How to increase proximal adenoma detection rate: a meta-analysis comparing water exchange, water immersion and air/CO2 insufflation methods for colonoscopy

Clinical effects of left-colon water exchange colonoscopy vs conventional air-insufflation colonoscopy

BACKGROUND

The left colon is difficult to detect via conventional air-injection colonoscopy, and patients may have obvious discomfort during intubation. Studies have reported that water exchange technology can significantly reduce the pain and discomfort of patients during endoscopy. However, there are still few studies comparing the clinical effects of left-colon water exchange (WE) colonoscopy with conventional air-insufflation (AI) colonoscopy.

AIM

To compare the clinical effects of left-colon WE colonoscopy and conventional AI colonoscopy.

METHODS

Consecutive patients who underwent colonoscopy at our hospital from June 2020 to December 2020 were collected and randomly divided into either a left-colon WE colonoscopy group or a conventional AI colonoscopy group at a ratio of 1:1. The success rate of ileocecal insertion, time to cecal insertion, time to colonoscope withdrawal, adenoma detection rate (ADR), visual analogue scale (VAS) score of pain, and rate of complications were recorded in the two groups.

RESULTS

A total of 276 patients were included according to the inclusion and exclusion criteria, including 139 cases in the left-colon WE colonoscopy group and 137 cases in the conventional AI colonoscopy group. There were no statistical differences in the success rate of ileocecal insertion, time to colonoscope withdrawal, or adenoma detection rate between the two groups (P > 0.05). However, time to cecal insertion was significantly shorter (4.6 min vs 5.3 min, P < 0.05) and VAS score was significantly lower (2.7 vs 3.1, P < 0.05) in the left-colon WE colonoscopy group than in the conventional AI colonoscopy group. No examination-related complications such as perforation occurred in either group.

CONCLUSION

Compared with conventional AI colonoscopy, left-colon WE colonoscopy significantly shortens the time to ileocecal insertion and reduces the pain and discomfort of the patients.

Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis

Background and study aims  With the advent of deep neural networks (DNN) learning, the field of artificial intelligence (AI) is rapidly evolving. Recent randomized controlled trials (RCT) have investigated the influence of integrating AI in colonoscopy and its impact on adenoma detection rates (ADRs) and polyp detection rates (PDRs). We performed a systematic review and meta-analysis to reliably assess if the impact is statistically significant enough to warrant the adoption of AI -assisted colonoscopy (AIAC) in clinical practice. Methods  We conducted a comprehensive search of multiple electronic databases and conference proceedings to identify RCTs that compared outcomes between AIAC and conventional colonoscopy (CC). The primary outcome was ADR. The secondary outcomes were PDR and total withdrawal time (WT). Results  Six RCTs (comparing AIAC vs CC) with 5058 individuals undergoing average-risk screening colonoscopy were included in the meta-analysis. ADR was significantly higher with AIAC compared to CC (33.7 % versus 22.9 %; odds ratio (OR) 1.76, 95 % confidence interval (CI) 1.55-2.00; I ²  = 28 %). Similarly, PDR was significantly higher with AIAC (45.6 % versus 30.6 %; OR 1.90, 95 %CI, 1.68-2.15, I ²  = 0 %). The overall WT was higher for AIAC compared to CC (mean difference [MD] 0.46 (0.00-0.92) minutes, I ²  = 94 %). Conclusions  There is an increase in adenoma and polyp detection with the utilization of AIAC.

Efficacy of Endocuff Vision compared to first-generation Endocuff in adenoma detection rate and polyp detection rate in high-definition colonoscopy: a systematic review and network meta-analysis

Background and study aims  Recently, the newer Endocuff Vision (ECV) has been evaluated for improving colonoscopy outcome metrics such as adenoma detection rate (ADR) and polyp detection rate (PDR). Due to lack of direct comparative studies between ECV and original Endocuff (ECU), we performed a systematic review and network meta-analysis to evaluate these outcomes. Methods  The following databases were searched: PubMed, Embase, Cochrane, and Web of Sciences to include randomized controlled trials (RCTs) comparing ECV or ECU colonoscopy to high-definition (HD) colonoscopy. Direct as well as network meta-analyses comparing ADR and PDR were performed using a random effects model. Relative-risk (RR) with 95 % confidence interval (CI) was calculated. Results  A total of 12 RCTs with 8638 patients were included in the final analysis. On direct meta-analysis, ECV did not demonstrate statistically improved ADR compared to HD colonoscopy (RR: 1.12, 95 % CI 0.99-1.27). A clinically and statistically improved PDR was noted for ECV compared to HD (RR: 1.15, 95 % CI 1.03-1.28) and ECU compared to HD (RR: 1.26, 95 % CI 1.09-1.46) as well as improved ADR (RR: 1.22, 95 % CI 1.05-1.43) was observed for ECU colonoscopy when compared to HD colonoscopy. These results were also consistent on network meta-analysis. Lower overall complication rates (RR: 0.14, 95 % CI 0.02-0.84) and particularly lacerations/erosions (RR: 0.11, 95 % CI 0.02-0.70) were noted with ECV compared to ECU colonoscopy. Conclusions  Although safe, the newer ECV did not significantly improve ADR compared to ECU and HD colonoscopy. Further device modification is needed to increase the overall ADR and PDR.