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Showing 2 results for Heart Attack
Short-term Survival Rates after Myocardial Infractions in Iran: Meta-analysis and Systematic Review
Mitra Rahimzadeh, Behrooz Kavehie,
Volume 20, Issue 3 (6-2017)
Abstract

Abstract

Background: Heart attacks are the cause of 40% of deaths in Iran and due to its upswing in Iran and the world, the determination of its short-term survival rate in order to assess treatment methods is of great importance. The purpose of this study is to estimate patients’ short-term survival rate after heart attacks by Meta-analysis method.

Materials and Methods: This study is a systematic review. The analysis was based on data extracted from English and Persian data bases. To analyze the information obtained, including the average age of patients, and one-month and one-year short-term survival rates, the STATA 11.2 and the random effect model were used.

Results: The results of the study on 18 studies entering the Meta-analysis including 62486 patients, demonstrated that one-month and one-year short-term survival rate in Iran are respectively 87.7 and 85.2 percent and no significant difference was observed between the two genders. The average age of patients was reported 62.43 years and no significant difference was observed between the two genders in the occurance of health attack.

Conclusion: The results of this Meta-analysis showed that although the survival rate of an Iranian patient after a myocardial Infarction is the same as patients in developed countries, the average age of the patients in Iran is lower, which indicates that the load of disease in Iran is greater than in other countries regarding the years lost to the disease.


Determination of Relations between Systolic Blood Pressure and Heart Attack in Patients with Type 2 Diabetes with Association Rules
Seyyed Payam Shariatpanahi, Danial Habibi, Mohammad Rafiei, Yazdan Ghandi, Mehdi Anvari,
Volume 20, Issue 12 (3-2018)
Abstract
Abstract
Background: Today, the high prevalence of diabetes and its complications are one of the most important public health issues worldwide. For this reason, finding relations between diabetes risk factors is very effective in preventing and reducing complications. For discovering these relations, the data mining methods can be used. By extracting association rules, which is one of the data mining techniques, we can discover the relations between a large numbers of variables in a disease.
Materials and Methods: The population of this study was 1046 patients with type 2 diabetes, whose data had recorded between 2011 and 2014 at the Special Clinic for Diabetes in Tehran's Imam Khomeini Hospital. After pre-processing step with SPSS19 software, 573 people entered the analysis phase. The FP-Growth algorithm was applied to the data set to discover the relations between heart attack and other risk factors using Rapid miner5 software. Relations, after extraction, were given to the doctor to confirm clinical validation.
Results: The obtained results of studying these 573 people (Including 292 (51%) women and 281 (49%) men, with age range 27 to 82 years) showed that the lack of blood pressure, creatinine and diastolic blood pressure at its normal level, despite higher systolic blood pressure level than normal, doesn't increase the probability of heart attack.
Conclusion: Using association rules is a good way of identifying relations between the risk factors of a disease. Also, it can provide new hypotheses to do epidemiological studies for researchers.
 

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