Background The traditional management of appendicular mass is an initial conservative treatment followed by interval appendectomy. Recently interval appendicectomy has been questioned.
Objective: The purpose of this study was to clarify the need and the role of interval appendicectomy after successful initial conservative treatment.
Method: This is a prospective study conducted in a major hospital in Basra from April 2006 to Septemper2010, included 65 patients with appendicular mass which subsequently proved postinflammmatory (phlegmonous) changes of the appendix were treated conservatively.
Results: Routine interval appendicectomy was not performed and needed after successful treatment in the majority of the patients (84.6%). Four patients (6.1%) developed abscess formation and operation
was necessary to drain the abscess. Four patients were readmitted with recurrent appendicitis after 2 months. During the 2 years follow up period another 2 patients presented with recurrent symptoms of acute appendicitis and appendectomy were arranged. The recurrence rate after successful conservative treatment was 10%.
Conclusion routine interval appendectomy after initial
successful conservative treatment is of questionable
benefit and needs further assessment.
Co-composting process can be acquired by combining organic fraction of municipal solid waste (OFMSW) with sewage sludge (SS) and mature compost (MC) as enhancement and bulking agent to overcome the problems of municipal solid waste and wastewater treatment plants besides the finally produced fertilizer usage for agriculture and horticulture. The effects of different mixture ratios of (OFMSW), (SS) and (MC) on the performance of composting process were investigated in this study. Piles of about 10 kg were prepared by mixing OFMSW, SS and MC in three different ratios (w/w) [OFMSW: SS: MC= 3:1:1, 3:2:1, and 3:3:1]. Results showed that the pile [3:1:1] was most beneficial to composting. The final compost products contained a
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... Show MoreAn intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co
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