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10.1038/ajg.2015.239 http://scihub22266oqcxt.onion/10.1038/ajg.2015.239 C4586067!4586067!26303128     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=26303128&cmd=llinks): Failed to open stream: HTTP request failed! 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A clinical prediction tool identifies cases of eosinophilic esophagitis without endoscopic biopsy: A prospective study |pdf=|usr=}}{{26303128}} gab.com Text A clinical prediction tool identifies cases of eosinophilic esophagitis without endoscopic biopsy: A prospective study JO: Am J Gastroenterol http://www.kidney.de/pget.php?&tw=1&pmid=26303128 #FOAvip Objectives: Eosinophilic esophagitis (EoE) is difficult to distinguish from gastroesophageal reflux (GERD) and other causes of dysphagia. We assessed the utility of a set of clinical and endoscopic features for predicting EoE without obtaining esophageal biopsies. Methods: We prospectively enrolled consecutive adults undergoing outpatient upper endoscopy at University of North Carolina from 7/2011?12/2013. Incident cases of EoE were diagnosed per consensus guidelines. Non-EoE controls had either GERD- or dysphagia-predominant symptoms. A predictive model containing clinical and endoscopic, but no histologic data was assessed. Receiver operator characteristic (ROC) curves were constructed and the area under the curve (AUC) was calculated. Results: A total of 81 EoE cases (mean age 38 years; 60% male; 93% white; 141 eos/hpf) and 144 controls (mean age 52, 38% male; 82% white; 3 eos/hpf) were enrolled. A combination of clinical (age, sex, dysphagia, food allergy) and endoscopic (rings, furrows, plaques, hiatal hernia) features was highly predictive of EoE. The AUC was 0.944, with sensitivity, specificity, and accuracy of 84%, 97%, and 92%. Similar values were seen after limiting controls to those with only reflux or dysphagia, or to those with esophageal eosinophilia not due to EoE. Conclusions: We validated a set of clinical and endoscopic features to predict EoE with a high degree of accuracy, and allow identification of those at very low risk of disease. Use of these predictors at the point-of-care will avoid the effort and expense of low-yield histological examinations for EoE. Twit Text FOAVip A clinical prediction tool identifies cases of eosinophilic esophagitis without endoscopic biopsy: A prospective study ????Am J Gastroenterol http://www.kidney.de/pget.php?&tw=1&pmid=26303128 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26303128 #FOAvip English Wikipedia <ref>{{Cite pmid|26303128}}</ref> A clinical prediction tool identifies cases of eosinophilic esophagitis without endoscopic biopsy: A prospective study #MMPMID26303128 Dellon ES; Rusin S; Gebhart JH; Covey S; Speck O; Woodward K; Higgins LL; Beitia RM; Madanick RD; Levinson S; Woosley JT; Shaheen NJ Am J Gastroenterol 2015[Sep]; 110 (9): 1347-54 PMID26303128show ga Objectives: Eosinophilic esophagitis (EoE) is difficult to distinguish from gastroesophageal reflux (GERD) and other causes of dysphagia. We assessed the utility of a set of clinical and endoscopic features for predicting EoE without obtaining esophageal biopsies. Methods: We prospectively enrolled consecutive adults undergoing outpatient upper endoscopy at University of North Carolina from 7/2011?12/2013. Incident cases of EoE were diagnosed per consensus guidelines. Non-EoE controls had either GERD- or dysphagia-predominant symptoms. A predictive model containing clinical and endoscopic, but no histologic data was assessed. Receiver operator characteristic (ROC) curves were constructed and the area under the curve (AUC) was calculated. Results: A total of 81 EoE cases (mean age 38 years; 60% male; 93% white; 141 eos/hpf) and 144 controls (mean age 52, 38% male; 82% white; 3 eos/hpf) were enrolled. A combination of clinical (age, sex, dysphagia, food allergy) and endoscopic (rings, furrows, plaques, hiatal hernia) features was highly predictive of EoE. The AUC was 0.944, with sensitivity, specificity, and accuracy of 84%, 97%, and 92%. Similar values were seen after limiting controls to those with only reflux or dysphagia, or to those with esophageal eosinophilia not due to EoE. Conclusions: We validated a set of clinical and endoscopic features to predict EoE with a high degree of accuracy, and allow identification of those at very low risk of disease. Use of these predictors at the point-of-care will avoid the effort and expense of low-yield histological examinations for EoE. äA clinical prediction tool identifies cases of eosinophilic esophagiti(epmc).pdf DeepDyve Pubget Overpricing