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Article ; Online: Prevalence of Methicillin-resistant Staphylococcus aureus and their antibiotic resistance patterns in patients hospitalized in Birjand-based Imam Reza Hospital

Parvin Askari / kiarash Ghazvini / Mohammad Hassan Namaee / Ehsan Aryan / Hadi Safdari / Masoud Yousefi

مجله دانشگاه علوم پزشکی بیرجند, Vol 24, Iss 3, Pp 218-

2017 Volume 226

Abstract: ... antibiotic resistance patterns of MRSA in patients hospitalized in the Birjand-based Imam Reza hospital. Materials and ...

Abstract	Background and Aim: As one of the major causes of hospital and community acquired infections, Methicillin-resistant Staphylococcus aureus (MRSA) requires accurate and timely diagnosis. This study aimed to investigate the prevalence and antibiotic resistance patterns of MRSA in patients hospitalized in the Birjand-based Imam Reza hospital. Materials and Methods: In this cross-sectional study, a total of 102 clinical Staphylococcus aureus isolates were evaluated. Staphylococcus aureus isolates were confirmed via conventional microbiological and PCR methods (coa gene). The antimicrobial resistance patterns of the isolates were determined using the Kirby-Bauer disk-diffusion based on CLSI guidelines. Resistance to methicillin in the isolates was confirmed by means of PCR method (mceA gene). Finally, the obtained data was analyzed using SPSS software (version 16). Results: In this study, 50.9% and 58.8% of Staphylococcus aureus isolates were reported as methicillin-resistant using the Kirby-Bauer disk-diffusion and PCR methods, respectively. The highest antibiotic resistance in MRSA strains was found to penicillin (96.6%), to erythromycin (45%), and to ciprofloxacin (36.6%). In present study, resistance to azithromycin, erythromycin, ciprofloxacin, gentamicin, minocycline, and rifampin in MRSA isolates was significantly greater than Methicillin-sensitive Staphylococcus aureus (P<0.05). Conclusion: A significant percentage of MRSA isolates in the hospitalized patients was resistant to methicillin, which is confirmed even with a wider range in their genotype.
Keywords	Methicillin-resistant Staphylococcus aureus ; Antibiotic resistance ; Polymerase chain reaction ; Medicine ; R ; Medicine (General) ; R5-920
Subject code	610
Language	Persian
Publishing date	2017-10-01T00:00:00Z
Publisher	Birjand University of Medical Sciences and Health Services
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: A Framework for Neonatal Prematurity Information System Development Based on a Systematic Review on Current Registries: An Original Research.

Pahlevanynejad, Shahrbanoo / Danaee, Navid / Safdari, Reza

Journal of biomedical physics & engineering

2024 Volume 14, Issue 2, Page(s) 183–198

Abstract: Background: Registries are regarded as a just valuable fount of data on determining neonates suffering prematurity or low birth weight (LBW), ameliorating provided care, and developing studies.: Objective: This study aimed to probe the studies, ... ...

Abstract	Background: Registries are regarded as a just valuable fount of data on determining neonates suffering prematurity or low birth weight (LBW), ameliorating provided care, and developing studies. Objective: This study aimed to probe the studies, including premature infants' registries, adapt the needed minimum data set, and provide an offered framework for premature infants' registries. Material and methods: For this descriptive study, electronic databases including PubMed, Scopus, Web of Science, ProQuest, and Embase/Medline were searched. In addition, a review of gray literature was undertaken to identify relevant studies in English on current registries and databases. Screening of titles, abstracts, and full texts was conducted independently based on PRISMA guidelines. The basic registry information, scope, registry type, data source, the purpose of the registry, and important variables were extracted and analyzed. Results: Fifty-six papers were qualified and contained in the process that presented 51 systems and databases linked in prematurity at the popular and government levels in 34 countries from 1963 to 2017. As a central model of the information management system and knowledge management, a prematurity registry framework was offered based on data, information, and knowledge structure. Conclusion: To the best of our knowledge, this is a comprehensive study that has systematically reviewed prematurity-related registries. Since there are international standards to develop new registries, the proposed framework in this article can be beneficial too. This framework is essential not only to facilitate the prematurity registry design but also to help the collection of high-value clinical data necessary for the acquisition of better clinical knowledge.
Language	English
Publishing date	2024-04-01
Publishing country	Iran
Document type	Journal Article
ZDB-ID	2673599-4
ISSN	2251-7200
ISSN	2251-7200
DOI	10.31661/jbpe.v0i0.2105-1345
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Article ; Online: Identification of Minimum Data Set of Neonatal Prematurity Information Management System for Iran.

Safdari, Reza / Danaee, Navid / Kahouei, Mehdi / Mirmohammadkhani, Majid / Pahlevanynejad, Shahrbanoo

Iranian journal of public health

2023 Volume 52, Issue 1, Page(s) 210–212

Language	English
Publishing date	2023-02-14
Publishing country	Iran
Document type	Journal Article
ZDB-ID	2240935-X
ISSN	2251-6093 ; 2251-6093
ISSN (online)	2251-6093
ISSN	2251-6093
DOI	10.18502/ijph.v52i1.11687
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Article: Evaluation of the PSO Metaheuristic Algorithm in Different Types of Sleep Apnea Diagnosis Using RR Intervals.

Kohzadi, Zeinab / Safdari, Reza / Sadeghniiat Haghighi, Khosro

Journal of biomedical physics & engineering

2023 Volume 13, Issue 2, Page(s) 147–156

Abstract: Background: Sleep apnea is one of the most common sleep disorders that facilitating and accelerating its diagnosis will have positive results on its future trend.: Objective: This study aimed to diagnosis the sleep apnea types using the optimized ... ...

Abstract	Background: Sleep apnea is one of the most common sleep disorders that facilitating and accelerating its diagnosis will have positive results on its future trend. Objective: This study aimed to diagnosis the sleep apnea types using the optimized neural network. Material and methods: This descriptive-analytical study was done on 50 cases of patients referred to the sleep clinic of Imam Khomeini Hospital in Tehran, including 11 normal, 13 mild, 17 moderate and 9 severe cases. At the first, the data were pre-processed in three stages, then The Electrocardiogram (ECG) signal was decomposed to 8 levels using wavelet transform convert and 6 nonlinear features for the coefficients of this level and 10 features were calculated for RR Intervals. For apnea categorizing classes, the multilayer perceptron neural network was used with the backpropagation algorithm. For optimizing Multi-layered Perceptron (MLP) weights, the Particle Swarm Optimization (PSO) evolutionary optimization algorithm was used. Results: The simulation results show that the accuracy criterion in the MLP network is allied with the Backpropagation (BP) training algorithm for different types of apnea. By optimizing the weights in the MLP network structure, the accuracy criterion for modes normal, obstructive, central, mixed was obtained %96.86, %97.48, %96.23, and %96.44, respectively. These values indicate the strength of the evolutionary algorithm in improving the evaluation criteria and network accuracy. Conclusion: Due to the growth of knowledge and the complexity of medical decisions in the diagnosis of the disease, the use of artificial neural network algorithms can be useful to support this decision.
Language	English
Publishing date	2023-04-01
Publishing country	Iran
Document type	Journal Article
ZDB-ID	2673599-4
ISSN	2251-7200
ISSN	2251-7200
DOI	10.31661/jbpe.v0i0.2004-1110
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Article ; Online: Feasibility study and determination of prerequisites of telecare programme to enhance patient management in lung transplantation: a qualitative study from the perspective of Iranian healthcare providers.

Gholamzadeh, Marsa / Safdari, Reza / Amini, Shahideh / Abtahi, Hamidreza

BMJ open

2023 Volume 13, Issue 6, Page(s) e073370

Abstract: Background: Non-adherence to treatment plans, follow-up visits and healthcare advice is a common obstacle in the management of lung transplant patients. This study aims to investigate experts' views on the needs and main aspects of telecare programmes ... ...

Abstract	Background: Non-adherence to treatment plans, follow-up visits and healthcare advice is a common obstacle in the management of lung transplant patients. This study aims to investigate experts' views on the needs and main aspects of telecare programmes for lung transplantation. Design: A qualitative study incorporating an inductive thematic analysis. Setting: Lung transplant clinic and thoracic research centre. Participants: Clinicians: four pulmonologists, two cardiothoracic surgeons, two general physicians, two pharmacotherapists, one cardiologist, one nurse and one medical informatician. Method: This study adopted a focus group discussion technique to gather experts' opinions on the prerequisites and features of a telecare programme in lung transplantation. All interviews were coded and combined into main categories and themes. Thematic analysis was performed to extract the key concepts using ATLAS.Ti. Ultimately, all extracted themes were integrated to devise a conceptual model. Results: Ten focus groups with 13 participants were conducted. Forty-six themes and subthemes were extracted through the thematic analysis. The main features of the final programme were extracted from expert opinions through thematic analysis, such as continuous monitoring of symptoms, drug management, providing a specific care plan for each patient, educating patients module, creating an electronic medical record to collect patient information, equipping the system with decision support tools, smart electronic prescription and the ability to send messages to the care team. The prerequisites of the system were summarised in self-care activities, clinician's tasks and required technologies. In addition, the barriers and benefits of using a telecare system to enhance the quality of care were determined. Conclusion: Our investigation recognised the main factors that must be considered to design a telecare programme to provide ideal continuous care for lung transplant patients. Users should further explore the proposed model to support the development of telecare interventions at the point of care.
MeSH term(s)	Humans ; Iran ; Feasibility Studies ; Qualitative Research ; Lung Transplantation ; Ambulatory Care Facilities ; General Practitioners
Language	English
Publishing date	2023-06-22
Publishing country	England
Document type	Journal Article
ZDB-ID	2599832-8
ISSN	2044-6055 ; 2044-6055
ISSN (online)	2044-6055
ISSN	2044-6055
DOI	10.1136/bmjopen-2023-073370
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Article ; Online: The Application of Knowledge-Based Clinical Decision Support Systems to Enhance Adherence to Evidence-Based Medicine in Chronic Disease.

Gholamzadeh, Marsa / Abtahi, Hamidreza / Safdari, Reza

Journal of healthcare engineering

2023 Volume 2023, Page(s) 8550905

Abstract: Among the technology-based solutions, clinical decision support systems (CDSSs) have the ability to keep up with clinicians with the latest evidence in a smart way. Hence, the main objective of our study was to investigate the applicability and ... ...

Abstract	Among the technology-based solutions, clinical decision support systems (CDSSs) have the ability to keep up with clinicians with the latest evidence in a smart way. Hence, the main objective of our study was to investigate the applicability and characteristics of CDSSs regarding chronic disease. The Web of Science, Scopus, OVID, and PubMed databases were searched using keywords from January 2000 to February 2023. The review was completed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Then, an analysis was done to determine the characteristics and applicability of CDSSs. The quality of the appraisal was assessed using the Mixed Methods Appraisal Tool checklist (MMAT). A systematic database search yielded 206 citations. Eventually, 38 articles from sixteen countries met the inclusion criteria and were accepted for final analysis. The main approaches of all studies can be classified into adherence to evidence-based medicine (84.2%), early and accurate diagnosis (81.6%), identifying high-risk patients (50%), preventing medical errors (47.4%), providing up-to-date information to healthcare providers (36.8%), providing patient care remotely (21.1%), and standardizing care (71.1%). The most common features among the knowledge-based CDSSs included providing guidance and advice for physicians (92.11%), generating patient-specific recommendations (84.21%), integrating into electronic medical records (60.53%), and using alerts or reminders (60.53%). Among thirteen different methods to translate the knowledge of evidence into machine-interpretable knowledge, 34.21% of studies utilized the rule-based logic technique while 26.32% of studies used rule-based decision tree modeling. For CDSS development and translating knowledge, diverse methods and techniques were applied. Therefore, the development of a standard framework for the development of knowledge-based decision support systems should be considered by informaticians.
MeSH term(s)	Humans ; Decision Support Systems, Clinical ; Expert Systems ; Electronic Health Records ; Evidence-Based Medicine ; Chronic Disease
Language	English
Publishing date	2023-05-29
Publishing country	England
Document type	Journal Article ; Review ; Research Support, Non-U.S. Gov't
ZDB-ID	2545054-2
ISSN	2040-2309 ; 2040-2295
ISSN (online)	2040-2309
ISSN	2040-2295
DOI	10.1155/2023/8550905
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Article ; Online: Effect of acupressure on pain intensity and physiological indices in patients undergoing extracorporeal shock wave lithotripsy: a randomized double-blind sham-controlled clinical trial.

Safdari, Ali / Khazaei, Salman / Biglarkhani, Mahdi / Mousavibahar, Seyed Habibollah / Borzou, Seyed Reza

BMC complementary medicine and therapies

2024 Volume 24, Issue 1, Page(s) 55

Abstract: Background: Despite the widespread use of extracorporeal shock wave lithotripsy (ESWL) as a treatment for kidney stones, it is essential to apply methods to control pain and improve patient comfort during this procedure. Therefore, this study aimed to ... ...

Abstract	Background: Despite the widespread use of extracorporeal shock wave lithotripsy (ESWL) as a treatment for kidney stones, it is essential to apply methods to control pain and improve patient comfort during this procedure. Therefore, this study aimed to investigate the effect of acupressure at the Qiu point on pain intensity and physiological indices in patients undergoing ESWL. Methods: This randomized, sham-controlled clinical trial was conducted at the Shahid Beheshti Educational-medical Center in Hamadan City (western Iran) from May to August 2023. Seventy-four eligible patients were split into intervention (n = 37) and sham (n = 37) groups. Ten minutes before lithotripsy, the intervention group received acupressure at the Qiu point, while the sham group received touch at a neutral point. The primary outcomes were pain intensity measured by the Visual Analog Scale (VAS) and physiological indices such as blood pressure and heart rate at baseline, 1, 10, 20, 30, 40, and 50 min after the intervention. The secondary outcomes included lithotripsy success and satisfaction with acupressure application. Results: The analysis of 70 patients showed no significant differences in the demographic and clinical information of the patients across the two groups before the study (P > 0.05). Generalized estimating equations revealed that the interaction effects of time and group in pain and heart rate were significant at 30 and 40 min (P < 0.05). The results of this analysis for systolic blood pressure revealed a significant interaction at 30 min (P = 0.035). However, no significant interaction effects were found for diastolic blood pressure changes (P > 0.05). Conclusions: Acupressure at the Qiu point positively impacts pain in patients undergoing ESWL treatment and increases their satisfaction. However, these results for physiological indices require further studies. Thus, acupressure can be considered a simple, easy, and effective option for pain management in patients during this procedure. Trial registration: [ https://en.irct.ir/trial/69117 ], identifier [IRCT20190524043687N4].
MeSH term(s)	Humans ; Pain Measurement ; Acupressure ; Pain/drug therapy ; Pain Management/methods ; Lithotripsy/methods
Language	English
Publishing date	2024-01-25
Publishing country	England
Document type	Randomized Controlled Trial ; Journal Article
ISSN	2662-7671
ISSN (online)	2662-7671
DOI	10.1186/s12906-024-04360-1
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Article ; Online: Comparison of different machine learning algorithms to classify patients suspected of having sepsis infection in the intensive care unit

Marsa Gholamzadeh / Hamidreza Abtahi / Reza Safdari

Informatics in Medicine Unlocked, Vol 38, Iss , Pp 101236- (2023)

2023

Abstract: Background: Sepsis is a life-threatening disease that occurs as a result of the body's response to an infection. This study aims to develop a classification model for predicting patients at risk of sepsis using clinical findings and demographic ... ...

Abstract	Background: Sepsis is a life-threatening disease that occurs as a result of the body's response to an infection. This study aims to develop a classification model for predicting patients at risk of sepsis using clinical findings and demographic information. Methods: The study was conducted using a MIMICIII dataset which is freely available as open-access data. The synthetic minority oversampling technique (SMOTE) was applied to address the imbalanced data problem in our dataset. Through preprocessing, the dataset was cleaned and missing values were imputed. Split validation was done by dividing the dataset into training and test data for developing classification models. Six algorithms including Gaussian Naïve Bayes (NB), decision tree (DT), random forest (RF), logistic regression (LR), KNN algorithm, and XGBoost classifier were developed. A combination of evaluation metrics was employed to evaluate the performance of the proposed models. Results: Our dataset includes 1,552,210 entries with 44 features of critically ill patients who were admitted to the ICU. Comparing the performance of developed models using different metrics showed that the RF model had the best performance in terms of F-Measure and the area under the ROC curve. The 20 top features with high importance were determined based on the RF model. Conclusion: Our analysis showed that the RF model predicted sepsis with significantly higher performance in comparison to other classification models using the MIMICIII dataset. Due to the high mortality of sepsis, these kinds of studies could be supportive to prevent the side effects of the disease and lessen the risk of mortality in hospitalized patients by providing early sepsis prediction.
Keywords	Sepsis ; Machine learning ; Classification ; ICU ; Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	006
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Evaluation of the PSO Metaheuristic Algorithm in Different Types of Sleep Apnea Diagnosis Using RR Intervals

Zeinab Kohzadi / Reza Safdari / Khosro Sadeghniiat Haghighi

Journal of Biomedical Physics and Engineering, Vol 13, Iss 2, Pp 147-

2023 Volume 156

Abstract: Background: Sleep apnea is one of the most common sleep disorders that facilitating and accelerating its diagnosis will have positive results on its future trend. Objective: This study aimed to diagnosis the sleep apnea types using the optimized neural ... ...

Abstract	Background: Sleep apnea is one of the most common sleep disorders that facilitating and accelerating its diagnosis will have positive results on its future trend. Objective: This study aimed to diagnosis the sleep apnea types using the optimized neural network.Material and Methods: This descriptive-analytical study was done on 50 cases of patients referred to the sleep clinic of Imam Khomeini Hospital in Tehran, including 11 normal, 13 mild, 17 moderate and 9 severe cases. At the first, the data were pre-processed in three stages, then The Electrocardiogram (ECG) signal was decomposed to 8 levels using wavelet transform convert and 6 nonlinear features for the coefficients of this level and 10 features were calculated for RR Intervals. For apnea categorizing classes, the multilayer perceptron neural network was used with the backpropagation algorithm. For optimizing Multi-layered Perceptron (MLP) weights, the Particle Swarm Optimization (PSO) evolutionary optimization algorithm was used. Results: The simulation results show that the accuracy criterion in the MLP network is allied with the Backpropagation (BP) training algorithm for different types of apnea. By optimizing the weights in the MLP network structure, the accuracy criterion for modes normal, obstructive, central, mixed was obtained .86, .48, .23, and .44, respectively. These values indicate the strength of the evolutionary algorithm in improving the evaluation criteria and network accuracy. Conclusion: Due to the growth of knowledge and the complexity of medical decisions in the diagnosis of the disease, the use of artificial neural network algorithms can be useful to support this decision.
Keywords	sleep apnea ; ecg ; polysomnography ; rr intervals ; pso ; wavelet analysis ; algorithm ; Medical physics. Medical radiology. Nuclear medicine ; R895-920
Subject code	006
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Shiraz University of Medical Sciences
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Predictors of the worry about cancer recurrence among women with breast cancer.

Safdari-Molan, Masoumeh / Mehrabi, Esmat / Nourizadeh, Roghaiyeh / Eghdam-Zamiri, Reza

BMC women's health

2023 Volume 23, Issue 1, Page(s) 131

Abstract: Introduction: Worry about cancer recurrence is identified as the most common psychological burdens experienced by cancer patients and survivors. The present study aimed to determine the predictors of worry about cancer recurrence among women with breast ...

Abstract	Introduction: Worry about cancer recurrence is identified as the most common psychological burdens experienced by cancer patients and survivors. The present study aimed to determine the predictors of worry about cancer recurrence among women with breast cancer. Materials and methods: This cross-sectional study was conducted on 166 women with breast cancer undergoing chemotherapy and radiotherapy, who referred to private and public oncology centers in Tabriz, Iran using the convenience sampling. Data collection tools were demographic and disease characteristics questionnaire, cancer worry scale, social support questionnaire, brief illness perception questionnaire, international physical activity questionnaire-short form, and The EORTC-in-patsat32. The data were analyzed using SPSS 25 software. Pearson correlation coefficient, independent t-test, ANOVA, and multivariate linear regression were used. Results: In the present study, the mean (standard deviation) of score of worry about cancer recurrence was 17.41 (7.88), ranging from 8-32. The results revealed that the type of surgery, illness perception, satisfaction with care, and place of treatment were the most important predictors of worry about cancer recurrence, which explained 44.3% of the variance. Conclusion: The enhancement of satisfaction with care and training coping strategies among individuals with high perceived severity of the illness contribute to the reduction of worry about cancer recurrence and adaptation to breast cancer.
MeSH term(s)	Humans ; Female ; Breast Neoplasms/therapy ; Breast Neoplasms/psychology ; Cross-Sectional Studies ; Neoplasm Recurrence, Local ; Anxiety/psychology ; Adaptation, Psychological ; Surveys and Questionnaires
Language	English
Publishing date	2023-03-25
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2050444-5
ISSN	1472-6874 ; 1472-6874
ISSN (online)	1472-6874
ISSN	1472-6874
DOI	10.1186/s12905-023-02296-1
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