Prevalence of missed lesions in patients with inadequate bowel preparation through a very early repeat colonoscopy

The prospective validation of a scoring system to assess mucosal cleanliness during EGD

BACKGROUND AND AIMS

Cleanliness of the mucosa of the upper GI (UGI) tract is critical for performing a high-quality EGD. The aim of this study was to validate a recently developed UGI cleanliness scale (the Polprep: Effective Assessment of Cleanliness in Esophagogastroduodenoscopy [PEACE] system) in the detection of clinically significant lesions (CSLs) in the UGI tract.

METHODS

Patients who underwent a complete diagnostic EGD were prospectively enrolled from August 2021 to October 2022. The UGI tract (esophagus, stomach, and duodenum) cleanliness was scored from 0 to 3 for each segment. The primary outcomes were the detection of CSLs and PEACE scores.

RESULTS

Of 995 patients enrolled from 5 centers, adequate cleanliness (AQ; all scores ≥2) was found in 929 patients. In multivariate regression analysis, AQ was associated with the number of diagnosed CSLs (odds ratio [OR], 1.78; 95% confidence interval [CI], 1.06-3.01; P = .03). Other factors related to CSL detection were duration of EGD (OR, 1.29, 95% CI, 1.23-1.35, P < .001), male sex (OR, 1.33, 95% CI, 1.04-1.71; P = .025), and EGD indication (dyspepsia, alarm symptoms, gastritis surveillance, other indications vs GERD) (OR, 0.43 [95% CI, 0.31-0.6, P < .001], OR, 0.44 [95% CI, 0.28-0.67, P < .001], OR, 0.44 [95% CI, 0.25-0.76; P = .004], and OR, 0.44 [95% CI, 0.31-0.62; P < .001], respectively). Twenty-seven patients were diagnosed with UGI neoplasia, all in patients with adequate cleanliness of the UGI tract.

CONCLUSIONS

Adequate cleanliness of the UGI tract as assessed with the PEACE system was associated with a significantly higher detection rate of CSLs during EGD. The relationship of this scale with UGI neoplasia detection warrants further investigation.

The Machine Learning Model for Predicting Inadequate Bowel Preparation Before Colonoscopy: A Multicenter Prospective Study

INTRODUCTION

Colonoscopy is a critical diagnostic tool for colorectal diseases; however, its effectiveness depends on adequate bowel preparation (BP). This study aimed to develop a machine learning predictive model based on Chinese adults for inadequate BP.

METHODS

A multicenter prospective study was conducted on adult outpatients undergoing colonoscopy from January 2021 to May 2023. Data on patient characteristics, comorbidities, medication use, and BP quality were collected. Logistic regression and 4 machine learning models (support vector machines, decision trees, extreme gradient boosting, and bidirectional projection network) were used to identify risk factors and predict inadequate BP.

RESULTS

Of 3,217 patients, 21.14% had inadequate BP. The decision trees model demonstrated the best predictive capacity with an area under the receiver operating characteristic curve of 0.80 in the validation cohort. The risk factors at the nodes included body mass index, education grade, use of simethicone, diabetes, age, history of inadequate BP, and longer interval.

DISCUSSION

The decision trees model we created and the identified risk factors can be used to identify patients at higher risk of inadequate BP before colonoscopy, for whom more polyethylene glycol or auxiliary medication should be used.

Optimization of colonoscopy quality: Comprehensive review of the literature and future perspectives

Colonoscopy is crucial in preventing colorectal cancer (CRC) and reducing associated mortality. This comprehensive review examines the importance of high-quality colonoscopy and associated quality indicators, including bowel preparation, cecal intubation rate, withdrawal time, adenoma detection rate (ADR), complete resection, specimen retrieval, complication rates, and patient satisfaction, while also discussing other ADR-related metrics. Additionally, the review draws attention to often overlooked quality aspects, such as nonpolypoid lesion detection, as well as insertion and withdrawal skills. Moreover, it explores the potential of artificial intelligence in enhancing colonoscopy quality and highlights specific considerations for organized screening programs. The review also emphasizes the implications of organized screening programs and the need for continuous quality improvement. A high-quality colonoscopy is crucial for preventing postcolonoscopy CRC- and CRC-related deaths. Health-care professionals must develop a thorough understanding of colonoscopy quality components, including technical quality, patient safety, and patient experience. By prioritizing ongoing evaluation and refinement of these quality indicators, health-care providers can contribute to improved patient outcomes and develop more effective CRC screening programs.

Impact of WeChat guidance on bowel preparation for colonoscopy: a quasi-experiment study

Colonoscopy is a standard procedure for screening, monitoring, and treating colorectal lesions. To explore the impact of WeChat guidance on bowel preparation before colonoscopy. This quasi-experiment study included patients who underwent colonoscopy at Qingdao Endoscopy Center between March 2016 and September 2016. The primary outcome was bowel preparation quality (Ottawa score), the secondary outcomes were intubation time, withdrawal time, adenoma detection rate (ADR), and adverse reactions. Finally, 588 patients were included and divided into the WeChat guide (n = 295) and the non-WeChat guide (n = 293) groups, they were comparable in baseline characteristics. The Ottawa score (1.59 ± 1.07 vs. 6.62 ± 3.07, P < 0.001), intubation time (6.47 ± 1.81 vs. 11.61 ± 3.34, P < 0.001), withdrawal time (13.15 ± 3.93 vs. 14.99 ± 6.77, P < 0.001), and occurrence rate of adverse reactions (2.0% vs. 5.5%, P = 0.029) were significantly lower in the WeChat guide group than those in the non-WeChat guide group. ADR was significantly higher in the WeChat guide than that in the non-WeChat guide group (1.47 ± 2.30 vs. 0.84 ± 1.66, P < 0.001). WeChat guidance might improve the quality of bowel preparation and adenoma detection rate, shorten the time of colonoscopy, and reduce adverse reactions in bowel preparation.