Impact of routine cerebral CT angiography on treatment decisions in infective endocarditis.

BACKGROUND:Infective endocarditis (IE) is commonly complicated by cerebral embolization and hemorrhage secondary to intracranial mycotic aneurysms (ICMAs). These complications are associated with poor outcome and may require diagnostic and therapeutic plans to be modified. However, routine screening by brain CT and CT angiography (CTA) is not standard practice. We aimed to study the impact of routine cerebral CTA on treatment decisions for patients with IE. METHODS:From July 2007 to December 2012, we prospectively recruited 81 consecutive patients with definite left-sided IE according to modified Duke's criteria. All patients had routine brain CTA conducted within one week of admission. All patients with ICMA underwent four-vessel conventional angiography. Invasive treatment was performed for ruptured aneurysms, aneurysms ≥ 5 mm, and persistent aneurysms despite appropriate therapy. Surgical clipping was performed for leaking aneurysms if not amenable to intervention. RESULTS:The mean age was 30.43 ± 8.8 years and 60.5% were males. Staph aureus was the most common organism (32.3%). Among the patients, 37% had underlying rheumatic heart disease, 26% had prosthetic valves, 23.5% developed IE on top of a structurally normal heart and 8.6% had underlying congenital heart disease. Brain CT/CTA revealed that 51 patients had evidence of cerebral embolization, of them 17 were clinically silent. Twenty-six patients (32%) had ICMA, of whom 15 were clinically silent. Among the patients with ICMAs, 11 underwent endovascular treatment and 2 underwent neurovascular surgery. The brain CTA findings prompted different treatment choices in 21 patients (25.6%). The choices were aneurysm treatment before cardiac surgery rather than at follow-up, valve replacement by biological valve instead of mechanical valve, and withholding anticoagulation in patients with prosthetic valve endocarditis for fear of aneurysm rupture. CONCLUSIONS:Routine brain CT/CTA resulted in changes in the treatment plan in a significant proportion of patients with IE, even those without clinically evident neurological disease. Routine brain CT/CTA may be indicated in all hospitalized patients with IE

Accuracy of Emergency Severity Index, Version 4 in emergency room patients’ classification

Introduction: Emergency Severity Index Version 4 (ESI v.4) is a validated triage tool for emergency departments, with an easy training system optimizing the allocation of limitedresources to emergency patients. The present study aimed to determine the outcomes of triagewith ESI v.4 method in all five levels of patients triage in emergency departments. Methods: In this retrospective observational-descriptive study, following the training coursesand implementation of triage with ESI v.4 method, the third quarter of 2008 was randomly selected for study. In this period, all patient files with their codes ending in zero were selectedequaling one-tenth of all files. Triage levels and outcomes were extracted and the obtaineddata from 1309 were expressed using descriptive statistics. Results: The mean age of the patients was 40.73 ± 21.37 years and 59.4% of the subjects weremales. Classification of patients by ESI v.4 level was as the following: 1 (4.0%), 2 (11.6%), 3 (52.8%), 4 (25.5%) and 5 (6.1%). Hospitalization rate by ESI v.4 level was as below: 1(80.76%), 2 (23.68%), 3 (25.75%), 4 (11.76%) and 5 (14.5%). Conclusion: The rate of hospitalization decreased from ESI level 1 to ESI level 5. Althoughthe findings of this study were in line with the previous reports, some discrepancies indicated the existing inaccuracy in out-patient hospitalization system in the evening and night shiftsand also at stage 5 triage level

Spectroscopic Methods for Analysis of Nano Drug Distribution System

The size of the objects that are constituted within an alleged nano metric measurement of 1 to 100 nm is generally the main feature of nanoscience and nanotechnology. The system of unharness may be an essential method of acknowledging contained drug delivery systems in the formation of nano drug. Nanoparticles may surpass the crucial troubles of traditional little molecules / biomacromolecules, such as protein, ribonucleic acid, and DNA, utilized in several diseases through permitting objective delivery and surpassing biological obstacles. Many spectroscopical analytical techniques have been applied to define the free drug component from the nano drug formation, in various substantial cases, during various duration. One of them is analytical chemistry concerning the development of new techniques to develop old ones and supply the requirements of chemical information constrained by modern issues. Analytical chemistry is greatly affected by the development of nanoscience and nanotechnology. The aim of this review is to present a comparison of different spectroscopic analytical techniques which are presently applied to various systems of nano drug delivery to present elaborate and helpful data for other researchers

Edge Detection of Noisy Medical Images Based Mixed Entropy

Edge detection of medical image has used as one of diagnostics techniques largely applied for the doctor's diagnosis determination. Although the edge detection of medical images is existing since years but it is still challenging and scope of research. It has been found that the previous used algorithms were not able to produce optimized or ideal results in different cases. In most applications, medical images contain object boundaries and object shadows and noise. Therefore, they may be difficult to distinguish the exact edge from noise or trivial geometric features. In this paper, we propose a new efficient algorithm for edge detection of noisy medical images based on mixed entropy. Mixed entropy  is defined in order to suppress noise and adapt to different edge in the image. Our target is to get the best edge representation under noise effect. The performance of our algorithm is compared against other methods using images corrupted with various levels of "salt and pepper". It is observed that the proposed algorithm displayed superior noise resilience and decrease the computation time. The results indicate the accuracy of the proposed edge-detection method is superior to that of conventional edge-detection methods for medical image. Keywords: Edge Detection; Medical Images ; Entropy; Noisy Image