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Causes of Infant Mortality in Kalaleh City During 2004-2012
Abed Nouri, Leila Barati, Farzad Qhezelsofly, Sedighe Niazi,
Volume 1, Issue 2 (10-2013)
Abstract

Background and objectives:

Almost 130 million infants are born each year, more than 8 million of whom

die before their first year of life. In the developing countries, two thirds of these deaths occur in the first month

of their life. Reduced infant mortality is among the Millennium Development indicators, and this rate is high

in Kalaleh city. This study aimed to identify the most common causes of infant death, so that the avoidable

deaths be prevented by offering intervention plans.

Methods:

information was collected with the designed form. The data were, then, coded and entered into the SPSS 17

software, and analyzed using independent statistical chi-square test.

In this study, all causes of infant death in Kalaleh city during 2003-2013 were investigated. The

Results:

prematurity (47.42%), congenital abnormalities (22.42%), and disasters and accidents (9.79%). 82.73%

of the infants weighed below 2500 g. 60% of the prematurity deaths occurred to primigravid women. There

388 infant deaths accounted for 83% of under-5 mortality. The most common causes of death include

was a statistically significant relationship between primigravity and prematurity infant death with a 95% confidence

(P=0.003). 74.74% of the infant deaths occurred in the first week, and 58.96% in the first 24 hours.

Conclusion:

As 38.4% of the infant deaths occurred in the first pregnancy, and 60% of prematurity deaths

happened to primigravid women, and there was a relationship between primigravity and prematurity infant

deaths, the importance of the particular care of these mothers comes into sight. Planning for teaching the im

of caring the primigravid mothers and making their families more sensitive about the significance of

portance

caring these mothers can be effective in reducing premature infant mortality.


Determination of the Distribution Pattern of Mortality Using Data Mining Technique in Golestan Province since 2007 to 2009
Fatemeh Bagheri, , ,
Volume 3, Issue 2 (10-2015)
Abstract

Background and objectives: Investigatingg the mortality in a population has been considered as one of the appropriate methods of health detection. Although, there are some problems such as lack of confidence in accuracy measurement and quality of data collection. Establishment of death registration systems and using international classification codes of diseases, and also mortality data integrating by responsible organizations have solved great parts of the previous problems. In this study, considering a set of parameters, the study population was divided into two groups: deceased under one year (infants) and over one year (adults).  Then both groups were clustered using the K-means method to identify different groups. Hidden models and useful patterns were also discovered using decision tree algorithms. Finally, a neural network algorithm was used to show the ranking of attributes in order of their importance.

Methods: In this research, data of 12,865 deceased individuals in Golestan province since 2007 to 2009 is studied. The data has been obtained from the Health Center of Golestan province. The main characteristics used in this study are: deceased age, gender, cause of death, place of residence and place of death. K-means algorithm is used to cluster data. The decision tree algorithms and neural networks algorithm were also used for classification. Finally, results and rules were extracted. Due to different natures of causes of death in infants and adults, studying on these different groups is performed separately.

Results: In clustering phase, the optimal number of clusters is obtained by Dunn index; eight clusters for infants and seven clusters for adults were obtained. Among four decision-tree algorithms (C5.0, QUEST, CHAID and CART), C5.0 algorithm with high correction rate, 77.37% in infants data and 96.86% in adults data was the best classifier algorithm. Age, gender and place of death were the most important variables that were detected by neural network algorithm.

Conclusion: In the present study, the collected mortality data was clustered by considering the effective factors and the standard of International Classification of Diseases. The hidden patterns of mortality for infants and adults were extracted. Due to the explicit nature and the intelligibility of the decision tree algorithms, the results and extracted rules are very useful for specialists in this field.


Epidemiological Study of the Suburban Accident Mortalities Recorded in Golestan, Iran in 2015
Farzaneh Afkhaminia, Dr Jamshid Yazdani Charati, Elaheh Rahimi, Dr Nourodin Mousavi Nasab,
Volume 6, Issue 1 (3-2018)
Abstract
Background and objectives: Road accidents are one of the most important causes of mortality and severe physical and psychological damage which may lead to adverse social, cultural and economic consequences in the human community. Frequency and severity of road accidents in developing countries are noticeably higher in comparison to developed countries. In Iran, 25% of casualties are due to the abnormal deaths caused by road accidents. It is estimated that more than 22,000 people die due to road accidents every year. The present study aimed to epidemiologically investigate the mortality rate of suburban accidents in Golestan province, Iran.
Methods: This cross-sectional study was conducted using a descriptive approach. Required data were obtained from the traffic police of Golestan province. In total, 2,922 cases of road accidents were investigated in Golestan province in 2015. The analyzed data included the demographic characteristics of the deceased and the environmental and geographical conditions of the accident. Data analysis was performed in SPSS version 20.
Results: Among 2,922 road accidents in Golestan province, 251 cases led to the death of 317 individuals. Most of the accidents leading to death were by automobiles (69.7%) and due to distraction from the road (33.1%), which occurred on main roads (47.8%). Moreover, 29.7% of guilty drivers had not fastened seatbelts. Motorcycle riders and car passengers accounted for the highest percentage of accident victims (30.6% and 25.5%, respectively).
Conclusion: Education and emphasis on the use of seatbelts and motorcycle helmets while driving seem essential to reducing the injuries caused by road traffic accidents. Considering that most road accidents occur due to the distraction of the driver from the road, changing traffic behaviors to improve discipline is of paramount importance.
A Survey for Predictors of Mortality among COVID-19 Patients: A Retrospective Study from Iran
Arezoo Monfared, Mohammad Taghi Moghadamnia, Samad Karkhah, Saman Maroufizadeh, Mohammad Asadian Rad, Jalal Kheirkhah, Fatemeh Jafaraghayee,
Volume 9, Issue 4 (12-2021)
Abstract
Background and Objective: In the current COVID-19 pandemic, disease diagnosis is essential for optimal management and timely isolation of infected cases in order to prevent further spread. The aim of this study is to assess of predictors of mortality among COVID-19 patients.
Material and Methods: In a retrospective study, 522 COVID-19 patients were enrolled in Razi hospital, Guilan Province, Iran. This hospital was the main center for the treatment of COVID-19 patients in Guilan province. Data gathering was performed by census sampling from March to August 2020. Simple and Multiple logistic regression analysis was applied to assess the relationships of clinical and demographic characteristics with in-hospital mortality.
Results: Multiple logistic regression showed that older age (aOR=1.04, 95%CI: 1.02 to 1.06, P<0.001), decreased O2 saturation (aOR=0.89, 95%CI: 0.86 to 0.92, P<0.001), having a dysrhythmia (aOR=2.97, 95%CI: 1.46 to 6.05, P=0.003), symptoms associated with heart failure (aOR=0.43, 95%CI: 0.18 to 0.99, P=0.048), and mixed drug antiviruses (aOR=2.44, 95%CI: 1.22 to 4.90, P=0.012) were mortality predictor variables among COVID-19 patients.
Conclusion: Therefore, special attention should be paid to the factors influencing the mortality of COVID-19 patients. It is recommended that older patients, dysrhythmia, and symptoms associated with heart failure be treated with extreme caution.

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