Faculty Bibliography

This document is an update to the 2014 recommendations for optimizing the adequacy of bowel cleansing for colonoscopy from the US Multi-Society Task Force on Colorectal Cancer, which represents the American College of Gastroenterology and the American Society for Gastrointestinal Endoscopy. The US Multi-Society Task Force developed consensus statements and key clinical concepts addressing important aspects of bowel preparation for colonoscopy. The majority of consensus statements focus on individuals at average risk for inadequate bowel preparation. However, statements addressing individuals at risk for inadequate bowel preparation quality are also provided. The quality of a bowel preparation is defined as adequate when standard screening or surveillance intervals can be assigned based on the findings of the colonoscopy. We recommend the use of a split-dose bowel preparation regimen and suggest that a 2 L regimen may be sufficient. A same-day regimen is recommended as an acceptable alternative for individuals undergoing afternoon colonoscopy, but we suggest that a same-day regimen is an inferior alternative for individuals undergoing morning colonoscopy. We recommend limiting dietary restrictions to the day before a colonoscopy, relying on either clear liquids or low-fiber/low-residue diets for the early and midday meals. We suggest the adjunctive use of oral simethicone for bowel preparation before colonoscopy. Routine tracking of the rate of adequate bowel preparations at the level of individual endoscopists and at the level of the endoscopy unit is also recommended, with a target of >90% for both rates.

This document is an update to the 2014 recommendations for optimizing the adequacy of bowel cleansing for colonoscopy from the US Multi-Society Task Force on Colorectal Cancer, which represents the American College of Gastroenterology, the American Gastroenterological Association, and the American Society for Gastrointestinal Endoscopy. The US Multi-Society Task Force developed consensus statements and key clinical concepts addressing important aspects of bowel preparation for colonoscopy. The majority of consensus statements focus on individuals at average risk for inadequate bowel preparation. However, statements addressing individuals at risk for inadequate bowel preparation quality are also provided. The quality of a bowel preparation is defined as adequate when standard screening or surveillance intervals can be assigned based on the findings of the colonoscopy. We recommend the use of a split-dose bowel preparation regimen and suggest that a 2 L regimen may be sufficient. A same-day regimen is recommended as an acceptable alternative for individuals undergoing afternoon colonoscopy, but we suggest that a same-day regimen is an inferior alternative for individuals undergoing morning colonoscopy. We recommend limiting dietary restrictions to the day before a colonoscopy, relying on either clear liquids or low-fiber/low-residue diets for the early and midday meals. We suggest the adjunctive use of oral simethicone for bowel preparation before colonoscopy. Routine tracking of the rate of adequate bowel preparations at the level of individual endoscopists and at the level of the endoscopy unit is also recommended, with a target of >90% for both rates.

Artificial intelligence (AI) has potential to significantly impact clinical research when it comes to research preparation and data interpretation. Development of AI tools that can help in performing literature searches, synthesizing and streamlining data collection and analysis, and formatting of study could make the clinical research process more efficient. Several of these tools have been developed and trialed and many more are being rapidly developed. This article highlights the AI applications in clinical research in gastroenterology including its impact on drug discovery and explores areas where further guidance is needed to supplement the current understanding and enhance its use.

Rates of colorectal cancer (CRC) screening in the United States continue to fall short of guideline-recommended benchmarks. Challenges to increasing CRC screening include racial disparities, barriers at multiple levels of the health care system, and inadequate completion of 2-step screening. With new options for CRC screening and employment of programmatic strategies for screening by physicians, patients will have more opportunities to initiate and complete testing, which can ultimately improve CRC detection and prevention. This article highlights the current state of and optimal approach to CRC screening.

The substantial carbon footprint imparted by medical services warrants increased attention to their environmental impact. National guideline organizations such as the US Preventive Services Task Force (USPSTF) recommend multiple modalities for average-risk colorectal cancer (CRC) screening with varying resource intensity. The aim of this study was to quantify the environmental burden for 2 of the most used CRC screening modalities, colonoscopy and the multi-target stool DNA (mt-sDNA) test. A validated CRC microsimulation model was used to estimate the number of screening and follow-up tests for a cohort of 1 million average-risk individuals who underwent screening between ages 45 and 75. Component resources used for mt-sDNA, including waste products, energy, and transportation for colonoscopy and mt-sDNA, were collected from January 1, 2023, to January 1, 2024, and converted to carbon-equivalent emissions. Resources used for colonoscopy were captured from the literature. Resources devoted to screening colonoscopy were substantially (59%) higher than those to mt-sDNA, even when including follow-up colonoscopy. Of note, follow-up colonoscopy accounted for the majority (64%) of total emissions for the mt-sDNA screening strategy. Compared with colonoscopy screening, mt-sDNA substantially reduces the carbon emissions attributable to population-level CRC screening. Environmental impact should be included as a factor when choosing among guideline-recommended CRC screening strategies.

BACKGROUND/UNASSIGNED:The development of a prognostic model for patients with colorectal cancer (CRC) can facilitate the assessment of patient survival and the effectiveness of clinical treatments. A reasonable prognostic model can provide a basis for individualized treatment, prognostic risk stratification, and subsequent therapy for CRC patients. The aim of our study was to construct a prognostic model for patients with CRC using sequencing data derived from The Cancer Genome Atlas (TCGA) database. METHODS/UNASSIGNED:Sequencing data of paracancerous tissues (n=51) and CRC samples (n=647) were downloaded from the TCGA database. Least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were employed to identify prognostic factors. A restricted cubic spline (RCS) model was used to assess the nonlinear relationship between risk score and poor overall survival (OS). The Genomics of Drug Sensitivity in Cancer (GDSC) database was accessed to evaluate the correlation between the prognostic model's risk score and drug sensitivity. The single-sample gene set enrichment analysis (ssGSEA), estimate, and CIBERSORT algorithms were applied to quantify the association between prognostic genes and immune cell infiltration in CRC. RESULTS/UNASSIGNED:) (HR =1.55; 95% CI: 1.09-2.20; P=0.02) function as independent prognostic factors for CRC. Based on these six genes, the developed prognostic assessment model identified a strong association between high risk score and poor OS (HR =2.43; 95% CI: 1.67-3.53; P<0.001) in patients with CRC. Furthermore, the analysis revealed a nonlinear relationship (P<0.001) between continuous variation in risk score and the risk of poor OS. Additionally, specific genes included in the prognostic model were found to be strongly associated with cancer stem cell and immune cell infiltration in CRC. CONCLUSIONS/UNASSIGNED:We developed a prognostic risk model incorporating a six-gene panel for patients with CRC. Our analysis revealed a nonlinear relationship between this prognostic model and OS in patients with CRC. A high risk score was associated with poor prognosis, indicating that the adverse outcomes observed in patients with CRC may be influenced by cancer stem cell and immune cell infiltration. Our model provides a promising predictive method for the prognosis of CRC patients, but it still needs to be validated in a larger sample size.

BACKGROUND:Measurement of colorectal polyps is typically performed via visual estimation, which is prone to bias. Studies have evaluated the accuracy of visual estimation and utility of assistive tools, but results have been mixed. This study aims to clarify the accuracy of visual estimation as a measurement tool, and the benefits of artificial intelligence. METHODS:MEDLINE and Embase were searched through October 2024. Extraction and quality assessment were performed independently by two authors. The primary outcome was the pooled absolute mean difference in size between visual estimation and control. Secondary outcomes included subgroup analysis of expert vs trainee status, accuracy of artificial intelligence, study origin (East vs. West), comparator type, definition of accuracy, polyp size, direction of estimation, and image type. RESULTS:35 studies with 42,964 polyp measurements were included in our analysis. All studies were of high quality and there was no evidence of publication bias. The pooled absolute mean difference from comparator was 1.68mm (CI 1.21-2.15) with high variability explained by differences in the comparator, the direction of estimation, image type, and size of the polyp. Overall accuracy was 60% with high variability as well, with increased accuracy with video displayed over photos. Artificial intelligence improved accuracy with an odds ratio of 7.46. CONCLUSION/CONCLUSIONS:Visual estimation is an inaccurate and imprecise way to measure colorectal polyps. Further research is needed to determine the impact on clinical outcomes related to colorectal cancer. Investment in new technology to aid in polyp measurement is an important next step.

IMPORTANCE/UNASSIGNED:A substantial number of individuals worldwide experience long COVID, or post-COVID condition. Other postviral and autoimmune conditions have a female predominance, but whether the same is true for long COVID, especially within different subgroups, is uncertain. OBJECTIVE/UNASSIGNED:To evaluate sex differences in the risk of developing long COVID among adults with SARS-CoV-2 infection. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cohort study used data from the National Institutes of Health (NIH) Researching COVID to Enhance Recovery (RECOVER)-Adult cohort, which consists of individuals enrolled in and prospectively followed up at 83 sites in 33 US states plus Washington, DC, and Puerto Rico. Data were examined from all participants enrolled between October 29, 2021, and July 5, 2024, who had a qualifying study visit 6 months or more after their initial SARS-CoV-2 infection. EXPOSURE/UNASSIGNED:Self-reported sex (male, female) assigned at birth. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Development of long COVID, measured using a self-reported symptom-based questionnaire and scoring guideline at the first study visit that occurred at least 6 months after infection. Propensity score matching was used to estimate risk ratios (RRs) and risk differences (95% CIs). The full model included demographic and clinical characteristics and social determinants of health, and the reduced model included only age, race, and ethnicity. RESULTS/UNASSIGNED:Among 12 276 participants who had experienced SARS-CoV-2 infection (8969 [73%] female; mean [SD] age at infection, 46 [15] years), female sex was associated with higher risk of long COVID in the primary full (RR, 1.31; 95% CI, 1.06-1.62) and reduced (RR, 1.44; 95% CI, 1.17-1.77) models. This finding was observed across all age groups except 18 to 39 years (RR, 1.04; 95% CI, 0.72-1.49). Female sex was associated with significantly higher overall long COVID risk when the analysis was restricted to nonpregnant participants (RR, 1.50; 95%: CI, 1.27-1.77). Among participants aged 40 to 54 years, the risk ratio was 1.42 (95% CI, 0.99-2.03) in menopausal female participants and 1.45 (95% CI, 1.15-1.83) in nonmenopausal female participants compared with male participants. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this prospective cohort study of the NIH RECOVER-Adult cohort, female sex was associated with an increased risk of long COVID compared with male sex, and this association was age, pregnancy, and menopausal status dependent. These findings highlight the need to identify biological mechanisms contributing to sex specificity to facilitate risk stratification, targeted drug development, and improved management of long COVID.