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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Journal of Kerman University of Medical Sciences
- نوع مقاله: Journal Article
- کلمات کلیدی: patient safety,nurse,Medication Error,Medication error reporting
- چکیده:
- چکیده انگلیسی: Background & Aims: Administration of medications is an important part of treatment. Reporting of medication errors by nurses maintains patient safety and the lack of appropriate reporting can cause serious problems in health systems. The aim of this study was to determine the causes of medication errors and the barriers of error reporting from the viewpoints of nurses. Methods: This cross-sectional study was conducted on 248 nurses in hospitals affiliated to Neyshabur University of Medical Sciences, Iran. Participants were selected by simple random sampling. Data were collected through a questionnaire and analyzed by descriptive and inferential statistics in SPSS software. Results: The most important reasons of medication errors were nursing staff shortage (4.3 ± 1.2), fatigue due to overwork (4.1 ± 1.05), and high workload (4.1 ± 2.8). The main reasons for not reporting medication errors were authorities' focusing on the person who has made the error regardless of other factors involved (3.86 ± 1.06), fear of legal issues (3.79 ± 1.07), and lack of clarity of the definition of medication error (3.34 ± 1.13). There was a significant difference between the factors affecting medication errors from the view of nurses, and fixed and rotating work shifts (P < 0.05). Conclusion: Due to the importance of patient safety, establishing a system for reporting and recording errors along with the positive reaction of managers to errors by personnel is essential.
- انتشار مقاله: 29-04-1395
- نویسندگان: Bahram Hesari,Hasan Ghodsi,Mohammad Hoseinabadi,Hasan Chenarani,Alireza Ghodsi
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Industrial Engineering International
- نوع مقاله: Journal Article
- کلمات کلیدی: Supply Chain Management,Outsourcing,responsiveness,Agile supply chain network design
- چکیده:
- چکیده انگلیسی: The characteristics of today's competitive environment, such as the speed with which products are designed,
manufactured, and distributed, and the need for higher responsiveness and lower operational cost, are forcing
companies to search for innovative ways to do business. The concept of agile manufacturing has been proposed
in response to these challenges for companies. This paper copes with the strategic and tactical level decisions in
agile supply chain network design. An efficient mixed-integer linear programming model that is able to consider
the key characteristics of agile supply chain such as direct shipments, outsourcing, different transportation modes,
discount, alliance (process and information integration) between opened facilities, and maximum waiting time of
customers for deliveries is developed. In addition, in the proposed model, the capacity of facilities is determined as
decision variables, which are often assumed to be fixed. Computational results illustrate that the proposed model
can be applied as a power tool in agile supply chain network design as well as in the integration of strategic
decisions with tactical decisions.- انتشار مقاله: 10-07-1399
- نویسندگان: Reza Babazadeh,Jafar Razmi,Reza Ghodsi
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Pediatrics
- نوع مقاله: Journal Article
- کلمات کلیدی: children,Iran,PCR,Antibody,HTLV-1
- چکیده:
- چکیده انگلیسی: Background
Human T cell lymphotropic virus type I (HTLV-1) infection is endemic in specific regions of the world, including northeastern Iran. Besides mother to fetus transmission, it can be transmitted through breast feeding, sexual contact, and blood transfusion. The aim of this study was to determine the frequency of HTLV-1 in children.
Materials and Methods
This cross-sectional study was conducted on children from 6 months to 14 years of age hospitalized in Imam Reza Hospital between January 2016 and January 2017. HTLV-1 antibody testing was done on all patients admitted within one year, and the positive results were further confirmed by Polymerase chain reaction (PCR). After determining the frequency, the types of feeding and possible transmission ways of the virus were investigated.
Results
Out of the 1358 children admitted, 758 entered the study and were tested for HTLV-1 antibody. The result was positive in 58 patients (7.65%) who were further tested by PCR and 11 (1.45%) had positive antibody result. Out of the 58 positive children, 28 (48.3%) were male and 30 (51.7%) female. Most of the children were in the age range of 6 to 30 months and breastfed. In terms of location, most of them lived in Mashhad (58.62%).
Conclusion
Our results demonstrated that the frequency of HTLV-1 antibody among children of 6 months to 14 years was 7.65%. They were tested by PCR and 1.45% were positive. This region therefore still remains an endemic area for HTLV-1 infection.- انتشار مقاله: 24-09-1399
- نویسندگان: Alireza Ghodsi,Saeid Amel Jamehdar,Abdol Karim Hamedi
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Pediatrics
- نوع مقاله: Journal Article
- کلمات کلیدی: children,pyogenic arthritis,Septic arthritis,suppurate arthritis
- چکیده:
- چکیده انگلیسی:
Background
Septic arthritis is an acute infection of the joint space and a pediatric emergency. Delay in proper diagnosis and treatment, while prolonging the course of treatment, can have serious complications. The present study aimed to assess the clinical and laboratory profile of septic arthritis among patients hospitalized in the pediatric ward of Imam Reza Hospital of Mashhad, Iran.
Materials and Methods: This retro-prospective study was conducted on the medical files of children from 2 months to 16 years old hospitalized in Imam Reza Hospital, Mashhad, Iran, from March 2011 to March 2019 due to a diagnosis of septic arthritis. A checklist capturing the age, gender, clinical symptoms, laboratory symptoms, affected joint, and type of treatment was prepared and completed according to the medical files of the patients.
Results: Out of 173 studied patients, 91 (53%), and 82 (47%) of cases were boys and girls, respectively. The patient was two months to 16 years old. The hip joint was affected more in 78 patients (45%). Among the clinical symptoms, fever was the most common found in 134 cases (77%). Moreover, 11 cases had positive blood culture where staphylococcus aurous with five positive reported cases (45%) was a major observation. Furthermore, four cases were reported to have a positive joint culture. CRP was positive in 94.8% of patients.
Conclusion
Septic arthritis is one of the pediatric emergencies that should be diagnosed rapidly, and immediate treatment should be started to prevent irreversible complications. The most common symptom of arthritis in infants is restlessness and immobility and limp in children.
- انتشار مقاله: 19-05-1399
- نویسندگان: Maryam Khalesi,Alireza Ghodsi,Abdol Karim Hamedi
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Pediatrics
- نوع مقاله: Journal Article
- کلمات کلیدی: Pregnancy,COVID-19,neonate
- چکیده:
- چکیده انگلیسی: Background
The COVID-19 infection, which has been a pandemic since early 2020, can occur in pregnant women and can be transmitted to the baby after birth. There are few reports of this transmission in newborns. Because there are several causes for respiratory symptoms in a neonate, it is difficult to diagnose COVID-19 infection in the newborn. Evaluation of antibody in the blood umbilical cord may be an option in the future. We studied the COVID-19 infection in newborns.
Materials and Methods
In this longitudinal follow-up study, pregnant mothers who had suspicious symptomsof coronavirus infection before or after childbirth were consulted by the medical team for neonatal infection. Newborns were evaluated for respiratory symptoms. PCR test for corona virus was performed on pharyngeal swab or tracheal tube sample of the newborns.
Results
Twenty-five pregnant women with symptoms suspicious coronavirus infections were consulted by the team of specialists from March 15 to April 15, 2020. After delivery their babies were carefully examined and followed up. Four neonates had coronavirus confirmed by PCR test.
Conclusion
Our study showed that neonates can become infected with Covid-19 and it should be considered amongst various differential diagnosis of neonatal respiratory diseases.- انتشار مقاله: 30-01-1399
- نویسندگان: Ahmad Shah Farhat,Seyed Javad Sayedi,Farideh Akhlaghi,Abdolkarim Hamedi,Alireza Ghodsi
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Time series,Forecasting raining,Disaster management,Seasonal auto-regressive integrated moving average,Locally linear nero-fuzzy networks
- چکیده:
- چکیده انگلیسی: Ecological changes resulting from climate conditions can severely affect human societies especially in the area of economy and safety. Climate catastrophes may cause social and economic tension. Forecasting such changes accurately can help the government to control the disasters and to achieve possible benefits (such as water supply in flood). Weather forecasting is the application of science and technology to predict the state of the atmosphere for a given location. Rate of raining is a very important factor in weather forecasting. Different forms of weather forecasting models represent different stochastic processes. Three broad classes of time series modeling in practice are the autoregressive (AR) models, the integrated (I) models, and the moving average (MA) models. These models represent the linear dependence on previous observations. Cyclic variation known as periodic fluctuation or seasonality (S) might be dealt with in time series analysis by using a sinusoidal model. A less completely regular cyclic variation might be considered by using a special form of an auto regressive integrated moving average. In this paper, a hybrid approach based on seasonal auto regressive integrated moving average (SARIMA) method and Locally Linear Model Tree (LoLiMoT) is proposed for forecasting rate of raining. A neural network based on local linear models weighted constructed by a tree algorithm is applied in this research. Training of this network is divided into a structure and a parameter optimization part. A recursive least-squares algorithm is used for training the network since the network is linear in its parameters. A two phase model is developed based on data gathered in Zabol Synoptic Station from 1939 to 2011. In the first phase, the SARIMA model is implemented to predict the raining rate. In the second step neural network based on locally linear model tree is applied to residuals to improve the prediction result. Finally, the proposed model is compared to Sin-Cos model; Result obtained confirm the efficiency of this approach as a practical tool for forecasting the rate of raining.
- انتشار مقاله: 07-08-1391
- نویسندگان: Meisam Nasrollahi,Hassan Mina,Seyed Farid Ghaderi,Reza Ghodsi
- مشاهده