Background: The effect of current infection of Helicobacter pylori on gastric cancer has rarely been studied in a large population. We investigated the association of current H. pylori infection and metabolic factors with gastric cancer in a large population.Methods: Persons who made their first visit to the National Cancer Center for a health examination, including endoscopy and H. pylori testing using gastric tissue between 2003 and 2013, were included. The association of H. pylori with gastric cancer was estimated using odds ratios (ORs) and 95% confidence intervals (CIs).Results: Among 35,519 people, 113 gastric cancer and 158 gastric dysplasia cases were detected. In the adjusted analysis, gastric cancer was associated with current H. pylori infection (OR, 2.39; 95% CI, 1.53–3.74), age (OR, 1.06; 95% CI 1.04–1.08), first‐degree relatives with gastric cancer (OR, 2.08; 95% CI, 1.30–3.32) and hyperglycaemia (OR, 1.66; 95% CI, 1.04–2.65), whereas it was inversely associated with high‐density lipoprotein (HDL) (OR, 0.49; 95% CI, 0.22–0.94). In the subanalysis, gastric cancer was associated with first‐degree relatives with gastric cancer (OR, 3.23; 95% CI, 1.39–7.50) in the absence of H. pylori, whereas it was associated with hyperglycaemia (OR, 1.98; 95% CI, 1.16–3.39) in the presence of H. pylori.Conclusions: Gastric cancer was associated with current H. pylori infection, hyperglycaemia, and low HDL levels in a large population.

Capsule endoscopy (CE) quality control requires an objective scoring system to evaluate the preparation of the small bowel (SB). We propose a deep learning algorithm to calculate SB cleansing scores and verify the algorithm’s performance. A 5-point scoring system based on clarity of mucosal visualization was used to develop the deep learning algorithm (400,000 frames; 280,000 for training and 120,000 for testing). External validation was performed using additional CE cases (n = 50), and average cleansing scores (1.0 to 5.0) calculated using the algorithm were compared to clinical grades (A to C) assigned by clinicians. Test results obtained using 120,000 frames exhibited 93% accuracy. The separate CE case exhibited substantial agreement between the deep learning algorithm scores and clinicians’ assessments (Cohen’s kappa: 0.672). In the external validation, the cleansing score decreased with worsening clinical grade (scores of 3.9, 3.2, and 2.5 for grades A, B, and C, respectively, p < 0.001). Receiver operating characteristic curve analysis revealed that a cleansing score cut-off of 2.95 indicated clinically adequate preparation. This algorithm provides an objective and automated cleansing score for evaluating SB preparation for CE. The results of this study will serve as clinical evidence supporting the practical use of deep learning algorithms for evaluating SB preparation quality.

Purpose: Dry eye syndrome (DES) is a common disease with an increasing occurrence. Although DES symptoms are considered mild, it can reduce quality of life for individuals. Many studies on DES have been conducted, but these focused on the use of electronic devices. Here, we investigate an association between DES and sleep disorders in the context of emerging health issues. Methods: Our data came from the National Health Insurance Service (NHIS) National Sample Cohort, which included 44,366 patients and was based on a 1:1 matching method (sleep disorder patients vs. patients without sleep disorders) during 2012–2015. Using survival analysis with a Cox proportional hazard model, we identified an association of sleep disorders with DES. Results: About 16.7% of all patients were diagnosed with DES, and prevalence was higher in patients with sleep disorders (sleep disorders: 19.82%, no sleep disorders: 13.67%). Survival analysis showed that sleep disorders positively correlated with DES diagnosis (Hazard Ratio (HR): 1.320, 95% Confidence Interval (CI): 1.261–1.382, p-value < 0.0001). Positive trends were enhanced in males, younger patients, lower economic levels, and with higher severity of comorbid. Conclusions: Our findings suggest that sleep disorder was positively associated with DES. This correlation can be helpful in effective management of both sleep disorders and DES in South Koreans.

The quality of bowel preparation is one of the quality indicators for colonoscopy. The aim of this study was to compare the efficacy of oral sulfate solution (OSS) and polyethylene glycol plus ascorbic acid (PEG-AA) for bowel preparation. The study involved 167 patients who underwent diagnostic colonoscopies. Inadequate bowel preparation was defined as any score of ≤1 in each colon section based on the Boston Bowel Preparation Scale. Multivariate logistic regression was used to compare the efficacy of OSS and PEG-AA. Subgroup analyses were performed based on patient characteristics. Overall, 106 (63.5%) patients received OSS, and 61 (36.5%) patients received PEG-AA. The rate of inadequate bowel preparation was 12.3% in patients receiving OSS and 32.8% in patients receiving PEG-AA (p=0.001). OSS (odds ratio [OR] = 0.26; p=0.003) and morning examination (OR=0.11; p=0.038) were significantly associated with efficient bowel preparation. The efficacy of OSS compared with PEG-AA was only significant in patients ≥50 years of age vs. <50 years of age (OR=0.13; p=0.001 vs. OR=0.96; p=0.959) and female vs. male patients (OR=0.06; p=0.002 vs. OR=0.58; p=0.339). OSS was significantly more efficient for bowel preparation than PEG-AA, especially in patients ≥50 years of age and female patients. Morning examination led to a good quality of bowel preparation, irrespective of the preparation regimen.

Gastrointestinal (GI) bleeding is one of the most common conditions among patients visiting emergency departments in Korea. GI bleeding is divided into upper and lower GI bleeding, according to the bleeding site. GI bleeding is also divided into overt and occult GI bleeding based on bleeding characteristics. In addition, obscure GI bleeding refers to recurrent or persistent GI bleeding from a source that cannot be identified after esophagogastroduodenoscopy or colonoscopy. The small intestine is the largest part of the alimentary tract. It extends from the pylorus to the cecum. The small intestine is difficult to access owing to its long length. Moreover, it is not fixed to the abdominal cavity. When hemorrhage occurs in the small intestine, the source cannot be found in many cases because of the characteristics of the small intestine. In practice, small-intestinal bleeding accounts for most of the obscure GI bleeding. Therefore, in this review, we introduce and describe systemic approaches and examination methods, including video capsule endoscopy and balloon enteroscopy, that can be performed in patients with suspected small bowel bleeding in clinical practice.

Capsule endoscopy (CE) is the only non-invasive diagnostic tool that enables the direct visualization of the gastrointestinal (GI) tract. Even though CE was initially developed for small-bowel investigation, its clinical application is expanding, and technological advances continue. The final iteration of CE will be a mouth to anus (M2A) capsule that investigates the entire GI tract by the ingestion of a single capsule. This narrative review describes the current developmental status of CE and discusses the possibility of realizing an M2A capsule and what needs to be overcome in the future.