Showing 3 results for Zeraati
M Qorbani, M Yunesian, A Fotouhi, H Zeraati, S Sadeghian, Y Rashidi,
Volume 3, Issue 1 (21 2007)
Abstract
Background & Objectives: Recent evidence suggests that long-term exposure to air pollution contributes to progression of atherosclerosis and the risk of cardiac morbidity and mortality short-term exposure may also lead to thrombosis and acute ischemic events. To evaluate the relation between the levels of major air pollutants (CO and PM10) and hospital admission for acute coronary syndrome (ACS) in Tehran, we performed a case-crossover design and checked whether individual characteristics act as effect modifiers.
Methods: We selected 250 Tehran residents who had been hospitalized with an acute coronary syndrome from 4th of April to 10th of June, 2007. The following individual data were gathered: sex, age, date of hospitalization, and coexisting illnesses (hypertension, diabetes). Daily air pollution data were taken from the Air Quality Control Center. Temperature, humidity, stress, physical activity and weekend days were treated as confounding variables, and a conditional logistic regression model was used for statistical analysis.
Results: We found a positive association between ACS and average 24-hour CO levels. The OR for each unit increase of the average 24-hour CO was 1.18 (95%CI: 1.03-1.34). The relation between ACS and 24-hour average PM10 did not reach statistical significance (OR for average 24-hour PM10 was 1.005, 95%CI: 0.99-1.01). The association between ACS and 24-hour average CO tended to be stronger in women (OR=1.68 for each unit increase, 95%CI: 1.25-2.26). The relation between 24-hour average PM10 and ACS did not change across the layers of the effect modifiers.
Conclusions: The results suggest that an increase in average 24-hour CO levels will augment the risk of ACS, and the effect is stronger in females. On the other hand, we were unable to document an association between ACS and average 24-hour PM10 levels.
Mr Ghadimi, M Mahmoodi, K Mohammad, H Zeraati, M Hosseini, A Fotouhi,
Volume 7, Issue 2 (19 2011)
Abstract
Background and Objectives: Each year almost 400,000 people are diagnosed with oesophageal cancer worldwide. Wide variation in incidence has been reported both between countries and in different ethnic groups and populations within a country. The area with the highest reported incidence for oesophageal cancer is the so-called Asian ‘oesophageal cancer belt’, which stretches from eastern Turkey through north-eastern Iran, northern Afghanistan and southern Russia to northern China. In the high risk area of Gonbad in Iran, world age-standardised rates are more than 200 per 100,000 and the male/female ratio is reported as 0.8:1.0.This study aimed to assess the risk factors and demographic factors influencing survival of patients with esophageal cancer in north of Iran using weibull and log-logistic regression models.
Methods: Demographic and clinical data of 359 patients with confirmed diagnosis of esophageal cancer from Babol Cancer registry utilized for our model. parametric and weibull models were employed to analyze the data. The Akaike information criterion (AIC) was also considered as a criterion to select the best model(s). All p values as 0.05 were considered as statistically significant.
Results: The sample study consisted of 62.7% men and 37.3% women. Estimated survival rates in 1, 3, and 5 years following diagnosis were 23%, 15%, and 13% respectively. According to AIC criterion, the hazard rate of non-monotonic and rejection proportional hazards assumption (p<0.05), log-logistic model was more efficient than weibull model. Family history of having cancer in patients showed a significant difference in both models.
Conclusion: It is concluded that early detection of people with a family history of cancer can be effective as an important factor in reducing the risk of death in patients with esophageal cancer.
M Kandi Kele , M Kadivar, H Zeraati, E Ahmadnezhad, K Holakoui Naini,
Volume 10, Issue 1 (Vol 10, No 1 2014)
Abstract
Background & Objectives : The length of stay (LOS) is a useful indicator that can be used according to the objective to improve hospital care performance. The purpose of our study was to find factors affecting infants LOS in NICU at Children's Medical Center, Imam Khomeini Hospital, Tehran University of Medical Sciences, using the Cox multiple hazards regression model.
Methods : This historical cohort study reviewed 369 medical records of all NICU admitted newborns at Children's Medical Center in 2009. The required data were collected through a data collection form. The Cox multiple hazards regression model was used to determine the factors affecting LOS in infants who were discharged on the physician‘s order.
Results: The median of stay in NICU was 9 days. Of 369 infants, 272 were discharged with improvement. The results of multiple Cox proportional hazards regression model showed the following factors were associated with LOS in the NICU: prematurity, referral from other hospitals, gastrointestinal diseases and infections, central venous catheterization, mechanical ventilation, and antibiotic therapy (P < 0.05).
Conclusion : Cox proportional hazards regression model should be used when the dependent variable is time and we have censored data. Improving prenatal health care, constructing NICU in hospitals with high risk labor, reduction of preterm birth risk factors, and improving primary health-care services can help us to reduce LOS in NICU.
