OBJECTIVES:Amputation is a multifactorial complication in diabetic patients. The aim of this study was to determine the risk factors associated with amputation in patients with diabetic foot ulcers.METHODS:This matched case-control study was conducted based on new cases of amputation from March 2012 to November 2014. We selected new cases who had undergone amputation, and the control group was chosen from the cities or areas where the cases resided. Each case was matched with two controls based on the duration of diabetes and location. Conditional logistic regression was used to evaluate the associations between potential risk factors and amputation.RESULTS:A total of 131 cases were compared with 262 controls. The results of the adjusted model showed that sex (odds ratio [OR], 8.66; 95% confidence interval [CI], 2.68 to 27.91), fewer than two hemoglobin A1c (HbA1c) tests per year (OR, 13.97; 95% CI, 4.97 to 39.26), unsuitable shoes (OR, 5.50; 95% CI, 2.20 to 13.77), smoking (OR, 3.44; 95% CI, 1.45 to 8.13), and body mass index (OR, 1.20; 95% CI, 1.03 to 1.41) were associated with amputation in diabetic patients.CONCLUSIONS:The most important factors associated with amputation were females, irregular monitoring of HbA1c levels, improper footwear, and smoking. Developing educational programs and working to ensure a higher quality of care for diabetic patients are necessary steps to address these issues.

Purpose Traffic accidents are one of the major health problems in the world, being the first cause of burden of illness and the second leading cause of death in Iran. The Sistan-Baluchestan province is one of the most accidental provinces of Iran with the highest rate of accidents-caused deaths. This study was conducted to determine the risk factors associated with traffic accidents in Zahedan through 2013 to 2016. Methods This analytical cross-sectional study was carried out on 223 drivers from Zahedan who were traumatized by traffic accident and sent to Zahedan hospitals. The data were obtained through interviews taken by the trained interviewers via refereeing to the medical records and collected in the researcher-made checklist. Census was obtained from the study subjects. For data analysis, independent t -test, one-way ANOVA, Chi-square and logistic regression were used with the Stata software version 11.0. Results In this study, 223 male subjects with the mean age of (32.54 ± 12.95) years, 39.8% single and 60.2% married, entered for investigation. Most accidents (38.8%) occurred between 12:00 to 17:59. While driving, 47.1% of the study subjects were using cell phones, 89.1% had manual use of mobile phones, 21.9% had a habit of sending short message service (SMS) and 23.4% had sent SMS within 10 min before the accident. The one way analysis of variance showed that the mean age of individuals with marital status, driving experience, education and accident with motorcycle were significantly different ( p < 0.05). Also, the multivariate logistic regression test indicated a significant relationship of smoking, ethnicity, insurance and SMS typing while driving with motorcycle accident ( p < 0.05). Conclusion In this study, SMS and smoking while driving had the highest risk among the variables studied in the motorcycle accidents. Therefore, effective education attempting to enhance people's awareness about the consequences of using cell phone and smoking during driving to reduce traffic accidents seems necessary.

Background: The World Health Organization repeatedly emphasizes the spread and association of nosocomial infections with microbial resistance. In a 2014 report, the World Health Organization cited microbial resistance as a global threat. In recent years, the world has seen the rapid growth of antibiotic-resistant E. coli in most areas, which poses a serious threat to public health. A high percentage of bacteria that cause nosocomial infections have been resistant to treatment. The most common bacterial agent among these nosocomial infections is E. coli. This bacterium is one of the main causes of nosocomial infections among hospitalized patients. One of the most important goals of the Global Antimicrobial Resistance and Use Surveillance System (GLASS) is timely identification and transmission of Emerging Antimicrobial Resistance (EAR) or outbreak of antibiotic resistance. One of the main ways to identify this "emerging" at the national or local level is to identify deviations from the expected resistance in drug compounds. As a result, if the observed cases of a drug-resistant pathogen are significantly higher than expected, it could indicate "emerging".Purpose: This study aimed to identify and transmit EAR or outbreak of antibiotic resistance among antibiotics used in the treatment of nosocomial infections caused by E. coli. This was done by comparing the observed cases of resistant E. coli with the predicted cases of resistant E. coli, which were predicted by the compartment model.Methods: This is a hospital-based study that used data from the nosocomial infection survelliance system to investigate observed cases of antibiotic resistance. In this study, the results of 12,954 antibiogram tests related to 57 hospitals located in 31 provinces of Iran were divided into two parts (results related to the first half of 2017 and results related to the second half of 2017). The model was developed in the second half of the year to predict expected cases. Before developeing model to predict the expected cases of resistant E. coli, the validity of the model was evaluated by implementing the model in the first half of the year. Finally, the predicted cases of resistant E. coli were compared with those observed in 2017. If the difference between the two was statistically significant, it indicated the outbreak of E.coli. This model evaluated 11 antibiotics recommended by the World Health Organization that are used to treat nosocomial infections caused by E. coli.Results: The results of this study showed that the outbreak of E. coli resistant to ampicillin and ceftazidime occurred in 2017 in hospitals of Iran. This means that resistance to ampicillin and ceftazidime antibiotics in nosocomial infections caused by E. coli is higher than expected and has become "emerging".Conclusion: This study showed how the outbreak of antibiotic resistance in the country's hospitals can be investigated. Using the method of this study, we can investigate the outbreak of antibiotic-resistant E. coli in the coming years and in different substrates. The results of this study showed that the administration and use of antibiotics should be reconsidered.

Background: The World Health Organization repeatedly emphasizes the spread and association of nosocomial infections with microbial resistance. In a 2014 report, the World Health Organization cited microbial resistance as a global threat. In recent years, the world has seen the rapid growth of antibiotic-resistant E. coli in most areas, which poses a serious threat to public health. A high percentage of bacteria that cause nosocomial infections have been resistant to treatment. The most common bacterial agent among these nosocomial infections is E. coli. This bacterium is one of the main causes of nosocomial infections among hospitalized patients. One of the most important goals of the Global Antimicrobial Resistance and Use Surveillance System (GLASS) is timely identification and transmission of Emerging Antimicrobial Resistance (EAR) or outbreak of antibiotic resistance. One of the main ways to identify this "emerging" at the national or local level is to identify deviations from the expected resistance in drug compounds. As a result, if the observed cases of a drug-resistant pathogen are significantly higher than expected, it could indicate "emerging".Purpose: This study aimed to identify and transmit EAR or outbreak of antibiotic resistance among antibiotics used in the treatment of nosocomial infections caused by E. coli. This was done by comparing the observed cases of resistant E. coli with the predicted cases of resistant E. coli, which were predicted by the compartment model.Methods: This is a hospital-based study that used data from the nosocomial infection survelliance system to investigate observed cases of antibiotic resistance. In this study, the results of 12,954 antibiogram tests related to 57 hospitals located in 31 provinces of Iran were divided into two parts (results related to the first half of 2017 and results related to the second half of 2017). The model was developed in the second half of the year to predict expected cases. Before developeing model to predict the expected cases of resistant E. coli, the validity of the model was evaluated by implementing the model in the first half of the year. Finally, the predicted cases of resistant E. coli were compared with those observed in 2017. If the difference between the two was statistically significant, it indicated the outbreak of E.coli. This model evaluated 11 antibiotics recommended by the World Health Organization that are used to treat nosocomial infections caused by E. coli.Results: The results of this study showed that the outbreak of E. coli resistant to ampicillin and ceftazidime occurred in 2017 in hospitals of Iran. This means that resistance to ampicillin and ceftazidime antibiotics in nosocomial infections caused by E. coli is higher than expected and has become "emerging".Conclusion: This study showed how the outbreak of antibiotic resistance in the country's hospitals can be investigated. Using the method of this study, we can investigate the outbreak of antibiotic-resistant E. coli in the coming years and in different substrates. The results of this study showed that the administration and use of antibiotics should be reconsidered.

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