Background and aims Artificial intelligence has been shown to increase adenoma detection rate (ADR) as the main surrogate outcome parameter of colonoscopy quality. To which extent this effect may be related to physician experience is not known. We performed a randomised trial with colonoscopists in their qualification period (AID-2) and compared these data with a previously published randomised trial in expert endoscopists (AID-1). Methods In this prospective, randomised controlled non-inferiority trial (AID-2), 10 non-expert endoscopists (<2000 colonoscopies) performed screening/surveillance/diagnostic colonoscopies in consecutive 40–80 year-old subjects using high-definition colonoscopy with or without a real-time deep-learning computer-aided detection (CADe) (GI Genius, Medtronic). The primary outcome was ADR in both groups with histology of resected lesions as reference. In a post-hoc analysis, data from this randomised controlled trial (RCT) were compared with data from the previous AID-1 RCT involving six experienced endoscopists in an otherwise similar setting. Results In 660 patients (62.3±10 years; men/women: 330/330) with equal distribution of study parameters, overall ADR was higher in the CADe than in the control group (53.3% vs 44.5%; relative risk (RR): 1.22; 95% CI: 1.04 to 1.40; p<0.01 for non-inferiority and p=0.02 for superiority). Similar increases were seen in adenoma numbers per colonoscopy and in small and distal lesions. No differences were observed with regards to detection of non-neoplastic lesions. When pooling these data with those from the AID-1 study, use of CADe (RR 1.29; 95% CI: 1.16 to 1.42) and colonoscopy indication, but not the level of examiner experience (RR 1.02; 95% CI: 0.89 to 1.16) were associated with ADR differences in a multivariate analysis. Conclusions In less experienced examiners, CADe assistance during colonoscopy increased ADR and a number of related polyp parameters as compared with the control group. Experience appears to play a minor role as determining factor for ADR. Trial registration number NCT:04260321.

Background. Sarcopenia is a complication and independent risk factor for mortality in patients with liver cirrhosis. To assess the prevalence and influence of sarcopenia on overall survival in a cohort of cirrhotic patients with hepatocellular carcinoma managed in a tertiary center. Abdominal computed tomography of 92 consecutive hepatocellular carcinoma cirrhotic patients, enrolled and followed from 2004 to 2014, were retrospectively studied with a software analyzing the cross-sectional areas of muscles at third lumbar vertebra level. Data was normalized for height, skeletal muscle index (SMI) calculated and presence of Sarcopenia measured. Sarcopenia was defined by SMI ≤ 41 cm2/m2 for women and ≤ 53 cm2/m2 for men with body mass index (BMI) ≥ 25, and ≤ 43 cm2/m2 for men and women with BMI < 25, respectively. Median age at diagnosis was 71.9 years (30.7-86.4) and BMI 24.7 (17.5-36.7), comparable in women 23.1, (17.5-36.7) and men 24.7 (18.4-36.7). A class of CHILD score and BCLC A prevailed (55.4% and 41.3%, respectively); metastatic disease was found in 12% of cases. Sarcopenia was present in 40.2% of cases, mostly in females (62.9%; p = 0.005). Mean overall survival was reduced in sarcopenic patients, 66 (95% CI 47 to 84) vs. 123 (95% CI 98 to 150) weeks (p = 0.001). At multivariate analysis, sarcopenia was a predictor of reduced overall survival, independent of age (p = 0.0027). This retrospective study shows high prevalence of sarcopenia among cirrhotic patients with hepatocellular carcinoma. Presence of sarcopenia was identified as independent predictor of reduced overall survival. As easily measurable by CT, sarcopenia should be determined for prognostic purposes in this patient population.

Objective Artificial intelligence (AI) may reduce underdiagnosed or overlooked upper GI (UGI) neoplastic and preneoplastic conditions, due to subtle appearance and low disease prevalence. Only disease-specific AI performances have been reported, generating uncertainty on its clinical value. Design We searched PubMed, Embase and Scopus until July 2020, for studies on the diagnostic performance of AI in detection and characterisation of UGI lesions. Primary outcomes were pooled diagnostic accuracy, sensitivity and specificity of AI. Secondary outcomes were pooled positive (PPV) and negative (NPV) predictive values. We calculated pooled proportion rates (%), designed summary receiving operating characteristic curves with respective area under the curves (AUCs) and performed metaregression and sensitivity analysis. Results Overall, 19 studies on detection of oesophageal squamous cell neoplasia (ESCN) or Barrett's esophagus-related neoplasia (BERN) or gastric adenocarcinoma (GCA) were included with 218, 445, 453 patients and 7976, 2340, 13 562 images, respectively. AI-sensitivity/specificity/PPV/NPV/positive likelihood ratio/negative likelihood ratio for UGI neoplasia detection were 90% (CI 85% to 94%)/89% (CI 85% to 92%)/87% (CI 83% to 91%)/91% (CI 87% to 94%)/8.2 (CI 5.7 to 11.7)/0.111 (CI 0.071 to 0.175), respectively, with an overall AUC of 0.95 (CI 0.93 to 0.97). No difference in AI performance across ESCN, BERN and GCA was found, AUC being 0.94 (CI 0.52 to 0.99), 0.96 (CI 0.95 to 0.98), 0.93 (CI 0.83 to 0.99), respectively. Overall, study quality was low, with high risk of selection bias. No significant publication bias was found. Conclusion We found a high overall AI accuracy for the diagnosis of any neoplastic lesion of the UGI tract that was independent of the underlying condition. This may be expected to substantially reduce the miss rate of precancerous lesions and early cancer when implemented in clinical practice.

Background: Sarcopenia has been associated with poor outcomes in patients with cirrhosis and solid tumours.Objective: Analyse the influence of sarcopenia on survival and treatment duration in patients with advanced hepatocellular carcinoma (HCC) treated with sorafenib.Methods: We conducted a multicentre, retrospective study on 96 patients with advanced HCC treated with sorafenib, all with available abdominal computed tomography (CT) scan within 30 days from treatment start. Anthropometric, laboratory, treatment and follow‐up data were collected. Sarcopenia was defined by reduced skeletal muscle index calculated from an L3 section CT image.Results: Sarcopenia was present in 49% of patients. Patients were divided into two groups according to sarcopenia: age was significantly higher in the sarcopenic group (SG) (66 years (31–87) versus 72 years (30–84), p = 0.04], with no difference in other baseline characteristics. The SG showed shorter overall survival (OS) (39 (95% confidence interval (CI) 26–50) versus 61 (95% CI 47–77) weeks (p = 0,01)) and shorter time on treatment (12.3 (95% CI 8–19) versus 25.9 (95% CI 15–33) weeks (p = 0.0044)). At multivariate analysis, sarcopenia was independently associated to reduced OS (p = 0.03) and reduced time on treatment (p = 0.001).Conclusion: Sarcopenia is present in almost half of patients with advanced HCC, and is associated with reduced survival and reduced duration of oral chemotherapy.

Computer-aided diagnosis (CADx) allows prediction of polyp histology during colonoscopy, which may reduce unnecessary removal of nonneoplastic polyps. However, the potential benefits and harms of CADx are still unclear. To quantify the benefit and harm of using CADx in colonoscopy for the optical diagnosis of small (≤5-mm) rectosigmoid polyps. Medline, Embase, and Scopus were searched for articles published before 22 December 2023. Histologically verified diagnostic accuracy studies that evaluated the real-time performance of physicians in predicting neoplastic change of small rectosigmoid polyps without or with CADx assistance during colonoscopy. The clinical benefit and harm were estimated on the basis of accuracy values of the endoscopist before and after CADx assistance. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. The outcome measure for benefit was the proportion of polyps predicted to be nonneoplastic that would avoid removal with the use of CADx. The outcome measure for harm was the proportion of neoplastic polyps that would be not resected and left in situ due to an incorrect diagnosis with the use of CADx. Histology served as the reference standard for both outcomes. Ten studies, including 3620 patients with 4103 small rectosigmoid polyps, were analyzed. The studies that assessed the performance of CADx alone (9 studies; 3237 polyps) showed a sensitivity of 87.3% (95% CI, 79.2% to 92.5%) and specificity of 88.9% (CI, 81.7% to 93.5%) in predicting neoplastic change. In the studies that compared histology prediction performance before versus after CADx assistance (4 studies; 2503 polyps), there was no difference in the proportion of polyps predicted to be nonneoplastic that would avoid removal (55.4% vs. 58.4%; risk ratio [RR], 1.06 [CI, 0.96 to 1.17]; moderate-certainty evidence) or in the proportion of neoplastic polyps that would be erroneously left in situ (8.2% vs. 7.5%; RR, 0.95 [CI, 0.69 to 1.33]; moderate-certainty evidence). The application of optical diagnosis was only simulated, potentially altering the decision-making process of the operator. Computer-aided diagnosis provided no incremental benefit or harm in the management of small rectosigmoid polyps during colonoscopy. European Commission. (PROSPERO: CRD42023402197).