Search

Background: Despite the passing of many years of introduction of peritoneal dialysis as a replacement therapy for renal function, the rate of acceptance of this method is still low. This study aimed to determine the effect of educational program based on the removal of barrierson knowledge and intention to do peritoneal dialysis in patients with end-stage renal disease. Materials and Methods: In a quasi-experimental pre-test-post-test study, 45 patients with peritoneal dialysis who had criteria for entering the study were selected in a purposive sampling method. The research instrument was a researcher-made questionnaire. After the sampling, an educational program based on the removal reported barriers in the research background was presented to the subjects. The program was presented individually and mainly in a 60- to 75-minute session. The results were analyzed by paired t-test and McNemar test. Results According to the results of this study, the implementation of educational program based on removal of barriers significantly increased the knowledge of patients about peritoneal dialysis (P

Cucumber (Cucumis sativus L.) seed is imported to Iran. A breeding program is needed locally to select elite lines. Factor analysis is a useful tool for investigating variable relationships for complex factors because it allows investigation of concepts that are not easily measured directly by collapsing a large number of variables into a few interpretable underlying factors. Forty genotypes, representing hybrids of commercial cucumber, cv. Negeen, and lines B10 and B12, developed locally, were used in the experiment at Rasht, Iran. Factor analysis, based on principal component analysis and varimax rotation, indicated the factors yield, major yield contributing factors, fruit quality, fruit firmness, and vegetative factors accounted for 66.5% of total variation. Genotypes positioned near the commercial cultivar in scatter diagrams were acceptable because they had high yield, and major yield contributing factors, and good fruit quality. If gynociouse and parthenocarpic lines are not available germplasm can be selected from progenies of commercial hybrids and local lines with a simple factor analysis. [ABSTRACT FROM AUTHOR]

Background: Elderly individuals use more drug and they are at a higher risk of polypharmacy complications. This study aimed to evaluate the polypharmacy and its related factors among the elderly group in Kashan (Iran) during 2011-2012. Materials and Methods: In a cross-sectional study, 360 elderly people over 60 years old were selected using the cluster-randomized method. Data were gathered based on a questionnaire contained demographic variables (e.g. age, sex, marital status, income status, level of education, hospitalization history) and main variables (e.g. the name and number of medications used, duration of use, the number of physicians prescribed drug, the number of potentially inappropriate medication use in elderly due to their background diseases and the number of potentially inappropriate medication used in an elderly group using the 2000 Beers criteria. Results: A total of 308 (88%) elderly (170 women and 138 men) had taken at least one medication during the interview. Mean and range of age of the elderly were 70.8 ±7.9 and 60-100 years, respectively. Mean and range of medications were 6.2±3.53 and 1-23 respectively had taken by among individuals older than age 60 in kashan. Prevalence of polypharmacy in related population was 54.5 % (167 cases) and 66 elderly people (21.4%) at least took one inappropriate drug among their medications. Conclusion: Polypharmacy among the Kashan elderly population is relatively high. Therefore, to decrease the number of prescribed medications and their related side effects in elderly individuals, applying up to date criteria in prescribing the medication for aged population is recommended. [ABSTRACT FROM AUTHOR]

Background: Nursing students' safe medication administration is a crucial aspect of ensuring patient safety. Clinical simulation is a novel teaching method applied to reduce factors threatening medication safety in the education of nursing students. Therefore, the aim of the present study was to conduct a review study in this field., Materials and Methods: The present review was conducted using keywords of education, clinical competence, medication safety, medication error, nursing student, clinical simulation, and educational strategies. Suitable articles published between 2000 and 2023 were systematically searched in various national and international online databases, including SID, Magiran, Ovid, Scopus, Web of Science, PubMed, ProQuest, and Google Scholar in both English and Persian languages., Results: A total of 855 articles were retrieved from the initial search findings. After eliminating duplicate and irrelevant articles based on predetermined criteria, a qualitative selection was conducted using CONSORT, MMAT, and JBI critical appraisal checklists. Ultimately, a selection of 11 articles was made, specifically focusing on medication safety education for nursing students through clinical simulation. The findings showed that using clinical simulation improved medication safety and safety knowledge among nursing students. Additionally, this approach was found to enhance their competence in medication administration., Conclusions: Based on the findings, clinical simulation is a safe and effective approach for enhancing nursing students' proficiency in medication safety and administration. Therefore, it is recommended that nursing education authorities implement these findings to improve nursing students' knowledge, performance, and competency in safely administering medications., Competing Interests: Nothing to declare., (Copyright: © 2024 Iranian Journal of Nursing and Midwifery Research.)

The cognitive impairment known as dementia affects millions of individuals throughout the globe. The use of machine learning (ML) and deep learning (DL) algorithms has shown great promise as a means of early identification and treatment of dementia. Dementias such as Alzheimer's Dementia, frontotemporal dementia, Lewy body dementia, and vascular dementia are all discussed in this article, along with a literature review on using ML algorithms in their diagnosis. Different ML algorithms, such as support vector machines, artificial neural networks, decision trees, and random forests, are compared and contrasted, along with their benefits and drawbacks. As discussed in this article, accurate ML models may be achieved by carefully considering feature selection and data preparation. We also discuss how ML algorithms can predict disease progression and patient responses to therapy. However, overreliance on ML and DL technologies should be avoided without further proof. It's important to note that these technologies are meant to assist in diagnosis but should not be used as the sole criteria for a final diagnosis. The research implies that ML algorithms may help increase the precision with which dementia is diagnosed, especially in its early stages. The efficacy of ML and DL algorithms in clinical contexts must be verified, and ethical issues around the use of personal data must be addressed, but this requires more study.

Background: Despite the high antioxidant potential of grape seed extract (GSE), very limited studies have investigated its effect on non-alcoholic fatty liver disease (NAFLD). Therefore, this study was conducted with the aim of investigating the effect of GSE on metabolic factors, blood pressure and steatosis severity in patients with NAFLD., Methods: In this double-blind randomized clinical trial study, 50 NAFLD patients were divided into two groups of 25 participants who were treated with 520 mg/day of GSE or the placebo group for 2 months. The parameters of glycemic, lipid profile, blood pressure and steatohepatitis were measured before and after the intervention., Results: The GSE group had an average age of 43.52 ± 8.12 years with 15 women and 10 men, while the placebo group had an average age of 44.88 ± 10.14 years with 11 women and 14 men. After 2 months of intervention with GSE, it was observed that insulin, HOMA-IR, TC, TG, LDL-c, ALT, AST, AST/ALT, SBP, DBP and MAP decreased and QUICKi and HDL-c increased significantly (p-value for all < 0.05). Also, before and after adjustment based on baseline, the average changes indicated that the levels of insulin, HOMA-IR, TC, TG, LDL-c, SBP, DBP, MAP in the GSE group decreased more than in the control group (p for all < 0.05). Furthermore, the changes in HDL-c were significantly higher in the GSE group (p < 0.05). The between-groups analysis showed a significant decrease in the HOMA-β and AST before and after adjustment based on baseline levels (p < 0.05). Moreover, the changes in QUICKi after adjustment based on baseline levels were higher in the GSE group than in the control group. Also, between-groups analysis showed that the severity of hepatic steatosis was reduced in the intervention group compared to the placebo group (P = 0.002)., Conclusions: It seems that GSE can be considered one of the appropriate strategies for controlling insulin resistance, hyperlipidemia, hypertension and hepatic steatosis in NAFLD patients., Trial Registration: The clinical trial was registered in the Iranian Clinical Trial Registration Center (IRCT20190731044392N1). https://irct.behdasht.gov.ir/trial/61413 . (The registration date: 30/03/2022)., (© 2024. The Author(s).)

Introduction: We aimed to investigate the association between cardiovascular disease (CVD) and various anthropometric indices, as well as the serum levels of copper (Cu) and zinc (Zn), copper-zinc ratio (Cu/Zn ratio) and zinc-copper ratio (Zn/Cu ratio), in a large population sample from northeastern Iranian., Method: 9704 individuals aged 35 to 65 were enrolled in the first phase of the study. After a 10-year follow-up, 7560 participants were enrolled into the second phase. The variables used in this study included demographic characteristics, such as gender and age; biochemical parameters including: serum Zn, Cu, Cu/Zn ratio, and Zn/Cu ratio; anthropometric parameters including: waist circumference (WC), body mass index (BMI), and waist-to-hip ratio (WHR). The relationship between the aforementioned indices and CVD was examined using decision tree (DT) and logistic regression (LR) models., Results: A total of 837 individuals were diagnosed with CVD among the 7560 participants. LR analysis showed that BMI, age, WH zinc-copper ratio (Zn/Cu ratio), and serum Zn/Cu ratio were significantly associated the development of CVD in men, and WHR, age, BMI, serum Cu, and Cu/Zn ratio in women. DT analysis showed that, age was the most important predictor of CVD in both genders. 71% of women, older than 49 years, with a WHR≥ 0.89, serum Cu< 75 (µg/dl), BMI≥ 22.93 (kg/m 2 ), and serum Cu≥ 14 (µg/dl), had the highest risk of CVD. In men, among those who were ≥ 53 years, with a WHR≥ 0.98, serum Zn/Cu ratio< 1.69, and BMI≥ 22.30, had the highest risk of CVD., Conclusion: Among Iranian adult population, BMI, age, and WHR were one of the predictors of CVD for both genders. The Zn/Cu ratio was CVD predictor for men while Cu/Zn ratio was CVD predictor for women., Competing Interests: Declaration of Competing Interest The authors confirm no conflicts of interest., (Copyright © 2024 Elsevier GmbH. All rights reserved.)

Background: The benefits of using Alteplase are time-dependent. This study aimed to evaluate delays between the onset of symptoms and the administration of Alteplase and related factors in patients with acute ischemic stroke (AIS)., Materials and Methods: In this cross-sectional study, 60 AIS patients receiving Alteplase were selected by census sampling from July 2020 to July 2021 from the eligible patients referred to Shahid Beheshti Hospital in Kashan, Iran. The data collection tool was a researcher-made questionnaire containing demographic information, time periods from the onset of symptoms to the injection of Alteplase, and associated factors. The required information was collected from the patients, their relatives, their health records, and Kashan Emergency Medical Service (EMS) information system. Data were analyzed in SPSS-16., Results: Eighty-five percent of the 60 patients participating in the study were transferred to the hospital by EMS ambulances. The mean time intervals between different phases were as follows: Onset-To-Door (OTD) time 81.35 ± 33.76 minutes; Door-To-CT (DTC) scan time 16.12 ± 17.46 minutes; Door-To-Needle (DNT) time 51.30 ± 26.14 minutes; and the overall Onset-To-Needle (ONT) time 133.75 ± 39.17 minutes. Also, the mean ONT in people transferred by EMS was about 129 minutes, and the longest prehospital delay in these patients was related to the time between the arrival of the EMS ambulance to the hospital. Marital status and geographical location where the stroke had occurred showed a significant relationship with prehospital delay and pre-hospital notification (PHN) by EMS But there was no relationship between underlying diseases or economic status and prehospital delays; also, the patient's diastolic blood pressure at the time of receiving Alteplase showed a significant relationship with in-hospital delay., Conclusion: The findings of the study showed that the majority of people trust and use EMS ambulances to transfer to the hospital and the time spent in different stages, from the onset of symptoms to the injection of the thrombolytic drug, was in an acceptable range in the patients., Competing Interests: There are no conflicts of interest., (Copyright: © 2024 Journal of Education and Health Promotion.)

As threat vectors and adversarial capabilities evolve, Cloud-Assisted Connected and Autonomous Vehicles (CCAVs) are becoming more vulnerable to cyberattacks. Several established threat analysis and risk assessment (TARA) methodologies are publicly available to address the evolving threat landscape. However, these methodologies inadequately capture the threat data of CCAVs, resulting in poorly defined threat boundaries or the reduced efficacy of the TARA. This is due to multiple factors, including complex hardware-software interactions, rapid technological advancements, outdated security frameworks, heterogeneous standards and protocols, and human errors in CCAV systems. To address these factors, this study begins by systematically evaluating TARA methods and applying the Spoofing, Tampering, Repudiation, Information disclosure, Denial of service, and Elevation of privileges (STRIDE) threat model and Damage, Reproducibility, Exploitability, Affected Users, and Discoverability (DREAD) risk assessment to target system architectures. This study identifies vulnerabilities, quantifies risks, and methodically examines defined data processing components. In addition, this study offers an attack tree to delineate attack vectors and provides a novel defense taxonomy against identified risks. This article demonstrates the efficacy of the TARA in systematically capturing compromised security requirements, threats, limits, and associated risks with greater precision. By doing so, we further discuss the challenges in protecting hardware-software assets against multi-staged attacks due to emerging vulnerabilities. As a result, this research informs advanced threat analyses and risk management strategies for enhanced security engineering of cyberphysical CCAV systems.