Background: Ankle injuries are one of the most common complaints of patients presenting to emergency departments (ED). The Ottawa ankle rules (OAR) was introduced to help physicians to decide who may require x-ray for blunt injuries. The present study aimed at validating the four steps weight-bearing rule of OAR as a sole criterion.    Methods: This prospective observational study wa...

OBJECTIVE To assess the diagnostic accuracy of pain on travelling over speed bumps for the diagnosis of acute appendicitis. DESIGN Prospective questionnaire based diagnostic accuracy study. SETTING Secondary care surgical assessment unit at a district general hospital in the UK. PARTICIPANTS 101 patients aged 17-76 years referred to the on-call surgical team for assessment of possible app...

We read with interest the Iranikhah et al’s article entitled “Stool Antigen Tests for the Detection of Helicobacter Pylori in Children” in the second issue of 2013 of Iran J Pediatr[1]. The authors have well reported an interesting investigation about the detection of bacterial antigens in stool for diagnosis of Helicobacter pylori in children. Also they appropriately used endoscopy and biopsy ...

OBJECTIVE To evaluate if prostate specific antigen test attains validity standards required for screening in view of recent prostate cancer screening trial results. DESIGN Case-control study nested in longitudinal cohort. SETTING Västerbotten Intervention Project cohort, Umeå, Sweden. PARTICIPANTS 540 cases and 1034 controls matched for age and date of blood draw. MAIN OUTCOME MEASURE V...

Background Currently, almost all patients with probable abdominal injury undergo urinalysis in emergency department (ED). The present survey was conducted with the aim of assessing the diagnostic values of urinalysis compare with abdominal computed tomography (CT) scan with contrast for predicting possible intra-abdominal injuries in children affected by blunt trauma. Materials and Methods: The...

Many learning algorithms form concept descriptions composed of clauses, each of which covers some proportion of the positive training data and a small to zero proportion of the negative training data. This paper presents a method using likelihood ratios attached to clauses to classify test examples. One concept description is learned for each class. Each concept description competes to classify...

Many learning algorithms form concept descriptions composed of clauses, each of which covers some proportion of the positive training data and a small to zero proportion of the negative training data. This paper presents a method using likelihood ratios attached to clauses to classify test examples. One concept description is learned for each class. Each concept description competes to classify...