Vol 2 No 3 (2016)

Original Article(s)

  • XML | PDF | downloads: 287 | views: 539 | pages: 111-117

    Background & Aim: Stroke is the second common cause of deaths and the third common cause of disability-adjusted life years worldwide in 2010, so knowledge of risk factors within a certain country is an essential step in reducing the stroke rate and resulting disease burden .
    Methods & Materials: This was a case–control study to determine and assess risk factors influencing ischemic stroke. In this study, 72 stroke patients hospitalized in Firoozgar Hospital of Tehran city for ischemic stroke from June 2012 to September 2013 were considered as a case group, and 72 individuals were selected as a control group that referred to the same laboratory of the hospital due to the causes other than risk factors for cardiovascular disease. The association between various risk factors such as history of cardiovascular disease, hypertension, diabetes mellitus, migraines, and stroke has been investigated. Multivariate regression analysis was implemented to estimate the odds ratio (OR) of each risk factor for stroke events.
    Results: Findings showed that according to multivariate logistic regression, factors such as a history coronary heart disease (OR = 23.33, P = 0.002) and hypertension (OR = 6.9, P = 0.001), low high-density lipoprotein (HDL) (OR = 6.84, P < 0.001), history of coronary heart disease, and cerebrovascular disease in first degree relatives (OR = 4.18, P = 0.007), have been identified as a predictor of ischemic stroke.
    Conclusion: Following this hospital-based study of Iranians, we demonstrated that among various risk factors, history of coronary heart disease, hypertension, as well as low HDL, and history of coronary heart disease and cerebrovascular disease in first degree relatives are the strongest independent predictors of stroke.

  • XML | PDF | downloads: 288 | views: 551 | pages: 118-124

    Background & Aim: There are some ambiguities in assessment of associations between continuous risk factors and different health outcomes usually from different cut points. Data loss, near to the cut point values different categorization, and no real definition of risk are important limitations for usual odds ratios (ORs). Fuzzy method considers a specific membership function for all numbers in range of the variable and can provide a similar OR. In this study, we used a large data set for these different measures calculation and making a comparison between them according to their privileges.
    Methods & Materials: The study was conducted on noncommunicable diseases risk factors surveillance data set (National Surveillance of Risk Factors of Non-Communicable Diseases-2007) with regard to obesity and abdominal (central) obesity as risk factors for hypertension according to a “fuzzy risk factor” approach and usual approach based on regular cut points in different literature. OR of chances to have hypertension calculated by both methods and compared with each other.
    Results: ORs with usual and fuzzy methods of calculations had similarities and some differences in amount, confidence interval and confidence length. With different cut points (for waist circumference), variation between different calculations was high. Fuzzy OR was more sensitive and resistant to minor change in individual data than the others.
    Conclusion: OR{Fuzzy} measures the association of exposure to risk factors with different outcomes in a closer form of clinical reality with no dependency to any cut point selection, less variability and more resistance to data variation and can be suggested as a good estimator.

  • XML | PDF | downloads: 202 | views: 307 | pages: 125-129

    Background & Aim: It is important that clinicians understand statistical methods into their own research and correctly apply in their research. The main objective of this study is to explore the study designs, statistical methods used and the issue of inaccuracy and inappropriate usage of statistical methods in the research publications of the specialty of general medicine as evidenced by five selected journals over a 10-year period and improvements thereof.
    Methods & Materials: Originally published articles were reviewed of the journals of specialty of general medicines for the above-defined objective (list of journals: Indian Journal of Medical Research, Indian Journal of Critical Care, Indian Journal of Nephrology, Journal of the Association of Physicians of India, and New England Journal of Medicine were reviewed). Qualitative data represented by percentage, Z-test of proportion applied at 95% level of significance.
    Results: The usage of some statistical methods in 2003 was 61.54% which increased to 79.26% by 2013. Only 2.19% research article had mentioned the concept of study design in 2003 which increased to 10.56% by 2013. There was a greater usage of statistical concepts and methods such as parametric and nonparametric tests, regression, survival analysis in 2013 as compared to 2003. There was a significant improvement observed in the usage of statistical software over a 10-year period. A common error observed was the usage of standard error instead of standard deviation to present the data and we found that there was a vast improvement in the use of advanced statistical methods over the decade.
    Conclusion: This study highlights the increasing importance of medical statistics in the research publications pertaining to the specialty of general medicine over time so that the inferences drawn from these studies are actually representative of the population that they represent and are valid and reliable. These concepts are of paramount importance while physicians read these articles and try to adopt their recommendations.

  • XML | PDF | downloads: 280 | views: 652 | pages: 130-135

    Background & Aim: Consider a sequence of independent Bernoulli trials with p denoting the probability of success at each trial. With this definition, the probability that the nth success proceed by r failures follows the negative binomial distribution (NB). NB model has been derived from two different forms. At first, the NB can be thought as a Poisson-gamma mixture. The second form of the NB can be derived as a full member of a single parameter exponential family distribution, and therefore considered as a GLM (generalized linear models).
    Methods & Materials: We have described a new generalized NB (GNB) distribution with three parameters α, β and k obtained as a compound form of the generalized Poisson and gamma distributions. This distribution gives a very close fit for a large number of data and provides an appropriate model for numerous studies. The most important feature of this model is, its time dependent probabilities, and also it can be used for a variety of researches especially in the survival analysis.
    Results: This model has been illustrated with two datasets that are indirect measures of illness, along comparing the results of the fitting with NB. Results indicate too much satisfaction. Expected frequencies have been calculated for these data sets to show that the distribution provides a very satisfactory fit in different situations.
    Conclusion: Using GNB models allows analyzing very complex data. This distribution gives a very close fit for a large number of data and provides an appropriate model for numerous studies. With k = 0 the model becomes the ordinary NB and with α = 1, it becomes a new model which we call it the generalized geometric distribution with two parameters. The most important feature of this model is its time-dependent probabilities.

  • XML | PDF | downloads: 198 | views: 368 | pages: 136-142

    Background & Aim: Visceral leishmaniasis (VL) or kala-azar is a protozoan disease caused by some species of Leishmania donovani complex. Mediterranean type of the disease is endemic in various parts of Iran. A cross-sectional study was designed to determine the seroprevalence of VL among asymptomatic adult population in Meshkin-Shahr area from the Northwest of Iran as an endemic focus of VL.
    Methods & Materials: Altogether, 180 blood samples were collected from asymptomatic adults’ population throughout 2015. Before sampling, a questionnaire was separately completed for each individual. All the collected blood samples were examined by direct agglutination test (DAT) after plasma separation. Anti-Leishmania infantum antibodies at titers 1:100 to 1:1600 was considered as L. infantum infection, while the cut-off titer of ≥ 1:3200 with specific signs and symptoms was considered as VL.
    Results: From 180 collected plasma samples, nine (5%) of them showed anti-Leishmania antibodies at titers 1:400 and higher. Distribution of anti-Leishmania antibodies titers was 1:400 (n = 2), 1:800 (n = 4), and 1:1600 (n = 3). All of the seropositive cases were observed among females. All the seropositive individuals had not a history of kala-azar. The highest seropositivity rate was observed among the age group of 13-23 years old. No changes in titers of anti-Leishmania antibodies observed after collected the seropositive blood samples again and tested by DAT with 1-month interval.
    Conclusion: Visceral Leishmania infection is relatively high among adult people reside in Meshkin-Shahr area without any clinical manifestations. Asymptomatic VL infection is very important in immunocompromized individuals such as HIV-positive cases; these patients are at risk to manifesting clinical signs and symptoms of VL. Therefore continuing serological surveillance for detection of visceral Leishmania infection should be recommended in the endemic foci of VL.

  • XML | PDF | downloads: 237 | views: 533 | pages: 143-151

    Background & Aim: Geographical analysis of the frequency of disease incidence can have an important role in the allocation of resources, facilities, and manpower in addition to the formulation and evolution of etiological assumptions. The main objective of this study was to estimate the prevalence of neck pain interprovincially, and set a disease mapping using spatial Besag, York and Mollie (BYM) with regard to surrounding neighborhoods. To reduce the incidence of neck pain in adulthood, identification of risk factors that predict the onset, and continuation of pain in the patients is important.
    Methods & Materials: The population examined in this study was extrapolated from records of the “National Disease and Health Survey in Iran,” which had a data plan of a general population survey conducted during 1999-2000, in which adults responded on the incidence of neck pain. The participants were guided by a questionnaire that had an image on which they could identify the exact location of the pain.
    Results: Explanatory variables in the model included sex, education level, area of residence, smoking, age and body mass index, and all of them showed a significant relationship with neck pain. To have a better model for a more reliable prediction, we grouped the provinces into divisions to have a more regular shape since the spatial BYM model cannot simultaneously account for population and spatial patterns. In neck pain, prevalence estimated by spatial BYM, Lorestan province with 7.85% had the lowest prevalence while Kurdistan province with 17.27% had the highest prevalence. Furthermore, in the male population, Ghazvin province with 5.53% had the lowest prevalence, whereas Kurdistan province with 10.33% had the highest prevalence of neck pain. Besides, in the female population, the Lorestan province with 10.33% had the lowest prevalence, while the province of Yazd with 22.45% has the highest prevalence of neck pain.
    Conclusion: In this study, the model assumed included measurable and immeasurable factors to provide reliable estimates for each province. The application of spatial BYM method with the inclusion of the location of disease occurrence is a more efficient and reliable method for diseases mapping with a higher power of predictability.

  • XML | PDF | downloads: 230 | views: 389 | pages: 152-157

    Background & Aim: Time series analysis is used to detect a model and predict the future amounts of the series, which is based on previous data. One of the commonly used models in time series is autoregressive integrated moving average (ARIMA) model. 30% of diseases in children are acute leukemia, out of which acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) consist 97% of acute leukemia types. In this study which is a modeling study, the ARIMA time series model is fitted on the acute leukemia cancer in children and the best model is selected.
    Methods & Materials: This study which is related to the children with cancer ALL and AML, and includes age groups from 1 year old to 15 years old, the ARIMA time series model is fitted on these data, and the best model is selected based on the Akaike information criteria. Trend analysis was also conducted based on the criteria R2 and mean squared error, mean absolute deviation, and mean absolute percentage error were considered as the best equations for the series.
    Results: ARIMA models are investigated, and the best model is selected and also it was shown that the procedure of catching blood cancer has been increasingly from 82 to 88 and then decreasingly but it may get an increasing procedure in the future. Furthermore, the procedure was shown in two sexual groups and it was observed that catching blood cancer had a decreasing procedure in men and had an increasing procedure in women and appropriate ARIMA model was also determined for each group.
    Conclusion: According to the forecasts for the next 10 years, the incidence of this cancer will be increasing in the future. There was an increasing trend for female group and a downward trend for male group.