Prolonged mechanical ventilation (PMV) is associated with increase in mortality and resource utilisation as well as hospitalisation costs. This study evaluates the risk factors of PMV. A retrospective study was conducted involving 890 paediatric patients comprising 237 neonates, 306 infants, 223 of pre-school age and 124 who are of school going age. The data mining decision trees algorithms and logistic regression was employed to develop predictive models for each age category. The independent variables were classified into four categories, that is, demographic data, admission factors, medical factors and score factors. The dependent variable is the duration of ventilation where it is categorized 0 denoting non-PMV and 1 denoting PMV. The performances of three decision tree models (CHAID, CART and C5.0) and logistic regression were compared to determine the best model. The results indicated that the decision tree outperformed the logistic regression model for all age categories, given its good accuracy rate for testing dataset. Decision trees results identified length of stay and inotropes as significant risk factors in all age categories. PRISM 12 hours and principal diagnosis were identified as significant risk factors for infants.
Input-Output analysis provides important information about the structure of a country’s economy. The construction of input-output tables based on detailed census or surveys is a complex procedure requiring substantial financial outlay, human capital, and time. This is the main reason why Malaysia Input-Output (MIO) Table is produced and published on average once every five years. For policy makers past data is not seen as suitable for planning economic policies. The aim of this study is to compare RAS and Euro methods to project input-output tables for Malaysia. The data for the study are MIO table and Gross Domestic Product for the years 2000, 2005 and 2010. The RAS and Euro method were used to project the MIO table 2005 using MIO table 2000 and also projection of MIO table 2010 using MIO table 2005. The projection of I-O tables involved an intensive iterative procedure using Excel Visual Basic programming. The projection performance of RAS and Euro methods were assessed based on Mean Absolute Deviation (MAD), Root Mean Squared Error (RMSE) and Dissimilarity Index (DI). The results show that Euro method performed better than the RAS method in the projection of MIO table.
A Structural Equation Model (SEM) is often used to test whether a hypothesised theoretical model agrees with data by examining the model fit. This study investigates the effect of sample size and distribution of data (normal and non-normal) on goodness of fit measures in structural equation model. Simulation results confirm that the GoF measures are affected by sample size, whereas they are quite robust when data are not normal. Absolute measures (GFI, AGFI, RMSEA) are more affected by sample size while incremental fit measures such as TLI and CFI are less affected by sample size and non-normality.
A cross sectional survey was conducted in Kampung Datuk Kerarnat, an urbanized residential area in Kuala Lumpur from August to November ZOO5 to assess knowledge, attitude and preventive practices on dengue among its residents. A two stage sampling strategy was used to select survey household. An adult aged at least 21 years old was identified from each selected household and interviewed using a standardized questionnaire. Data was collected on demographics, dengue related KAP and house-types. Knowledge, attitude and practice were assessed using a scoring system. Each appropriate answer was given a point and the points for each section of the questionnaire were totalled. Knowledge was assessed as ‘good' or ‘moderate to poor’ based on arbitrary cut-off point. Out of 133 respondents interviewed, 78.2% were able to identify at least one clinical sign of dengue, 73% knew that dengue fever was caused by the bite of dengue infected Aedes mosquitoes, 71 % correctly identified breeding sites, 69.2% correctly identified the Aedes mosquito and 42% correctly reported biting times ofthe mosquito vector. Overall, knowledge
was categorized as poor, attitude was good and dengue control and prevention practices was moderately poor. There was a weak but significant positive correlation between knowledge and practice (r=0.271, p=0.002) but there was no significant correlation between attitude with practice and between attitude with knowledge (p>0.05) . The results suggested that inspite of good attitude l
on dengue fever, it did not correlate with good practices and good knowledge in dengue prevention. We conclude that there is a need to increase health promotion activities to increase knowledge which forms the basis for preventive practices as part of the strategy to control dengue. Preventive strategies are the only means of controlling the disease.