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1.
Article | IMSEAR | ID: sea-203501

ABSTRACT

Background: The proper treatment of Avascular Necrosis(AVN) of Femoral Head has become a major challengeworldwide in younger age group as they are main effectiveforce of family and society. The patients who are young andsuffer from AVN of femoral head become immovable, worklessand unproductive. Thus they become burden to family andsociety. The Hip Replacement is a better way of treatment forthis type of patients, making them pain free and movable andimproving their everyday activity.Objective: To evaluate outcome of non-cemented total hiparthroplasty in avascular necrosis of femoral head among theactive younger age group of patients.Method: This was a prospective observational study of 30patients and all the patients had done non-cemented total hiparthroplasty (THA) through lateral approach at the NationalInstitute of Traumatology and Orthopaedic Rehabilitation(NITOR), Dhaka.Results: Mean age of the patients was 32 ±5.12 years,patients were diagnosed as Avascular Necrosis of FemoralHead in which 63% were affected at Right sided Hip 37%patients were at Left sided hip. Final outcome after six monthsof operation evaluated with Modified Harris Hip Score revealedthat, there was significant (p<0.005) improvement in functionalability of the patients after THA. Among the 30 studied cases,21 (70%) patients carried slight pain and 63.4% of them wereable to walk unlimitedly. Outcome of supporting functionanalysis indicated 76.7% patients could walk and climb stairswithout support and 100% patients could sit on chair, 66.7%patients among them could walk without limping. On clinicalassessment of deformity, range of motion before and afteroperation, significantly resolved the deformities and increasedthe range of motion (2100-2300). After evaluation with ModifiedHarris Hip Score showed that 60% excellent (HHS 90-100),30% good (HHS 80-89), 10% had fair (HHS 90-100) outcome.Conclusion: The progressive study of the patients of THAshowed that non-cemented THA has resulted in a better wayamong the younger age group of people

2.
Article in English | IMSEAR | ID: sea-144656

ABSTRACT

Background & objectives: Transmission of dengue virus depends on the presence of Aedes mosquito. Mosquito generation and development is known to be influenced by the climate. This study was carried out to examine whether the climatic factors data can be used to predict yearly dengue cases of Dhaka city, Bangladesh. Methods: Monthly reported dengue cases and climate data for the years 2000–2008 were obtained from the Directorate General of Health Services (DGHS) and Meteorological Department of Dhaka, Bangladesh, respectively. Data for the period 2000 to 2007 were used for development of a model through multiple linear regressions. Retrospective validation of the model was done with 2001, 2003, 2005 and 2008 data. Log transformation of the dependent variable was done to normalize data for linear regression. Average monthly humidity, rainfall, minimum and maximum temperature were used as independent variables and number of dengue cases reported monthly was used as dependent variable. Accuracy of the model for predicting outbreak was assessed through receiver operative characteristics (ROC) curve. Results: Climatic factors, i.e. rainfall, maximum temperature and relative humidity were significantly correlated with monthly reported dengue cases. The model incorporating climatic data of two-lag month explained 61 per cent of variation in number of reported dengue cases and this model was found to predict dengue outbreak (≥ 200 cases) with considerable accuracy [area under ROC curve = 0.89, 95%CI = (0.89-0.98)]. Interpretation & conclusions: Our results showed that the climate had a major effect on the occurrence of dengue infection in Dhaka city. Though the prediction model had some limitations in predicting the monthly number of dengue cases, it could forecast possible outbreak two months in advance with considerable accuracy.


Subject(s)
Bangladesh/epidemiology , Cities/epidemiology , Climate , Dengue/epidemiology , Dengue/transmission , Disease Outbreaks/statistics & numerical data , Humans , Linear Models , Models, Biological , Predictive Value of Tests , ROC Curve , Seasons
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