Foreign body in the upper oesophagus - A double scope extraction approach.

Flexible esophagogastroduodenoscopy is the gold standard for removing FB of the upper gastrointestinal tract. However large sharped FB are usually challenging to remove and are the subtype that most often requires surgery. We describe a case of a patient with a dental prothesis impacted in the proximal oesophagus. After a failed conventional approach, we made a successful attempt with two regular scopes with two independent operators.

Identification of biomarkers predictive of metastasis development in early-stage colorectal cancer using network-based regularization.

Colorectal cancer (CRC) is the third most common cancer and the second most deathly worldwide. It is a very heterogeneous disease that can develop via distinct pathways where metastasis is the primary cause of death. Therefore, it is crucial to understand the molecular mechanisms underlying metastasis. RNA-sequencing is an essential tool used for studying the transcriptional landscape. However, the high-dimensionality of gene expression data makes selecting novel metastatic biomarkers problematic. To distinguish early-stage CRC patients at risk of developing metastasis from those that are not, three types of binary classification approaches were used: (1) classification methods (decision trees, linear and radial kernel support vector machines, logistic regression, and random forest) using differentially expressed genes (DEGs) as input features; (2) regularized logistic regression based on the Elastic Net penalty and the proposed iTwiner-a network-based regularizer accounting for gene correlation information; and (3) classification methods based on the genes pre-selected using regularized logistic regression. Classifiers using the DEGs as features showed similar results, with random forest showing the highest accuracy. Using regularized logistic regression on the full dataset yielded no improvement in the methods' accuracy. Further classification using the pre-selected genes found by different penalty factors, instead of the DEGs, significantly improved the accuracy of the binary classifiers. Moreover, the use of network-based correlation information (iTwiner) for gene selection produced the best classification results and the identification of more stable and robust gene sets. Some are known to be tumor suppressor genes (OPCML-IT2), to be related to resistance to cancer therapies (RAC1P3), or to be involved in several cancer processes such as genome stability (XRCC6P2), tumor growth and metastasis (MIR602) and regulation of gene transcription (NME2P2). We show that the classification of CRC patients based on pre-selected features by regularized logistic regression is a valuable alternative to using DEGs, significantly increasing the models' predictive performance. Moreover, the use of correlation-based penalization for biomarker selection stands as a promising strategy for predicting patients' groups based on RNA-seq data.

Alcohol-Related Liver Disease Is Rarely Detected at Early Stages Compared With Liver Diseases of Other Etiologies Worldwide.

BACKGROUND & AIMS: Despite recent advances in treatment of viral hepatitis, liver-related mortality is high, possibly owing to the large burden of advanced alcohol-related liver disease (ALD). We investigated whether patients with ALD are initially seen at later stages of disease development than patients with hepatitis C virus (HCV) infection or other etiologies. METHODS: We performed a cross-sectional study of 3453 consecutive patients with either early or advanced liver disease (1699 patients with early and 1754 with advanced liver disease) seen at 17 tertiary care liver or gastrointestinal units worldwide, from August 2015 through March 2017. We collected anthropometric, etiology, and clinical information, as well as and model for end-stage liver disease scores. We used unconditional logistic regression to estimate the odds ratios for evaluation at late stages of the disease progression. RESULTS: Of the patients analyzed, 81% had 1 etiology of liver disease and 17% had 2 etiologies of liver disease. Of patients seen at early stages for a single etiology, 31% had HCV infection, 21% had hepatitis B virus infection, and 17% had nonalcoholic fatty liver disease, whereas only 3.8% had ALD. In contrast, 29% of patients seen for advanced disease had ALD. Patients with ALD were more likely to be seen at specialized centers, with advanced-stage disease, compared with patients with HCV-associated liver disease (odds ratio, 14.1; 95% CI, 10.5-18.9; P < .001). Of patients with 2 etiologies of liver disease, excess alcohol use was associated with 50% of cases. These patients had significantly more visits to health care providers, with more advanced disease, compared with patients without excess alcohol use. The mean model for end-stage liver disease score for patients with advanced ALD (score, 16) was higher than for patients with advanced liver disease not associated with excess alcohol use (score, 13) (P < .01). CONCLUSIONS: In a cross-sectional analysis of patients with liver disease worldwide, we found that patients with ALD are seen with more advanced-stage disease than patients with HCV-associated liver disease. Of patients with 2 etiologies of liver disease, excess alcohol use was associated with 50% of cases. Early detection and referral programs are needed for patients with ALD worldwide.