Showing 10 results for Risk
Seyed Abedein Hosseini, Ali Akbar Abdollahi, Naser Behnampour, Aref Salehi,
Volume 6, Issue 5 (1-2013)
Abstract
Background and Aim: Despite the information regarding CAD risk factors, there isn't agreement between the relation of this risk factors and coronary artery diseases. This study was done for determination of related factors with vessels involved in coronary artery angiography.
Materials and Methods: In this descriptive and analytical study, 2390 patients' .were selected via census sampling from Kosar Angiography center in the Golestan province. Data gathering form included data such as age, gender, body mass index (BMI), blood pressure, diabetes, smoking and opiates addiction history. Vessels involved were determined by angiography. Data analysis was done with one way ANOVAs and logistic regression using SPSS 16 soft ware.
Results: Mean and standard deviation of patient's age was 57.9±10. 58.2 percent of them were male. There were significant correlations between age, gender and BMI with numbers of vessels involved. Male gender(OR=1.329), hypertension (OR=1.25) and diabetes(OR=1.20) increased the probability of more than one vessels involvement. Regression analysis showed there were no significant correlations between age, BMI, smoking and opiates addiction history with more than one vessels involvement.
Conclusion: Our finding confirmed that male gender, hypertension and diabetes are the main risk factors in involvement of more than one vessel.
Mostafa Langarizadeh, Rozi Mahmud,
Volume 8, Issue 3 (9-2014)
Abstract
Background and Aim: The risk of breast cancer increases directly in line with breast density. Therefore, it is important to pay more attention to denser breasts in order to detect abnormalities. The aim of this paper was to design and suggest a quantitative method to categorize breast density in digital mammogram images using fuzzy logic.
Materials and Methods: This was a crosectional study which resulted in developing a new system. The research population was including patients who undergo mammography in National Cancer Society of Malaysia during 2010 to 2011. Sample included 220 mammogram images which was selected randomly. Data analysis was done using SPSS with Kappa statistics.
Results: Accuracy level of 92.8% was obtained based on evaluation of the system and there was a strong correlation between the system output and radiologists’ estimation (K=0.87, p=0.0001).
Conclusion : Results obtained from the suggested system had higher performance than similar systems. Therefore, it could be concluded that the fuzzy logic may be used in this area. In addition, such systems could be helpful for physicians.
Mahan Mohammadi, Fatemeh Rahi, Marzieh Javadi, Golrokh Atighechian, Alireza Jabbari ,
Volume 11, Issue 2 (7-2017)
Abstract
Background and Aim: Almost one out of 10 patients who are admitted in hospitals experience “never events” while researches show that about half of these harms are preventable through the utilization of Failure Modes and Effects Analysis (FMEA). This study aims to identify and evaluate the risks of care processes in three wards of Alzahra University Hospital of Isfahan and suggest some interventions for reducing these risks.
Materials and Methods: This was a cross-sectional study, which identified high-risk processes using FMEA in respiratory, gastroenterology and rheumatologic wards of Alzahra Hospital during the years 2014-2015. The study population comprised clinical staff members who worked in these three wards and were familiar with clinical care processes. The focus group team was selected through purposive sampling method. Finally, the information was gathered in standard FMEA work sheets and analyzed with SPSS software.
Results: A total of 72 clinical care processes were identified, and the 73.5% of the focus group members rated "blood and its products transfusion process" as the most risky care process. The step "checking the incompatible of patient's information and blood lable and its products" was the most dangerous step (with PRN = 300). The findings showed that human and equipment failures were the main reasons of facing the “never events” in these wards.
Conclusion: Risk management tells us that the efficiency and quality of care can be promoted by preventing errors through human resource training and proper maintenance of medical equipment.
Reza Safdari, Leila Shahmoradi, Marjan Daneshvar, Elmira Pourtorkan, Mersa Gholamzadeh,
Volume 12, Issue 1 (5-2018)
Abstract
Background and Aim: The Ovarian epithelial cancer is one of the most deadly types of cancers in women.Thus, the purpose of this study was to investigate the most effective factors in predicting and detecting Ovarian cancer in the form of a decision tree to facilitate the Ovarian cancer diagnosis.
Materials and Methods: The present study was a descriptive-developmental study. The main research tool applied in this study was a checklist which was designed based on the medical records, published studies, scientific references, and expert consultation.To determine the content validity of the checklist, the CVR method was applied. Next, survey research was done with aid of Likert-based checklist based on expert opinions in gynecology. Finally, to develop the decision tree, the results of the expert survey were analyzed and the final model was implemented based on the survey results.
Results: The data elements of final decision tree were derived from the result of expert surveys, guidelines, clinical pathways and strategies in context of diagnosis and screening of Ovarian cancer. The leaf nodes in the tree include different types of tumor markers, following up, therapeutic measures, and referrals. The accuracy of the decision tree was approved by the experts. The most important tumor markers that obtained from the decision model in this study were CA19-9, ROMA (CA125 + HE4) and CEA.
Conclusion: Clinical decision models can provide specific diagnosis and therapeutic suggestions by creating patient information integration framework. The model developed in this study can improve the diagnosis of epithelial Ovarian cancer considerably by facilitating decision making.
Atefeh Sadat Haghighat Hoseini, Hossein Bobarshad, Fatemeh Saghafi, Iman Noroozi,
Volume 12, Issue 2 (7-2018)
Abstract
Background and Aim: The emergence of Web interactive technologies has enabled interactive social networking services. The purpose of this research is to choose a model and present an architectural design for the social network of health at Shariati Hospital in Tehran.
Materials and Methods: At first, valid enterprise architecture frameworks were reviewed. Then, dimensions of the architecture frameworks needed for the social network of health were reviewed and six dimensions including of input, output, goals, views, abstraction, and system life cycle were selected. Architecture frameworks were prioritized on the basis of these six dimensions and the Zachman framework was selected. The extracted elements for these dimensions were evaluated by using a researcher-made questionnaire and experts’ opinion in the t-test. The questionnaire was distributed among 40 health-care information technology experts. After analyzing and verifying the dimensions and sub-indicators of each dimension, probable risks for the implementation of the health social network were identified based on interviews with experts and were approved by a panel of five experts.
Results: The Zachman framework was selected based on six dimensions as a suitable framework and potential implementation risks were identified.
Conclusion: The results showed that the proposed architecture model could be the basis for the implementation of this network in the country. Attention to extracted risks can minimize the failure of the implementation of the health social network.
Azita Yazdani, Ali Asghar Safaei, Reza Safdari, Maryam Zahmatkeshan,
Volume 13, Issue 3 (9-2019)
Abstract
Background and Aim: Breast cancer is the most common type of cancer and the main cause of death from cancer in women worldwide. Technologies such as data mining, have enabled experts in this area to improve decision making in the early diagnosis of the disease. Therefore, the purpose of this research is to develop an automatic diagnostic model for breast cancer by employing data mining methods and selecting the model with the highest accuracy of diagnosis.
Materials and Methods: In this study, 654 available patient records of Motahari breast cancer Clinic in Shiraz" were used as the sample. The number of records was reduced to 621 after the pre-processing operation. These samples had 22 features that ultimately used ten were used as effective features in the design of the model. Three types of Decision tree, Naive Bayes and Artificial neural network were used for diagnosis of breast cancer and 10-fold cross-validation method for constructing and evaluating the model on the collected data set.
Results: The results of the three techniques mentioned all three models showed promising results in detecting breast cancer. Finally, the artificial neural network accounted for the highest accuracy of 94/49%(sensitivity 96/19%, specificity 86/36%) in the diagnosis of breast cancer.
Conclusion: Based on the results of the decision tree, the risk factors such as age, weight, Age of menstruation, menopause, OCP of records duration, and the age of the first pregnancy were among the factors affecting the incidence of breast cancer in women.
Vahid Changizi, Mohammad Reza Zare, Sahel Kasiri,
Volume 13, Issue 5 (1-2020)
Abstract
Background and Aim: Due to the presence of ionizing radiation sources in the environment and their potential to enter the food chain, the natural radiation in the rice product of Mahmoud Abadu residents of this area should be evaluated.
Materials and Methods: Using standard sampling methods, the number of sampling points and locations (about 10 points) was determined. After recording the geographical location of the sites, 2 kg of soil and 2 kg of rice were removed and 20 samples were coded. 950 g of soil and rice were milled and transferred to standard Marinelli dishes with 50 mesh. The samples were completely sealed and after about one month, they were visualized with ultra-pure germanium detectors (HPGe). Subsequently, specific radionuclide radiosensitivity in soil and rice soil samples, radionuclide transfer factors from soil to rice, annual effective dose and risk of cancer due to rice consumption were measured.
Results: Effective total dose of nuclei studied in #value, lifetime cancer risk of U238 from #value to 0.00019, Ra226 from #value to 0.00008, U235 # value, Th232 from #value to 0.00027, K40 From 0.00014 to 0.00082 and finally for zero cesium.
Conclusion: There is no harmful effect on the people of the region regarding the radionuclides of rice.
Raoof Nopour, Mohammad Shirkhoda, Sharareh Rostam Niakan Kalhori,
Volume 14, Issue 2 (5-2020)
Abstract
Background and Aim: Colorectal cancer is one of the most common gastrointestinal cancers among human beings and the most important cause of death in the world. Based on the risk of colorectal cancer for individuals, using an appropriate screening program can help to prevent the disease. Therefore, the purpose of this study was to design a model for screening colorectal cancer based on risk factors to increase the survival rate of the disease on the one hand and to reduce the mortality rate on the other.
Materials and Methods: By reviewing articles and patients' records, 38 risk factors were detected. To determine the most important risk factors clinically, CVR(content validity ratio) was used; and considering the collected data, Spearman correlation coefficient and logistic regression analysis were applied for statistical analyses. Then, four algorithms -- J-48, J-RIP, PART and REP-Tree -- were used for data mining and rule generation. Finally, the most common model was obtained based on comparing the performance of the algorithms.
Results: After comparing the performance of algorithms, the J-48 algorithm with an F-Measure of 0.889 was found to be better than the others.
Conclusion: The results of evaluating J-48 data mining algorithm performance showed that this algorithm could be considered as the most appropriate model for colorectal cancer risk prediction.
Vahid Changizi, Maryam Mohammadi, Samaneh Baradaran, Mehran Taheri,
Volume 15, Issue 4 (10-2021)
Abstract
Background and Aim: On panoramic radiographs, sensitive organs, including the thyroid, are exposed to radiation. Thyroid cancer is one of the most common cancers in Iran. That is why, in this study the effective dose and risk of thyroid cancer were estimated on panoramic radiography.
Materials and Methods: Seventy GR200 thermoluminescence (TLD) dosimeters were used to estimate the absorbed dose of thyroid. The dosimeters were calibrated and placed on the patients’ necks during panoramic radiography. After dosimeters were read, the mean absorbed dose and effective thyroid dose were calculated in three groups with different radiation conditions. Lifetime Attributable Risk (LAR) of thyroid cancer was estimated using the model presented in the BEIR VII report. GraphPad Prism statistical software was used to analyze the data.
Results: The mean absorbed dose of thyroid lobes in groups M, L, XL (According to mandibular size) was estimated to be 0.116±0.01, 0.123±0.04 and 0.03±0.134 mg, respectively. The right thyroid lobe in group XL with absorption dose of 0.143±0.05 mg and the left lobe in group M with absorption dose of 0.106±0.03 mg had the highest and the lowest absorption doses, respectively. The difference between the absorbed doses of the right and left thyroid lobes in any of the three groups was not statistically significant. Thyroid absorption doses in these three groups were not statistically significant. The highest risk of thyroid cancer in the age range of 15-60 years was related to the age of 15, which was estimated to be 0.238 in women and 0.042 in men per 100,000 people.
Conclusion: In lower ages and among women, the risk of thyroid cancer is higher than that of men. Also, due to the impossibility of limiting thyroid radiation in panoramic radiography using lead thyroid collar that causes metal artifacts, we should reduce the number of panoramic radiographs as much as possible, especially at lower ages.
Sousan Rabihavy, Zhila Najafpour,
Volume 16, Issue 1 (3-2022)
Abstract
Background and Aim: Operation rooms have several specialty processes, a higher level of technology, complicated treatment protocols, and the need for skillful human recourses, which is one of the highest risk wards in the hospital. Therefore, this study was initiated to identify and evaluate potential errors by using the Failure Mode, Effects, and Criticality Analysis (FMECA) approach to recognize the potential errors in operation rooms of Golestan hospital of Ahvaz.
Materials and Methods: This research was done with a qualitative approach in seven stages and it was based on the FMECA protocol. Data were obtained through direct observation, assessment of documents and interviews with the related staff. In this regard, surgical processes were extracted from the beginig of the surgical planning to discharge patient from the post-anesthesia care unit, after that the potential errors associated with each process were identified. Finally, the risk priority number of each of them was calculated according to the indicators of Occurrence (O), Severity (S), and Detectability (D). Score analysis was performed using descriptive statistics and SPSS software.
Results: In the present study, during the analysis of processes related to surgical care, 17 primary surgery processes and 75 sub processes (from surgical planning to discharg from the post-anesthesia care unit) were identified. Seventy failure modes were identified. Ultimately, after analyzing the failure modes in the risk matrix, among the 70 identified failure modes, two failure modes had unacceptable risk, including no proper cleaning of the operation theatre and marking the surgical site, and there was Seven other failure modes with moderate risk, including unappropraite hand hygiene and environmental and operating room fixed equipment disinfection, central oxygen disconnection, lack of equipments in night shift, delay in delivery of prostheses to the surgical site, transfer of patient who requires intensive care to the ward, were identified. Human and organizational causes contributed the most to the occurrence of potential errors.
Conclusion: Analysis of failure modes showed that the highest probability of error occurs in the processes during surgery and due to human and organizational factors. Identification of 70 potential errors in 17 processes of the Operating Room indicates the integrity of FMECA’s preventive approach in identifying and prioritizing the high-risk areas of the processes, insensitive parts such as the operating room.
