent in GI clinical practice include availability and the cost of acquiring the devices needed, Dr. Muthusamy told GI & Hepatology News. “Also, the comparative efficacy of this technique in sterilizing GI endoscopes to ethylene oxide and the impact of VHP on scope durability and performance will need to be assessed, and the impact of VHP on the health and safety of reprocessing staff will need to be assessed and monitored,” he said.

There is an interest in the GI community in “green” endoscopy and reducing waste, Dr. Muthusamy said. If an inexpensive, safe, and cost-effective option for sterilization of other devices beyond endoscopes exists, “perhaps we could reduce our use of some disposables as well,” he said.

Dr. Muthusamy had no financial conflicts to disclose.

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The US Food and Drug Administration has expanded its guidance on medical device sterilization to include vaporized hydrogen peroxide, according to an agency press release issued on January 8.

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Q: What attributes does a GI hospitalist bring to the table?

Q: Are there enough of them going into practice right now?

Q: You received the 2021 Travis County Medical Society (TCMS) Young Physician of the Year. What achievements led to this honor?

Q: What teacher or mentor had the greatest impact on you?

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