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Background and Aim: Adenoma detection rate (ADR) is an important quality metric in colonoscopy. However, there is conflicting evidence around factors that influence ADR. This study aims to investigate the effect of time of day and endoscopist background on ADR and sessile serrated adenoma/polyp detection rate (SSA/P‐DR) for screening colonoscopies. Methods: Consecutive patients undergoing colonoscopy in 2016 were retrospectively evaluated. Primary outcome was the effect of time of day and endoscopist specialty on screening ADR. Secondary outcomes included evaluation of the same factors on SSA/P‐DR and other metrics and collinearity of ADR and SSA/P‐DR. Linear regression models were used for association between ADR, time of day, and endoscopist background. Bowel preparation, endoscopist, session, patient age, and gender were adjusted for. Linear regression model was also used for comparing ADR and SSA/P‐DR. Chi‐square was used for difference of proportions. Results: Two thousand six hundred fifty‐seven colonoscopies, of which 558 were screening colonoscopies, were performed. The adjusted mean ADR (screening) was 36.8% in the morning compared with 30.5% in the afternoon (P < 0.0001) and was 36.8% for gastroenterologists compared with 30.4% for surgeons (P < 0.0001). For every 1‐h delay in commencing the procedure, there was a reduction in mean ADR by 3.4%. Using a linear regression model, a statistically significant positive association was found between ADR and SSA/P‐DR (P < 0.0001). Conclusions: Morning and afternoon sessions and gastroenterologists and surgeons achieved the minimum standards recommended for ADR. Afternoon lists and surgeons were associated with a lower ADR compared with morning and gastroenterologists, respectively. Additionally, SSA/P‐DR showed collinearity with ADR. [ABSTRACT FROM AUTHOR]

Background and Aims: Endoscopy guidelines recommend adhering to policies such as resect and discard only if the optical biopsy is accurate. However, accuracy in predicting histology can vary greatly. Computer-aided diagnosis (CAD) for characterization of colorectal lesions may help with this issue. In this study, CAD software developed at the University of Adelaide (Australia) that includes serrated polyp differentiation was validated with Japanese images on narrow-band imaging (NBI) and blue-laser imaging (BLI)., Methods: CAD software developed using machine learning and densely connected convolutional neural networks was modeled with NBI colorectal lesion images (Olympus 190 series - Australia) and validated for NBI (Olympus 290 series) and BLI (Fujifilm 700 series) with Japanese datasets. All images were correlated with histology according to the modified Sano classification. The CAD software was trained with Australian NBI images and tested with separate sets of images from Australia (NBI) and Japan (NBI and BLI)., Results: An Australian dataset of 1235 polyp images was used as training, testing, and internal validation sets. A Japanese dataset of 20 polyp images on NBI and 49 polyp images on BLI was used as external validation sets. The CAD software had a mean area under the curve (AUC) of 94.3% for the internal set and 84.5% and 90.3% for the external sets (NBI and BLI, respectively)., Conclusions: The CAD achieved AUCs comparable with experts and similar results with NBI and BLI. Accurate CAD prediction was achievable, even when the predicted endoscopy imaging technology was not part of the training set., (Copyright © 2020 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.)

Current data shows there are differences in factors associated with colorectal neoplasia based on geographical location and cultural settings. There are no studies focusing on the association between environmental factors and colorectal polyps in Australia. The aim of this study was to prospectively evaluate the association of various factors with different colorectal neoplasia histology. We utilized a simplified one-page questionnaire for patients undergoing colonoscopy for information on age; gender; comorbidities; family history of colorectal cancer; physical activity; smoking; diet; alcohol intake; and body mass index. Factors were then evaluated for association with the presence of: (1) neoplastic lesions; (2) conventional adenomas; (3) neoplastic serrated polyps; (4) any lesions (past and present); and (5) hyperplastic polyps. 291 procedures and 260 patients were included. Factors with a p-value < 0.2 in a univariate regression were included in an initial multivariable regression model. Backwards elimination was then performed, removing one predictor at a time until only significant predictors remained. In the final multivariable model, age≥65, male gender, type-2 diabetes mellitus, active smoking and family history of colorectal cancer were found to be statistically significant predictors for the presence of colorectal neoplasia. However, the significant predictors found for conventional adenomas (older age, male gender and smoking) were different from the significant predictors for neoplastic serrated polyps (type-2 diabetes mellitus and family history of colorectal cancer). Older age, male gender, type-2 diabetes mellitus, and smoking were significantly associated with the presence of colorectal neoplasia. The factors associated with conventional adenomas differed from those associated with neoplastic serrated polyps., Competing Interests: All authors declare no conflicts of interest for this paper.

Background and Aim: Adenoma detection rate (ADR) is an important quality metric in colonoscopy. However, there is conflicting evidence around factors that influence ADR. This study aims to investigate the effect of time of day and endoscopist background on ADR and sessile serrated adenoma/polyp detection rate (SSA/P-DR) for screening colonoscopies., Methods: Consecutive patients undergoing colonoscopy in 2016 were retrospectively evaluated. Primary outcome was the effect of time of day and endoscopist specialty on screening ADR. Secondary outcomes included evaluation of the same factors on SSA/P-DR and other metrics and collinearity of ADR and SSA/P-DR. Linear regression models were used for association between ADR, time of day, and endoscopist background. Bowel preparation, endoscopist, session, patient age, and gender were adjusted for. Linear regression model was also used for comparing ADR and SSA/P-DR. Chi-square was used for difference of proportions., Results: Two thousand six hundred fifty-seven colonoscopies, of which 558 were screening colonoscopies, were performed. The adjusted mean ADR (screening) was 36.8% in the morning compared with 30.5% in the afternoon (P < 0.0001) and was 36.8% for gastroenterologists compared with 30.4% for surgeons (P < 0.0001). For every 1-h delay in commencing the procedure, there was a reduction in mean ADR by 3.4%. Using a linear regression model, a statistically significant positive association was found between ADR and SSA/P-DR (P < 0.0001)., Conclusions: Morning and afternoon sessions and gastroenterologists and surgeons achieved the minimum standards recommended for ADR. Afternoon lists and surgeons were associated with a lower ADR compared with morning and gastroenterologists, respectively. Additionally, SSA/P-DR showed collinearity with ADR., (© 2018 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.)