Artificial intelligence-based model to classify cardiac functions from chest radiographs: a multi-institutional, retrospective model development and validation study.

BACKGROUND: Chest radiography is a common and widely available examination. Although cardiovascular structures-such as cardiac shadows and vessels-are visible on chest radiographs, the ability of these radiographs to estimate cardiac function and valvular disease is poorly understood. Using datasets from multiple institutions, we aimed to develop and validate a deep-learning model to simultaneously detect valvular disease and cardiac functions from chest radiographs. METHODS: In this model development and validation study, we trained, validated, and externally tested a deep learning-based model to classify left ventricular ejection fraction, tricuspid regurgitant velocity, mitral regurgitation, aortic stenosis, aortic regurgitation, mitral stenosis, tricuspid regurgitation, pulmonary regurgitation, and inferior vena cava dilation from chest radiographs. The chest radiographs and associated echocardiograms were collected from four institutions between April 1, 2013, and Dec 31, 2021: we used data from three sites (Osaka Metropolitan University Hospital, Osaka, Japan; Habikino Medical Center, Habikino, Japan; and Morimoto Hospital, Osaka, Japan) for training, validation, and internal testing, and data from one site (Kashiwara Municipal Hospital, Kashiwara, Japan) for external testing. We evaluated the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. FINDINGS: We included 22 551 radiographs associated with 22 551 echocardiograms obtained from 16 946 patients. The external test dataset featured 3311 radiographs from 2617 patients with a mean age of 72 years [SD 15], of whom 49·8% were male and 50·2% were female. The AUCs, accuracy, sensitivity, and specificity for this dataset were 0·92 (95% CI 0·90-0·95), 86% (85-87), 82% (75-87), and 86% (85-88) for classifying the left ventricular ejection fraction at a 40% cutoff, 0·85 (0·83-0·87), 75% (73-76), 83% (80-87), and 73% (71-75) for classifying the tricuspid regurgitant velocity at a 2·8 m/s cutoff, 0·89 (0·86-0·92), 85% (84-86), 82% (76-87), and 85% (84-86) for classifying mitral regurgitation at the none-mild versus moderate-severe cutoff, 0·83 (0·78-0·88), 73% (71-74), 79% (69-87), and 72% (71-74) for classifying aortic stenosis, 0·83 (0·79-0·87), 68% (67-70), 88% (81-92), and 67% (66-69) for classifying aortic regurgitation, 0·86 (0·67-1·00), 90% (89-91), 83% (36-100), and 90% (89-91) for classifying mitral stenosis, 0·92 (0·89-0·94), 83% (82-85), 87% (83-91), and 83% (82-84) for classifying tricuspid regurgitation, 0·86 (0·82-0·90), 69% (68-71), 91% (84-95), and 68% (67-70) for classifying pulmonary regurgitation, and 0·85 (0·81-0·89), 86% (85-88), 73% (65-81), and 87% (86-88) for classifying inferior vena cava dilation. INTERPRETATION: The deep learning-based model can accurately classify cardiac functions and valvular heart diseases using information from digital chest radiographs. This model can classify values typically obtained from echocardiography in a fraction of the time, with low system requirements and the potential to be continuously available in areas where echocardiography specialists are scarce or absent. FUNDING: None.

Deep learning-based screening tool for rotator cuff tears on shoulder radiography.

BACKGROUND: Early diagnosis of rotator cuff tears is essential for appropriate and timely treatment. Although radiography is the most used technique in clinical practice, it is difficult to accurately rule out rotator cuff tears as an initial imaging diagnostic modality. Deep learning-based artificial intelligence has recently been applied in medicine, especially diagnostic imaging. This study aimed to develop a deep learning algorithm as a screening tool for rotator cuff tears based on radiography. METHODS: We used 2803 shoulder radiographs of the true anteroposterior view to develop the deep learning algorithm. Radiographs were labeled 0 and 1 as intact or low-grade partial-thickness rotator cuff tears and high-grade partial or full-thickness rotator cuff tears, respectively. The diagnosis of rotator cuff tears was determined based on arthroscopic findings. The diagnostic performance of the deep learning algorithm was assessed by calculating the area under the curve (AUC), sensitivity, negative predictive value (NPV), and negative likelihood ratio (LR-) of test datasets with a cutoff value of expected high sensitivity determination based on validation datasets. Furthermore, the diagnostic performance for each rotator cuff tear size was evaluated. RESULTS: The AUC, sensitivity, NPV, and LR- with expected high sensitivity determination were 0.82, 84/92 (91.3%), 102/110 (92.7%), and 0.16, respectively. The sensitivity, NPV, and LR- for full-thickness rotator cuff tears were 69/73 (94.5%), 102/106 (96.2%), and 0.10, respectively, while the diagnostic performance for partial-thickness rotator cuff tears was low at 15/19 (78.9%), NPV of 102/106 (96.2%) and LR- of 0.39. CONCLUSIONS: Our algorithm had a high diagnostic performance for full-thickness rotator cuff tears. The deep learning algorithm based on shoulder radiography helps screen rotator cuff tears by setting an appropriate cutoff value. LEVEL OF EVIDENCE: Level III: Diagnostic Study.

Deep Learning Model Based on Contrast-Enhanced Computed Tomography Imaging to Predict Postoperative Early Recurrence after the Curative Resection of a Solitary Hepatocellular Carcinoma.

We aimed to develop the deep learning (DL) predictive model for postoperative early recurrence (within 2 years) of hepatocellular carcinoma (HCC) based on contrast-enhanced computed tomography (CECT) imaging. This study included 543 patients who underwent initial hepatectomy for HCC and were randomly classified into training, validation, and test datasets at a ratio of 8:1:1. Several clinical variables and arterial CECT images were used to create predictive models for early recurrence. Artificial intelligence models were implemented using convolutional neural networks and multilayer perceptron as a classifier. Furthermore, the Youden index was used to discriminate between high- and low-risk groups. The importance values of each explanatory variable for early recurrence were calculated using permutation importance. The DL predictive model for postoperative early recurrence was developed with the area under the curve values of 0.71 (test datasets) and 0.73 (validation datasets). Postoperative early recurrence incidences in the high- and low-risk groups were 73% and 30%, respectively (p = 0.0057). Permutation importance demonstrated that among the explanatory variables, the variable with the highest importance value was CECT imaging analysis. We developed a DL model to predict postoperative early HCC recurrence. DL-based analysis is effective for determining the treatment strategies in patients with HCC.

Deep Learning-Based Time-to-Death Prediction Model for COVID-19 Patients Using Clinical Data and Chest Radiographs.

Accurate estimation of mortality and time to death at admission for COVID-19 patients is important and several deep learning models have been created for this task. However, there are currently no prognostic models which use end-to-end deep learning to predict time to event for admitted COVID-19 patients using chest radiographs and clinical data. We retrospectively implemented a new artificial intelligence model combining DeepSurv (a multiple-perceptron implementation of the Cox proportional hazards model) and a convolutional neural network (CNN) using 1356 COVID-19 inpatients. For comparison, we also prepared DeepSurv only with clinical data, DeepSurv only with images (CNNSurv), and Cox proportional hazards models. Clinical data and chest radiographs at admission were used to estimate patient outcome (death or discharge) and duration to the outcome. The Harrel's concordance index (c-index) of the DeepSurv with CNN model was 0.82 (0.75-0.88) and this was significantly higher than the DeepSurv only with clinical data model (c-index = 0.77 (0.69-0.84), p = 0.011), CNNSurv (c-index = 0.70 (0.63-0.79), p = 0.001), and the Cox proportional hazards model (c-index = 0.71 (0.63-0.79), p = 0.001). These results suggest that the time-to-event prognosis model became more accurate when chest radiographs and clinical data were used together.

Analysis of autonomic function during natural defecation in patients with irritable bowel syndrome using real-time recording with a wearable device.

BACKGROUND: Autonomic dysfunction is a factor in irritable bowel syndrome (IBS). However, there are no reports of autonomic nervous system (ANS) activity during natural defecation in patients with IBS. We aimed to clarify the relationship between ANS activity and life events, such as defecation and abdominal symptoms, using real-time recording. METHODS: Six patients with IBS and 14 healthy controls were enrolled in this prospective multicenter study. ANS activity was recorded for 24 h using a T-shirt wearable device, and life events were recorded simultaneously in real time using a smartphone application software. Low frequency/high frequency (LF/HF) and HF calculated by power spectrum analysis were defined as activity indicators of the sympathetic and parasympathetic nerves, respectively. RESULTS: The means of LF/HF and HF in the period with positive symptoms were comparable between the groups; however, the sum of LF/HF, sum of ΔLF/HF, and the maximum variation in ΔLF/HF were significantly higher in the IBS group. In the IBS group, the sum of ΔLF/HF and LF/HF increased significantly from 2 min before defecation, and the sum of LF/HF remained significantly higher until 9 min after defecation. The sum of ΔLF/HF at 2 min before defecation was significantly positively correlated with the intensity of abdominal pain and diarrhea and constipation scores. In contrast, it was significantly negatively correlated with defecation satisfaction and health-related quality of life. CONCLUSIONS: In patients with IBS, sympathetic nerve activity was activated 2 min before defecation, which was correlated with abdominal symptoms and lower QOL.

Deep convolutional neural networks for automated scoring of pentagon copying test results.

This study aims to investigate the accuracy of a fine-tuned deep convolutional neural network (CNN) for evaluating responses to the pentagon copying test (PCT). To develop a CNN that could classify PCT images, we fine-tuned and compared the pre-trained CNNs (GoogLeNet, VGG-16, ResNet-50, Inception-v3). To collate our training dataset, we collected 1006 correct PCT images and 758 incorrect PCT images drawn on a test sheet by dementia suspected patients at the Osaka City Kosaiin Hospital between April 2009 and December 2012. For a validation dataset, we collected PCT images from consecutive patients treated at the facility in April 2020. We examined the ability of the CNN to detect correct PCT images using a validation dataset. For a validation dataset, we collected PCT images (correct, 41; incorrect, 16) from 57 patients. In the validation testing for an ability to detect correct PCT images, the fine-tuned GoogLeNet CNN achieved an area under the receiver operating characteristic curve of 0.931 (95% confidence interval 0.853-1.000). These findings indicate that our fine-tuned CNN is a useful method for automatically evaluating PCT images. The use of CNN-based automatic scoring of PCT can potentially reduce the burden on assessors in screening for dementia.

Development and validation of a deep learning model for detection of breast cancers in mammography from multi-institutional datasets.

OBJECTIVES: The objective of this study was to develop and validate a state-of-the-art, deep learning (DL)-based model for detecting breast cancers on mammography. METHODS: Mammograms in a hospital development dataset, a hospital test dataset, and a clinic test dataset were retrospectively collected from January 2006 through December 2017 in Osaka City University Hospital and Medcity21 Clinic. The hospital development dataset and a publicly available digital database for screening mammography (DDSM) dataset were used to train and to validate the RetinaNet, one type of DL-based model, with five-fold cross-validation. The model's sensitivity and mean false positive indications per image (mFPI) and partial area under the curve (AUC) with 1.0 mFPI for both test datasets were externally assessed with the test datasets. RESULTS: The hospital development dataset, hospital test dataset, clinic test dataset, and DDSM development dataset included a total of 3179 images (1448 malignant images), 491 images (225 malignant images), 2821 images (37 malignant images), and 1457 malignant images, respectively. The proposed model detected all cancers with a 0.45-0.47 mFPI and had partial AUCs of 0.93 in both test datasets. CONCLUSIONS: The DL-based model developed for this study was able to detect all breast cancers with a very low mFPI. Our DL-based model achieved the highest performance to date, which might lead to improved diagnosis for breast cancer.

Evaluation of long-term survival in patients with severe comorbidities after endoscopic submucosal dissection for esophageal squamous cell carcinoma.

BACKGROUND: Endoscopic submucosal dissection (ESD) is becoming widely popular as a less invasive treatment option for superficial esophageal squamous cell carcinoma. However, data on long-term survival after esophageal ESD in patients with severe comorbidities are limited. This study aimed to evaluate long-term survival after ESD in such patients. METHODS: Altogether, 584 consecutive patients underwent esophageal ESD at our institution from May 2004 to September 2016. Based on the American Society of Anesthesiologists Physical Status (ASA-PS) classification system, patients were grouped according to severe (ASA-PS ≥ 3) or non-severe comorbidities (ASA-PS 1/2). The overall survival (OS), disease-specific survival (DSS), and risk factors for mortality were compared between the groups using a propensity score matching analysis. RESULTS: In a matched cohort of 69 pairs, the 5-year OS rate was poorer in ASA-PS 3 patients than in ASA-PS 1/2 patients (63.9% vs. 92.5%, P < 0.01), while the 5-year DSS rate was similar between the groups (100% vs. 100%). The mortality rate was significantly higher in ASA-PS 3 patients than in ASA-PS 1/2 patients (hazard ratio 3.47; 95% confidence interval 1.79-6.74; P < 0.01). Death due to exacerbation of comorbidities was significantly more frequent in ASA-PS 3 patients than in ASA-PS 1/2 patients (42.4% vs. 8.3%, P < 0.04). CONCLUSION: Because of the exacerbation of comorbidities, patients with severe comorbidities had poorer long-term outcomes after esophageal ESD than those with non-severe comorbidities. Further studies will be necessary to evaluate esophageal ESD in patients with severe comorbidities.

Comparison of the Diagnostic Efficiency of Radial- and Convex-Arrayed Echoendoscopes for Indirect Findings of Pancreatic Cancer: A Retrospective Comparative Study Using Propensity Score Method.

Endoscopic ultrasonography (EUS) is useful for detecting early-stage pancreatic cancer. Because the detection of small lesions is difficult, it is important to detect indirect findings, namely caliber change, retention cysts, and dilatation of the branch duct, during the procedure. Although two types of EUS endoscopes are frequently used, there is no comparative study on their efficacy for detecting indirect findings. Therefore, we aimed to compare the diagnostic efficacy of these two types for indirect findings. We retrospectively analyzed 316 consecutive patients who had undergone EUS for pancreaticobiliary disease at a single center between January 2017 and December 2018. The main outcome was the detection rate of indirect findings and its comparison between the two echoendoscope types. This outcome was achieved using the inverse probability of treatment weighting (IPTW) analysis. The detection rate of indirect findings was higher for the radial-arrayed endoscope than for the convex-arrayed echoendoscope (9.2% vs. 2.3% (p = 0.02)). The univariate analysis also revealed that the radial-arrayed echoendoscope was significantly superior to the convex-arrayed echoendoscope in terms of the detection of indirect findings (odds ratio, 5.94; 95% confidence interval, 1.68-21.10; p = 0.01) after IPTW. After adjustment for magnetic resonance imaging (MRI) and computed tomography (CT), radial-arrayed echoendoscope remained an independent factor for indirect finding detection (odds ratio, 6.04; 95% confidence interval, 1.74-21.00; p = 0.01). Finally, five patients who had indirect EUS findings were diagnosed with pancreatic cancer. Our results indicate that the radial-arrayed echoendoscope is useful for the detection of indirect findings.

Rebamipide ameliorates indomethacin-induced small intestinal damage and proton pump inhibitor-induced exacerbation of this damage by modulation of small intestinal microbiota.

Non-steroidal anti-inflammatory drugs (NSAIDs) induce small intestinal damage. It has been reported that rebamipide, a mucoprotective drug, exerts a protective effect against NSAID-induced small intestinal damage; however, the underlying mechanism remains unknown. In this study, we investigated the significance of the small intestinal microbiota in the protective effect of rebamipide against indomethacin-induced small intestinal damage in mice. A comprehensive analysis of the 16S rRNA gene sequencing revealed an alteration in the composition of the small intestinal microbiota at the species level, modulated by the administration of rebamipide and omeprazole. The transplantation of the small intestinal microbiota of the mice treated with rebamipide suppressed the indomethacin-induced small intestinal damage. Omeprazole, a proton pump inhibitor, exacerbated the indomethacin-induced small intestinal damage, which was accompanied by the alteration of the small intestinal microbiota. We found that the transplantation of the small intestinal microbiota of the rebamipide-treated mice ameliorated indomethacin-induced small intestinal damage and the omeprazole-induced exacerbation of the damage. These results suggest that rebamipide exerts a protective effect against NSAID-induced small intestinal damage via the modulation of the small intestinal microbiota, and that its ameliorating effect extends also to the exacerbation of NSAID-induced small intestinal damage by proton pump inhibitors.

Utility of olfactory identification test for screening of cognitive dysfunction in community-dwelling older adults.

BACKGROUND: There is a need for a large-scale screening test that can be used to detect dementia in older individuals at an early stage. Olfactory identification deficits have been shown to occur in the early stages of dementia, indicating their usefulness in screening tests. This study investigated the utility of an olfactory identification test as a screening test for mild cognitive dysfunction in community-dwelling older people. METHODS: The subjects were city-dwelling individuals aged over 65 years but under 85 years who had not been diagnosed with dementia or mild cognitive impairment. The Japanese version of the Mild Cognitive Impairment Screen was used to evaluate cognitive function. Based on the results, the subjects were divided into two groups: healthy group and cognitively impaired group. Olfactory identification abilities based on the Japanese version of the University of Pennsylvania Smell Identification Test were compared between the groups. RESULTS: There were 182 participants in total: 77 in the healthy group and 105 in the cognitively impaired group. The mean olfactory identification test score of the cognitively impaired group was significantly lower than that of the healthy group. The cognitive impairment test score was significantly correlated with the olfactory identification test score. CONCLUSIONS: Cross-sectional olfactory identification deficits at baseline in community-dwelling older adults reflected cognitive dysfunction. Assessing olfactory identification ability might be useful as a screening test for mild cognitive dysfunction in community-dwelling older people.

Predictive factors for difficult endoscopic submucosal dissection for esophageal neoplasia including failure of en bloc resection or perforation.

BACKGROUND: Endoscopic submucosal dissection (ESD) is accepted as the standard treatment for early-stage esophageal neoplasia. However, esophageal perforation may occur, leading to mediastinitis and pneumothorax, which occasionally require emergency surgery. Moreover, failure of en bloc resection causes local recurrence. However, studies on the predictors of such difficulties during ESD are limited. Hence, we evaluated the predictors associated with the difficulty of ESD for esophageal neoplasia including failure of en bloc resection or perforation. METHODS: Data of 549 consecutive patients who were treated with ESD between May 2004 and March 2016 at a single institution were retrospectively studied. Exclusion criteria were the presence of metachronous esophageal neoplasia or missing data. The primary outcome was determining the predictors associated with the difficulty of ESD for esophageal neoplasia including failure of en bloc resection or perforation. RESULTS: Altogether, 543 patients with 736 lesions were evaluated. Failure of en bloc resection occurred in 6 patients (1.1%) with 6 lesions, and perforation occurred in 11 patients (2.0%) with 11 lesions (1.5%). Multivariate logistic regression analysis showed that large lesion diameter (odds ratio [OR] 1.49; 95% confidence interval [CI] 1.21-1.84; p < 0.001) and previous chemoradiotherapy (OR 5.24; 95% CI 1.52-18.06; p = 0.009) were independent predictive factors. CONCLUSIONS: Larger lesions and previous chemoradiotherapy for esophageal cancer increased the risk for failure of en bloc resection or perforation in patients who underwent esophageal ESD.

Is a proton-pump inhibitor necessary after endoscopic submucosal dissection for superficial esophageal neoplasms? A propensity score analysis.

BACKGROUND: Little is known about the efficacy of proton-pump inhibitor (PPI) therapy in the management of esophageal ulcers after endoscopic submucosal dissection (ESD). Therefore, the objective of this study was to investigate the efficacy of PPI in ulcer healing following ESD for superficial esophageal neoplasms, using a propensity score analytic approach. METHODS: This retrospective cohort study was conducted at a single referral center. Between April 2005 and August 2015, 199 consecutive patients with superficial esophageal cancer and esophageal dysplasia underwent ESD. For patients with PPI administration, intravenous PPI therapy was commenced immediately after ESD, and oral PPI was administered daily from post-operative day 3, until ulcer healing was identified. We compared the remnant-ulcer rate at 4 weeks after esophageal ESD between the PPI administration and non-PPI groups, using propensity scores and the inverse probability of treatment weighting (IPTW) method. RESULTS: After exclusions, a total of 88 patients were analyzed. The remnant-ulcer rate at 4 weeks after ESD was 25.5% (12/47) and 14.6% (6/41) in the PPI administration and non-PPI groups (p = 0.21). After adjusting for background factors using IPTW, the risk of a remnant ulcer in the PPI administration group was not decreased significantly compared with that in the non-PPI group [odds ratio (OR) = 2.42, 95% confidence interval (CI): 0.73-7.97, p = 0.15]. Furthermore, PPI therapy did not decrease significantly the remnant-ulcer rate on logistic regression analysis after adjusting for the propensity score (OR = 2.40, 95% CI: 0.69-8.32, p = 0.15). CONCLUSION: PPI administration does not promote ulcer healing after ESD for superficial esophageal squamous cell carcinoma.

Repeated Endoscopic Submucosal Dissection for Esophageal Neoplasia Located Close to a Previous Endoscopic Submucosal Dissection Scar.

INTRODUCTION: Endoscopic submucosal dissection (ESD) could become a standard treatment for early stage esophageal neoplasia. Recurrence sometimes develops close to a previous ESD scar. These lesions are predictably difficult to treat with ESD because of severe fibrosis. We evaluated the clinical outcomes of ESD for esophageal neoplasia located close to a previous ESD scar. METHODS: This was a retrospective observational study in a single institution. A total of 549 consecutive patients with 927 esophageal lesions were treated with ESD. The primary outcomes were resectability and adverse events of esophageal neoplasia located close to previous ESD scars (ESD scar group) than in primary esophageal ESD (primary group). Furthermore, predictive factors of perforation were examined. RESULTS: A total of 545 primary and 29 ESD scars in consecutive patients were evaluated. En bloc and complete (R0) resection rates in the ESD scar group were lower than those in the primary group (79.3% vs 98.3%, P < 0.01 and 75.9% vs 93.4%, P < 0.01). Perforations occurred more frequently in the ESD scar group (10.3% vs 2.0%, P = 0.03). The ESD scar group was a predictive factor for perforation (odds ratio = 10.37, 95% confidence interval: 2.15-49.94, P = 0.004). There were similar results for inverse probability of treatment weighting methods (odds ratio = 6.78, 95% confidence interval: 1.40-32.98, P = 0.018). DISCUSSION: ESD for esophageal neoplasia located close to a previous ESD scar was difficult to completely resect and increased the likelihood of perforation but could be a treatment option.

Positive correlation between pancreatic volume and post-endoscopic retrograde cholangiopancreatography pancreatitis.

BACKGROUND AND AIM: Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) remains the most common and serious adverse event associated with ERCP. Risk factors for PEP have been described in various reports. However, risk factors have not been quantified to date. The aim of this study was to investigate the risk factors for PEP by quantification of pancreatic volume using pre-ERCP images. METHODS: Overall, 800 patients were recruited from April 2012 to February 2015 for this study. There were 168 patients who satisfied the inclusion criteria. Measurement of pancreatic volume was achieved using the volume analyzer SYNAPSE VINCENT in all cases and was used to evaluate the risk factors for PEP. RESULTS: According to the criteria established by the consensus guidelines (Cotton classification), 17 patients (10.1%) were classified as having mild disease, 4 (2.4%) as having moderate disease, and 5 (3.0%) as having severe disease. Multivariate model analysis showed that a large pancreatic volume was a significant risk factor for PEP (odds ratio [OR] 1.10, 95% confidence interval [CI] 1.06-1.13; P < 0.001). In addition, the association between the pancreatic volume and the severity of PEP was positively correlated (the effect of volume [per 1 mL]; OR 1.09, 95% CI 1.07-1.12; P < 0.001, the effect of volume [per 10 mL]; OR 2.27, 95% CI 1.72-3.00; P < 0.001). A larger pancreatic volume was significantly associated with a higher incidence of PEP. CONCLUSIONS: A large pancreatic volume was identified as a risk factor for PEP. The results of this study suggest that pre-ERCP images might be useful for predicting PEP.

Involvement of gliadin, a component of wheat gluten, in increased intestinal permeability leading to non-steroidal anti-inflammatory drug-induced small-intestinal damage.

Gliadin, a component of wheat gluten known to be an important factor in the etiology of celiac disease, is related to several other diseases through its enhancing effect on intestinal paracellular permeability. We investigated the significance of gliadin in non-steroidal anti-inflammatory drug (NSAID)-induced small-intestinal damage in mice. 7-week-old C57BL/6 male mice were divided into the following groups: standard diet group, in which mice were fed with wheat-containing standard rodent diet (CE-2); gluten-free diet group, in which mice were fed with gluten-free diet (AIN-76A); and gliadin-administered group, in which mice fed with gluten-free diet were administered with gliadin (~250 mg/kg BW). Each group was subdivided into negative, healthy control group and NSAID-treated group. To some mice fed with gluten-free diet and administered with gliadin, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor was administered for clarification of the significance of EGFR in NSAID-induced small intestinal damage and intestinal permeability. In mice fed with a gluten-free diet, indomethacin or diclofenac induced very mild mucosal damage in the small intestine compared with that in mice fed with a wheat-containing standard diet. Gliadin exacerbated the NSAID-induced small-intestinal damage in mice fed with a gluten-free diet. With the administration of indomethacin, MPO activity, a marker of neutrophil infiltration into the mucosa and mRNA expression level of tumor necrosis factor α and interleukin-1ß in the small intestine were higher in the gliadin-administered mice. Gliadin increased the intestinal paracellular permeability without indomethacin administration (4.3-fold) and further increased the permeability after indomethacin administration (2.1-fold). Gliadin induced phosphorylation of epidermal growth factor receptor (EGFR) in small-intestinal tissues, and erlotinib (an EGFR tyrosine kinase inhibitor) attenuated the indomethacin-induced intestinal damage and permeability exacerbated by gliadin, accompanied by inhibition of EGFR phosphorylation. These results suggest that gliadin plays an important role in the induction and exacerbation of NSAID-induced small-intestinal damage, and that increase in intestinal permeability via the EGFR signalling pathway is involved in its mechanism.

Impact of preoperative biopsy sampling on severe submucosal fibrosis on endoscopic submucosal dissection for colorectal laterally spreading tumors: a propensity score analysis.

BACKGROUND AND AIMS: It is believed that preoperative biopsy sampling for superficial-type colorectal tumors should be avoided because submucosal fibrosis caused by biopsy sampling makes EMR impossible. However, few studies have reported the influence of biopsy sampling on colorectal endoscopic submucosal dissection (ESD). This study aimed to examine the effect of biopsy sampling on submucosal fibrosis and treatment outcomes of ESD for laterally spreading tumors (LSTs). METHODS: Between April 2005 and September 2015, 441 consecutive patients underwent colorectal ESD in Osaka City University Hospital. Using propensity score matching and inverse probability of treatment weighting (IPTW), we retrospectively evaluated risk factors for severe submucosal fibrosis and treatment outcomes for patients with LSTs, with or without preoperative biopsy sampling. RESULTS: A total of 428 LSTs resected using ESD were enrolled. After matching, there were 136 matched pairs of lesions that did or did not undergo biopsy sampling. Preoperative biopsy sampling increased severe fibrosis compared with that in the non-biopsy sampling group (20.6% vs 11.0%; P = .03) and was significantly associated with severe fibrosis after matching (odds ratio [OR], 2.09; 95% confidence interval [CI], 1.07-4.10; P = .03). After adjustment with IPTW, biopsy sampling also increased the risk of severe fibrosis (OR, 2.33; 95% CI, 1.17-4.63; P = .02). However, no significant differences were observed between the 2 groups in treatment outcomes. CONCLUSIONS: Preoperative biopsy sampling for colorectal LSTs might cause severe submucosal fibrosis but has no adverse influence on clinical outcomes of ESD.

Long-term outcome of endoscopic submucosal dissection for early gastric cancer in patients with severe comorbidities: a comparative propensity score analysis.

BACKGROUND: Recently, endoscopic submucosal dissection (ESD) for early gastric cancer (EGC) has been performed on patients with severe comorbidities because it is less invasive, although little is known regarding long-term outcomes. This study aimed to assess the long-term outcomes of ESD for patients with severe and non-severe comorbidities. METHODS: We enrolled 1081 patients who underwent ESD for EGC between February 2004 and June 2013. Based on the American Society of Anesthesiologists Physical Status (ASA-PS) classification, we defined patients with severe and non-severe comorbidities as ASA-PS 3 and 1/2, respectively. We retrospectively compared the overall survival, risk factors for mortality, and adverse events between these two groups using propensity score matching and inverse probability of treatment weighting. RESULTS: A total of 488 patients met the eligibility criteria. After matching, the ASA-PS 3 group showed a significantly shorter survival than the ASA-PS 1/2 group (5-year overall survival rate, 79.1 vs. 87.7%; p < 0.01). In addition, only the ASA-PS 3 group had a significant risk factor for mortality using both the Cox analysis [hazard ratio (HR), 2.56; 95% confidence interval (CI) 1.18-5.52; p = 0.02] and the IPTW method (HR, 3.14; 95% CI 1.91-5.14; p < 0.01). There was no significant difference in adverse events after matching between the two groups (p = 0.21). CONCLUSIONS: The long-term outcome of gastric ESD for patients with severe comorbidities was worse than for those with non-severe comorbidities. Further studies will be necessary to determine if ESD is truly warranted in these patients.

Colorectal polyps located across a fold are difficult to resect completely using endoscopic mucosal resection: A propensity score analysis.

BACKGROUND: Incomplete polyp resection during colorectal endoscopic mucosal resection (EMR) might contribute to the development of interval cancer. OBJECTIVE: This retrospective study aimed to determine the incidence of incomplete polyp resection during EMR of colorectal polyps located across a fold compared with that of colorectal polyps located between folds. METHODS: In total, 262 patients with 262 lesions that were ≥10 mm in diameter and treated with conventional EMR were enrolled. The main outcome was the incidence of incomplete polyp resections. Propensity score matching and inverse probability of treatment weighting (IPTW) were performed to reduce the effects of selection bias. RESULTS: Fifty-seven lesions (21.8%) were incompletely resected. After propensity score matching, the lesions located across a fold were at higher risk of incomplete resection than those between folds (26/68, 38.2% vs 7/68, 10.3%; odds ratio (OR): 3.71; 95% confidence interval (CI): 1.61-8.56; p < 0.01). These findings persisted after adjusting for the differences at baseline using the IPTW method (OR: 3.63; 95% CI: 1.72-7.63; p = 0.001). CONCLUSIONS: There is an increased risk of an incomplete polyp resection for a colorectal polyp that is located across a fold compared with that for a polyp that is located between folds.

Heparin-bridging therapy is associated with post-colorectal polypectomy bleeding in patients whose oral anticoagulation therapy is interrupted.

OBJECTIVES: The American and Japanese Societies for Gastrointestinal Endoscopy Guidelines recommend heparin-bridging therapy for patients whose oral anticoagulants are interrupted for endoscopic procedures. However, little is known about the potential association between heparin-bridging therapy and post-polypectomy bleeding (PPB). The aim was to investigate the incidence of PPB associated with heparin-bridging therapy administered to patients whose anticoagulants were interrupted. MATERIALS AND METHODS: This was a retrospective observational study using inverse propensity analysis. Between 2013 and 2015, 1004 patients with 2863 lesions were included. The primary outcomes were the rates of PPB and thromboembolism associated with heparin-bridging therapy. The risk factors associated with PPB were identified using multivariate logistic regression analysis involving probability of treatment weighting (IPTW). RESULTS: The patients were categorized into a heparin-bridging therapy group (78 patients with 255 lesions) or a control group (926 patients with 2608 lesions). The PPB rate in the heparin-bridging therapy group (10.2%, 8/78) was significantly higher than in the control group (1.1%, 11/926) (p <.01). Thromboembolism occurred in one patient in the control group. The multivariate analysis revealed that heparin-bridging therapy was an independent risk factor associated with PPB (odds ratio [OR], 8.21; 95% confidence interval [95% CI], 2.32-29.10; p <.01). IPTW showed heparin-bridging therapy increased PPB (OR, 7.68; 95% CI, 1.83-32.28; p <.01). CONCLUSIONS: Heparin-bridging therapy administered to patients whose oral anticoagulants were interrupted was associated with an increased PPB risk.