Background: Lower gastrointestinal bleeding (LGIB) is bleeding arising below the ligament of Treitz. Hemorrhage from the lower gastrointestinal (GI) tract accounts for about 20% of all cases of acute GI bleeding. Lower GI bleeding is that which occurs from the colon, rectum, or anus, and presenting as either hematochezia (bright red blood or red wine color stools) or malena, blood streaking of the stool. The objective of this study was to evaluate the etiological profile of patients presenting with lower gastrointestinal bleeding.Methods: This one-year cross-sectional study was conducted in the Department of Medicine, KLES Dr. Prabhakar Kore Hospital and Medical Research Centre, Belagavi from January 2015 to December 2015. The study design was a cross-sectional study. This study was carried out from January 2015 to December 2015. Patients with lower gastro-intestinal bleeding presenting at Department of Medicine and Department of Gastro-enterology, KLES Dr. Prabhakar Kore Hospital and Medical Research Centre, Belagavi were studied.Results: In the present study majority of the patients were males with the mean age was 43.82±17.96 years and majority of the patients were married with moderate built and nourishment. As per the occupation majority were housewives followed by students. In the present study diabetes mellitus was the most common medical history reported. Internal haemorrhoids was significantly associated with male sex, student’s profession followed by housewife with mixed diet consumption, the clinical presentations significantly associated with internal haemorrhoids were haematochezia, loss of appetite, tenesmus, passage of mucus in stools, constipation, abdominal pain and vomiting.Conclusions: Internal hemorrhoids is the most common cause followed by ulcerative colitis. Though not common, carcinoma colon, solitary rectal ulcer syndrome, polyp, colonic diverticulosis, ischaemic colitis, non-specific proctitis, and radiation proctitis are the other causes of LGIB.
Esophagitis is a condition of inflammation of the esophageal mucosa, which is also called as acid reflux disease. The cause maybe be due to slackness of the lower esophageal sphintcer which allows acidic contents of the food from stomach to esophagus. Esophagitis is detected by observing the esophagus by video endoscopy of the Upper Gastro-Intestinal tract. The classification of esophagitis is done by analyzing the images captured during the process of endoscopy. Classification of Esophagitis has many standards , with each standard having its plus and minus. The Los Angeles(LA) Classification deals with precise measurement of the mucosal breaks, for an image processing system to measure the mucosal breaks the position of the camera is to be known. We attempt to classify the Esophagitis using LA Classification without the camera position information using low level image features and classification is performed using a neural network classifier. The results of the classifier are compared with inter and intra observer variability studies. General Terms :Medical Diagnosis, Decision Support System
Esophagitis is essentially inflammation of the esophageal squamous mucosa. One of the major reasons for cause of Esophagitis is the acid reflux from the stomach. This condition is observed in the process of upper gastro-intestinal tract endoscopy and the diagnosis is arrived at by examining the images of the esophagus. The diagnosis is based on the observation of the lesions and coloration of the digestive mucosa. Our paper reports an implementation of Decision Support System (DSS) for diagnosis of Esophagitis based on the analysis of color and texture features of the images captured during the process of endoscopy. The Hue Saturation and Intensity color model is adapted. The statistical features of the Hue and Saturation form the color features and the texture features are determined by Discrete Cosine Transform coefficients of the image. The decision making structure is a feed forward neural network. The DSS has been tested and results are reported.
Introduction: Saroglitazar is known to safely and effectively improve dyslipidemia by reducing triglyceride (TG), low density lipoprotein (LDL) cholesterol, very low-density lipoprotein (VLDL) cholesterol, non-high-density lipoprotein (non-HDL) cholesterol and increasing high density lipoprotein (HDL) cholesterol. In addition, saroglitazar can improve glycemic indices in diabetic patients by reducing fasting plasma glucose (FPG) and glycosylated haemoglobin (HbA1c). Aim of the study was to evaluate the hospital based clinic-pathological profile, diagnosis, treatment and follow up of Indian patients with Non-alcoholic fatty liver disease and to evaluate the safety and efficacy of Saroglitazar 4 mg in patients with Non-alcoholic fatty liver disease /Non-alcoholic Steatohepatitis in real life setting. Material and methods: This was an ongoing observational study with the sample size of 52 patients having Nonalcoholic fatty liver disease and dyslipidaemia with or without Type 2 Diabetes Mellitus and treatment follow up for a period of 1 year in the Department Of Gastroenterology. The data was collected from eligible patients who have been prescribed Saroglitazar 4 mg once daily in routine clinical practice. Primary endpoints were to see liver stiffness. Secondary endpoints were to measure serum alanine aminotransferase, aspartate aminotransferase level and Serum triglycerides level. Results: There was a significant decrease in Serum alanine aminotransferase (p <0.001), aspartate aminotransferase (p value < 0.001), triglycerides (p value <0.001) and triglycerides (p value 0.01), levels after the treatment as compared to the baseline. Conclusion: Saroglitazar treatment is effective and there is a significant difference in Serum alanine aminotransferase and aspartate aminotransferase, triglycerides and Liver Stiffness Measurement levels after treatment. The drug can be successfully administered for the treatment of Non-alcoholic fatty liver disease.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.