Background:-The Modified Alvarado Scoring System (MASS) has been reported to be a cheap and quick diagnostic tool in patients with acute appendicitis. However, differences in diagnostic accuracy have been observed if the scores were applied to various populations and clinical settings.
Objectives:- The purpose of this study was to evaluate the diagnostic value of Modified Alvarado Scoring System in patients with acute appendicitis in our setting.
Methods:-one hundre twenty eight patients ,were included in this study, admitted to Al-Kindy teaching hospital from June 2009 to June 2010. Patients’ age ranged from 8 to 56 years (21±10) they were divided into three groups; paediatrics, child bearing age females & adult males,. MASS was calculated for each patient included as the diagnosis & treatment were done on the bases of surgeon's clinical decision,confirmation was done by histopathological examination. Finally statistics done included negative appendectomy rate, sensitivity,specificity,positive predictive value,negative predictive value & accuracy.
Results:- Our negative appendectomy rate was 19.5% (22.22% for paediatrics 40.9% for females 4.2% for males). MASS showed sensitivity of 61%(92.8% for paediatrics 38% for females & 58% for males), specificity 80% (75% for paediatrics 88% for females & 50% for males), positive predictive value 92%(92.8% for paediatrics 83% for females 50% for males), negative predictive value 33% ( 75%for paediatrics 50% for females 5% for males) & accuracy 65% ( 88.9% for paediatrics 59% for females 58% for males).
Conclusion:- MASS was of limited help to junior doctors in our setting,clinical assessment & experience are still the gold standard for acute appendicitis.
Rate of zinc consumption during the cathodic protection of copper pipeline which carries saline water was measured by weight loss technique in the absence and presence of bacteria. Variables studied were solution flow rate, temperature, time and NaCl concentration. It was found that within the present range of variables; the rate of zinc consumption increases with the increase of all operating conditions. The presence of bacteria increases the zinc consumption. Fourth order multi-term model and one-term model were suggested to represent the consumption data. Nonlinear regression analysis was used to estimate the coefficients of these models, while statistical analysis was used to determine the effect of each coefficient. Both models were re
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
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