Establishment and Verification of Scoring System for Colorectal Adenoma Recurrence.

OBJECTIVE: The purpose of this study was to establish and verify a risk-scoring system for colorectal adenoma recurrence. METHODS: A total of 359 patients with colorectal adenoma who underwent polypectomy from October 2017 to December 2018 were included in this retrospective study. Information including taking traditional Chinese medicine, demographic characteristics, adenoma characteristics were collected. The patients will review the colonoscopy one year after surgery. The patients were divided into a modeling cohort (216 cases) and a model validation cohort (143 cases) according to the ratio of 6:4. Modeling and model verification were performed by logistic regression, ROC curve, nomogram (calibration chart) and other methods. RESULTS: After adjusting for confounding factors by logistic regression, it was found that taking Chinese medicine, the number, size, site, pathological type and morphology of adenoma were independent influencing factors for the recurrence of colorectal adenoma. The area under the ROC curve (AUC) in the model validation cohort of established risk scoring system was 0.771 (95% CI: 0.694-0.847), indicating that there was good consistency. CONCLUSION: The established risk prediction model of colorectal adenoma recurrence and its risk scoring system performed well and had high predictive value.

Association between anxiety, depression, and bowel air bubbles at colonoscopy: a prospective observational study.

BACKGROUND: Psychological illness could affect the gut transmission. However, few studies have reported on the association between anxiety and depression and bowel preparation failure at colonoscopy. Bowel air bubbles have become an indispensable index to evaluate intestinal cleanliness. The aim of the present study was to investigate whether anxiety and depression are associated with the bowel air bubbles. METHODS: The present study was a prospective observational study of patients who underwent colonoscopy in our hospital. Participants received the standard bowel preparation guidance, including split-dose polyethylene glycol and a low-fiber diet 1 day before colonoscopy. The primary outcome was degree of the bowel air bubble, measured by bubble scores. Univariate and multivariate logistic regression analyses were used to verify the association between anxiety and depression and bowel air bubbles. RESULTS: A total of 304 patients were enrolled in the present study between July 2019 and January 2020; 302 of these had complete data. The mean age was 48.74±11.73 years. Fifty six of 302 patients had anxiety. Age between 45 and 60 years [odds ratio (OR): 2.09, 95% confidence interval (CI): 1.13-3.87], age >60 years (OR: 1.99, 95% CI: 1.01-3.95), and anxiety (OR: 3.85, 95% CI: 2.12-6.97) were identified as risk factors for bowel air bubbles. A bachelor degree and above (OR: 0.27, 95% CI: 0.07-0.97) were identified as protective factors for bowel air bubbles. CONCLUSIONS: Anxiety is an independent risk factor of bowel air bubbles in colonoscopy diagnosis. Medical professionals should be mindful of this prior to performing colonoscopy.

Artificial intelligence-assisted detection and classification of colorectal polyps under colonoscopy: a systematic review and meta-analysis.

BACKGROUND: Artificial intelligence (AI) is used to solve the problem of missed diagnosis of polyps in colonoscopy, which has been proved to improve the detection rate of adenomas. The aim of this review was to evaluate the diagnostic performance of AI-assisted detection and classification of polyps in colonoscopy. METHODS: The literature search was undertaken on 4 electronic databases (PubMed, Web of Science, Embase, and Cochrane Library). The inclusion criteria were as follows: studies reporting AI-assisted detection and classification of polyps; studies containing patients, images, or videos receiving AI-assisted diagnosis; studies which included AI-assisted diagnosis and reported classification based on histopathology; and studies providing accurate diagnostic data. Non-English language studies, case-reports, reviews, meeting abstracts and so on were excluded. The Quality Assessment of Diagnostic Accuracy Studies-2 scale was used to evaluate the quality of literature and the Stata 13.0 software was used to perform meta-analysis. RESULTS: Twenty-six articles were included with all of medium quality. Meta-analysis showed none of literature had any obvious publication bias. The application of AI in detection of colorectal polyps achieved a sensitivity of 0.95 [95% confidence interval (CI): 0.89-0.98] and an area under the curve (AUC) of 0.79 (95% CI: 0.79-0.82). In the AI-assisted classification, the sensitivity was 0.92 (95% CI: 0.88-0.95) with a specificity of 0.82 (95% CI: 0.71-0.89) and an AUC of 0.94 (95% CI: 0.92-0.96). For the classification of diminutive polyps, the AI-assisted technique yielded a sensitivity of 0.95 (95% CI: 0.94-0.97), a specificity of 0.88 (95% CI: 0.74-0.95), and an AUC of 0.97 (95% CI: 0.95-0.98). For AI-assisted classification under magnifying endoscopy, the sensitivity was 0.954 (95% CI: 0.92-0.96) with a specificity of 0.95 (95% CI: 0.80-0.99) and an AUC of 0.97 (95% CI: 0.95-0.98). DISCUSSION: The AI-assisted technique demonstrates impressive accuracy for the detection and characterization of colorectal polyps and can be expected to be a novel auxiliary diagnosis method. Our study has inevitable limitations including heterogeneity due to different AI systems and the inability to further analyze the specificity and sensitivity of AI for different types of endoscopes.

Prognostic value of transforming growth factor-beta in patients with colorectal cancer who undergo surgery: a meta-analysis.

BACKGROUND: Transforming growth factor-beta (TGF-ß) is associated with a higher incidence of distant metastasis and decreased survival. Whether TGF-ß can be used as a prognostic indicator of colorectal cancer (CRC) remains controversial. METHODS: The Medline, EMBASE and Cochrane databases were searched from their inception to March 2016. The studies that focused on TGF-ß as a prognostic factor in patients with CRC were included in this analysis. Overall survival (OS) and disease-free survival (DFS) were analysed separately. A meta-analysis was performed, and hazard ratios (HR) with 95% confidence intervals (CI) were calculated. RESULTS: Twelve studies were included in the analysis, of which 8 were used for OS and 7 for DFS. In all, 1622 patients with CRC undergoing surgery were included. Combined HRs suggested that high expression of TGF-ß had a favourable impact on OS (HR = 1.68, 95% CI: 1.10-2.59) and DFS (HR = 1.11, 95% CI: 1.03-1.19) in CRC patients. For OS, the combined HRs of Asian studies and Western studies were 1.50 (95% CI: 0.61-3.68) and 1.80 (95% CI: 1.33-2.45), respectively. For DFS, the combined HRs of Asian studies and Western studies were 1.42 (95% CI: 0.61-3.31) and 1.11 (95% CI: 1.03-1.20), respectively. CONCLUSIONS: This meta-analysis demonstrates that TGF-ß can be used as a prognostic biomarker for CRC patients undergoing surgery, especially for CRC patients from Western countries.