Tehran University Medical Journal

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Difference aspects of multinomial statistical modelings and its classifications has been studied so far. In these type of problems Y is the qualitative random variable with T possible states which are considered as classifications. The goal is prediction of Y based on a random Vector X ? IR^m. Many methods for analyzing these problems were considered. One of the modern and general method of classification is Classification and Regression Trees (CART). Another method is recursive partitioning techniques which has a strange relationship with nonparametric regression. Classical discriminant analysis is a standard method for analyzing these type of data. Flexible discriminant analysis method which is a combination of nonparametric regression and discriminant analysis and classification using spline that includes least square regression and additive cubic splines. Neural network is an advanced statistical method for analyzing these types of data. In this paper properties of multinomial logistics regression were investigated and this method was used for modeling effective factors in selecting contraceptive methods in Ghom province for married women age 15-49. The response variable has a tetranomial distibution. The levels of this variable are: nothing, pills, traditional and a collection of other contraceptive methods. A collection of significant independent variables were: place, age of women, education, history of pregnancy and family size. Menstruation age and age at marriage were not statistically significant.

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Background: Colorectal carcinoma is considering as a curable disease. Treatment of recurrent cases is hard and sometimes impossible. Evaluation of the rate and affecting factors of recurrence in each hospital would help to decreasing recurrent cases. The aim of this study is evaluation of the rate, clinical and pathologic features, and outcome of recurrent colorectal carcinoma in a referral teaching hospital in Tehran. Methods: Clinical data of 166 curative resections of colorectal carcinoma who were operated between Mehr 1384 and Mehr 1388 (between 23 September 2005 and 23 September 2009) in Imam Khomeini Hospital and were accessible for follow up was collected. Follow up data was collected prospectively up to Farvardin 1391 (19 April 2012). Forty nine recurrences were happened in this period. We compared recurrent and non-recurrent cases for different variables Results: Average age of the patients was 53.5 years, and 47% of them were female. The median time to the diagnosis of recurrent disease was 12 months (range 1 months to 54 months). There were no significant differences between recurrent and non-recurrent patients about age, sex, sub-site of the tumor and sub-type of primary operation. Rate of overall recurrence, local recurrence and distant metastasis were 29.5%, 15.7% and 12.1% respectively. Local recurrence rate was higher in colon cancer (16.44% vs. 15.05%) but distant metastasis rate was higher in rectal cancer (12.9% vs. 10/96%). Rate of curative re-resection was about 25%. Overall survival of the recurrent patients who underwent surgery was better than who underwent chemo or radiotherapy (66.7% vs. 56.8%). Median survival time of recurrent patients after primary surgery was 28 months, and after diagnosis was 12 months (9.28- 14.72,95% CI). Conclusion: In this study the rate of overall recurrence was 29.5%. Local recurrence rate was higher in colon cancer (16.44% vs. 15.05%) but distant metastasis rate was higher in rectal cancer (12.9% vs. 10/96%).

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Background: Diarrhea is the most common bacterial infections, and the main cause of death in the children. Worldwide, food and waterborne diseases are estimated to cause more than two million deaths per year. Foodborne diseases and resistance to antimicrobial agents are two problems worldwide and are increasing. However, standard surveillance systems do not routinely collect information on controls. The aim of this study was to analysis epidemiological data of foodborne outbreaks at the country level. Methods: This is a descriptive study, in total 305 fecal swab samples from 73 outbreaks during one year from April 2012 to March 2013 in different provinces of Iran, were collected and transferred to the microbiology laboratory of Public Health School of Tehran University of Medical Sciences to identify the cause’s diarrhea. The patterns of antibiotic-resistance were determined by using Kirby Bauer method. Results: In total 73 food borne outbreaks that were studied, the largest number 26 (35.6%) were found in Hamadan province with 103 samples (34.2%). Out of 73 outbreaks 40 (54.79%) of were related to foods, 6 (8.22%) to water, and 27 (36.98%) were unspecified (P< 0.0001). Fifty seven outbreaks (78.08%) in the city and 16 outbreaks (21.92%) occurred in rural areas (P< 0.0001). The most dominated Gram-negative isolated organisms were Shigella (6.9%) and Gram-positive bacteria Staphylococcus aureus (12.8%). The dominated age group was under five years (16.4%), and dominant gender group was men 186 (61.8%) (P< 0.0001). In total 69 (22.9%) were hospitalized and 11 deaths were reported. Most clinical symptoms of abdominal cramping (82%), nausea and vomiting (68.4%), bloody diarrhea (23.3%), and non-bloody diarrhea (76.7%). All the isolated gram-negative were sensitive to ciprofloxacin and resistant to clindamycin. The gram-positive were sensitive to cephalexin and resistant to penicillin. Conclusion: The knowledge of bacterial agent of foodborne diseases and determination of antimicrobial resistance pattern are helpful to reduce the rate of foodborne outbreaks, the cost of treatment. The prevention control of outbreaks is also very important.

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Background: Warfarin is one of the most common oral anticoagulant, which role is to prevent the clots. The dose of this medicine is very important because changes can be dangerous for patients. Diagnosis is difficult for physicians because increase and decrease in use of warfarin is so dangerous for patients. Identifying the clinical and genetic features involved in determining dose could be useful to predict using data mining techniques. The aim of this paper is to provide a convenient way to select the clinical and genetic features to determine the dose of warfarin using artificial neural networks (ANN) and evaluate it in order to predict the dose patients.

Methods: This experimental study, was investigate from April to May 2014 on 552 patients in Tehran Heart Center Hospital (THC) candidates for warfarin anticoagulant therapy within the international normalized ratio (INR) therapeutic target. Factors affecting the dose include clinical characteristics and genetic extracted, and different methods of feature selection based on genetic algorithm and particle swarm optimization (PSO) and evaluation function neural networks in MATLAB (MathWorks, MA, USA), were performed.

Results: Between algorithms used, particle swarm optimization algorithm accuracy was more appropriate, for the mean square error (MSE), root mean square error (RMSE) and mean absolute error (MAE) were 0.0262, 0.1621 and 0.1164, respectively.

Conclusion: In this article, the most important characteristics were identified using methods of feature selection and the stable dose had been predicted based on artificial neural networks. The output is acceptable and with less features, it is possible to achieve the prediction warfarin dose accurately. Since the prescribed dose for the patients is important, the output of the obtained model can be used as a decision support system.

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Background: Burns and its complications are regarded as a major problem in the society. Skin injuries resulted from ultraviolet radiation, radioactivity, electricity or chemicals as well as respiratory damage from smoke inhalation are considered burns. This study aimed to determine the epidemiology and outcome of burn patients admitted to Motahari Hospital, Tehran, Iran.

Methods: Two hundred patients with second-degree burns admitted to Motahari Referral Center of Burn in Tehran, Iran. They were studied during a period of 12 months from May 2012 to May 2013. During the first week of treatment swabs were collected from the burn wounds after cleaning the site with sterile normal saline. Samples were inoculated in blood agar and McConkey agar, then incubation at 37 C for 48 hours. Identification was carried out according to standard conventional biochemical tests. Treatment continued up to epithelial formation and wound healing. Results of microbial culture for each patient was recorded. Healing time of the burn wounds in patients was recorded in log books. Chi-square test and SPSS Software v.19 (IBM, NY, USA) were used for data analysis.

Results: Our findings indicate that the most causes of burns are hot liquids in 57% of cases and flammable liquid in 21% of cases. The most cases of burns were found to be in the range of 21 to 30 percent with 17.5% and 7% in male and female respectively. Gram-negative bacteria were dominated in 85.7% and among them pseudomonas spp. with 37.5% were the most common cause of infected burns, followed by Enterobacter, Escherichia coli, Staphylococcus aureus, Acinetobacter and Klebsiella spp.

Conclusion: The results of this study showed that the most cause of burns in both sex is hot liquid. Men were more expose to burn than women and this might be due to the fact that men are involved in more dangerous jobs than female. Pseudomonas aeruginosa was the most common organism encountered in burn infection.

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