Faculty Bibliography

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.

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.

OBJECTIVES/OBJECTIVE:To assess strategies for optimizing participation of underserved minorities in a blood-based early CRC detection test study (PREEMPT CRC; NCT04369053) at a hospital serving primarily Black patients. METHODS:Culturally sensitive, racially congruent research staff approached patients undergoing average-risk screening colonoscopy. Consent/study procedures were synchronized with clinical appointments. Enrolled and not-enrolled patient characteristics were compared. Recruitment was compared with other study sites. RESULTS:247/509 eligible participants enrolled; most identified as Black (88.7%). No baseline characteristics were associated with participation. Recruitment was high compared to other sites (11th centile). CONCLUSIONS:Recruitment barriers for Black individuals can be overcome when easy, culturally sensitive access is facilitated.

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.

BACKGROUND AND STUDY AIMS/UNASSIGNED:Gastroenterologists are prone to endoscopy-related musculoskeletal injuries (ERI). Current interventions lack real-time monitoring and feedback. ErgoGenius, a novel artificial intelligence computer-vision tool, addresses this gap by providing continuous posture assessment and feedback without wearable motion trackers. The aim of this study was to determine the feasibility of ErgoGenius, its accuracy compared with human appraisers, and its ability to detect abnormal posture. METHODS/UNASSIGNED:-test was used to compare REBA scores between bed positions. RESULTS/UNASSIGNED:= 0.006). CONCLUSIONS/UNASSIGNED:ErgoGenius was successfully deployed to detect abnormal postures related to changes in bed position and quantify ERI risk. It performed at par with human appraisers. This tool shows promise in enhancing ergonomic practices among gastroenterologists and trainees, potentially leading to better health outcomes and reduced injury.

BACKGROUND:Despite reports indicating that polyps proximal to the splenic flexure have higher rates of metachronous colorectal adenocarcinoma (CRC), the role of adenoma location on surveillance recommendations remains unclear. This study aimed to analyze the association between index polyp location and post-colonoscopy CRC among participants of the Minnesota Colon Cancer Control Study (MCCCS). METHODS:The MCCCS randomized 46,551 patients 50-80 years to usual care, annual, or biennial screening with fecal occult-blood testing (FOBT). Screening was performed between 1976-1992. Positive FOBT was followed by colonoscopy. We analyzed participants whose colonoscopy revealed at least one adenoma. Patients were divided into those with at least one lesion proximal to the splenic flexure and those without. RESULTS:Of 2,295 patients, 815 had proximal adenomas. The majority were men; mean age =62 years at randomization, and 69 years at index polyp. There was a high rate of advanced adenomas: 44% ≥1 polyp ≥1 cm, 35% with villous histology, and 5% high grade dysplasia. At 20 years, 87 patients had a CRC diagnosis, and the estimated cumulative incidence of CRC was 4.3%. Proximal adenomas had a higher risk of developing a post-colonoscopy CRC (SHR=1.63, 95% CI=1.05-2.53, P=0.03), which was attenuated after adjusting for polyp multiplicity in sensitivity analyses (SHR=1.56, 95% CI=0.96-2.53, P=0.07). CONCLUSION/CONCLUSIONS:Although patients with proximal adenomas were found to have higher hazards of post-colonoscopy CRC, adjusting for polyp multiplicity attenuated the strength of association. Further research is warranted to determine whether polyp location should be factored in the determination of appropriate surveillance intervals.

INTRODUCTION/BACKGROUND:Failure to document colonoscopy follow-up needs postpolypectomy can lead to delayed detection of colorectal cancer (CRC). Automating the update of a unified follow-up date in the electronic health record (EHR) may increase the number of patients with guideline-concordant CRC follow-up screening. METHODS:Prospective pre-post design study of an automated rules engine-based tool using colonoscopy pathology results to automate updates to documented CRC screening due dates was performed as an operational initiative, deployed enterprise-wide May 2023. Participants were aged 45-75 years who received a colonoscopy November 2022 to November 2023. Primary outcome measure is rate of updates to screening due dates and proportion with recommended follow-up < 10 years. Multivariable log-binomial regression was performed (relative risk, 95% confidence intervals). RESULTS:Study population included 9,824 standard care and 19,340 intervention patients. Patients had a mean age of 58.6 ± 8.6 years and were 53.4% female, 69.6% non-Hispanic White, 13.5% non-Hispanic Black, 6.5% Asian, and 4.6% Hispanic. Postintervention, 46.7% of follow-up recommendations were updated by the rules engine. The proportion of patients with a 10-year default follow-up frequency significantly decreased (88.7%-42.8%, P < 0.001). The mean follow-up frequency decreased by 1.9 years (9.3-7.4 years, P < 0.001). Overall likelihood of an updated follow-up date significantly increased (relative risk 5.62, 95% confidence intervals: 5.30-5.95, P < 0.001). DISCUSSION/CONCLUSIONS:An automated rules engine-based tool has the potential to increase the accuracy of colonoscopy follow-up dates recorded in patient EHR. The results emphasize the opportunity for more automated and integrated solutions for updating and maintaining EHR health maintenance activities.