Eurasian Journal of Chemical, Medicinal and Petroleum Research

Abstract Background: Heart failure (HF) is a chronic, progressive condition with high prevalence and mortality rates worldwide. Despite advances in medical management, patients with HF face significant challenges in self-care, leading to poor clinical outcomes and frequent hospital readmissions. Adherence to self-care behaviors is critical for reducing hospital readmissions, yet many patients struggle with maintaining these behaviors due to insufficient education and follow-up.

Objective: This study examined the impact of the Continuous Care Model (CCM) on self-efficacy and hospital readmission among patients hospitalized with HF.

Methods: This quasi-experimental study conducted on 70 patients with HF visiting two teaching hospitals in southeastern Iran in 2021. Patients were selected using convenience sampling and randomly assigned to two groups: control (n=35) receiving routine care and intervention (n=35) receiving CCM. The intervention consisted of six individual training sessions during hospitalization, six sessions post-discharge, and weekly telephone follow-up until the twelfth week. Data collected using a demographic form, readmission assessment, and Sullivan's Cardiac Self-Efficacy Scale. Analysis was performed using SPSS version 22 with chi-square, independent and paired samples t-tests, and ANCOVA at P < 0.05 significance level.

Results: ANCOVA revealed significantly higher self-efficacy scores in the intervention group after implementing CCM (P = 0.001). Independent t-test results showed that readmission frequencies in the control group (1.03 ± 1.01) were significantly higher than in the intervention group (0.34 ± 0.68) (P = 0.001).

Conclusion: The Continuous Care Model significantly improved self-efficacy and reduced hospital readmission frequency among patients with HF. Given its ease of implementation, applicability, and low cost, healthcare authorities recommended to develop policies for implementing CCM for HF patients.

Abstract Breast cancer remains one of the leading causes of cancer-related mortality among women globally, highlighting the critical need for early detection and accurate diagnosis. Recent advances in artificial intelligence (AI), encompassing both machine learning (ML) and deep learning (DL) approaches, have demonstrated significant potential in enhancing diagnostic accuracy, reducing human error, and supporting clinical decision-making. This systematic review critically analyzes existing studies that employ AI for breast cancer detection, focusing on methodological approaches, dataset characteristics, model performance, and interpretability. ML-based techniques, including support vector machines, random forests, and gradient boosting, show promising results in structured datasets, particularly where dataset sizes are limited, and interpretability is essential. In contrast, DL approaches, primarily convolutional neural networks and their variants, outperform ML in raw image analysis, multi-modal imaging, and complex feature extraction, achieving higher accuracy and sensitivity. Hybrid models integrating ML and DL, often augmented with radiomics features, offer a balanced framework, combining high predictive performance with improved interpretability. Additionally, explainable AI (XAI) techniques are increasingly applied to DL models, mitigating the “black-box” problem and fostering clinical trust. Despite these advancements, challenges remain, including the need for large, high-quality, multi-institutional datasets, computational resource demands, and generalizability across diverse populations. Low-resource and portable AI solutions offer potential for broader accessibility, though with modest reductions in predictive performance. Overall, AI demonstrates transformative potential in early breast cancer detection, particularly when combined with hybrid and explainable frameworks. Future research should prioritize multi-modal integration, rigorous cross-center validation, and deployment strategies that balance accuracy, interpretability, and accessibility, ultimately facilitating clinical adoption and improving patient outcomes.

Abstract Backgrounds: The aim of the preset study was to evaluate the effect of mindfulness interventions on psychological detachment from work.

Methods: MEDLINE (PubMed and Ovid), Web of Science and Scopus were among the international databases searched for relevant study keywords up to December 2024 for this systematic review and meta-analysis. This study included RCT studies published in English. STATA/MP. Data were analyzed using v17 software.

Results: Six studies included in present meta-analysis. The mean differences of psychological detachment scores between the mindfulness intervention before and after the intervention were 0.97 (MD = 0.97; 95% CI = [0.85–1.10]; p < 0.01; I2 = 88.59%; p<0.01).

Conclusion: two, six and eight-week mindfulness-based interventions can effectively extent improve psychological detachment.

Abstract Objectives: Globalization has led to increasingly diverse patient populations in healthcare settings. Emergency departments (EDs), as high-pressure, fast-paced environments, require staff to possess strong communication and social interaction skills to ensure quality care. This study aimed to investigate the relationship between cultural intelligence (CQ) and the communication skills and social interactions of ED staff members.

Methods: This cross-sectional study conducted on 197 ED staff members from three hospitals in Zanjan, Iran, in 2019. Data collected using the Cultural Intelligence Scale (CQS), a Communication Skills Scale, and a Social Interactions Questionnaire. Data analysis performed using descriptive statistics and correlation tests.

Results: Participants' mean scores for cultural intelligence and communication skills were 85.78 ± 6.24 (out of 140) and 55.41 ± 3.9 (out of 90), respectively. For social interactions, the mean score for positive thoughts (47.86 ± 4.14) was higher than for negative thoughts (33.01 ± 3.92). The total CQ score showed a significant positive correlation with communication skills (P < 0.001). Furthermore, higher CQ scores were significantly associated with increased positive thoughts and decreased negative thoughts (P < 0.001).

Conclusions: The findings demonstrate that higher cultural intelligence among ED staff is associated with better communication skills and positive social interactions. Healthcare leaders recommended to educational programs and workshops to enhance the cultural intelligence of ED personnel, which can improve both staff communication and the quality of patient care.

Abstract Context: Cardiac arrest remains one of the leading causes of death worldwide, with survival rates remaining low despite advances in treatment protocols. Nurses play a critical role as first responders in cardiopulmonary-cerebral resuscitation (CPCR). Therefore, ensuring adequate CPCR training for nursing staff is essential to improve patient outcomes.

Objective: This systematic review aimed to provide an overview of CPCR training methods for nurses in Iran and to evaluate their effectiveness in improving nurses'' knowledge, skills, and performance.

Methods: A systematic search conducted in international databases including PubMed, Scopus, CINAHL, Google Scholar, and Persian databases including SID, IranMedex, and Magiran for articles published between 2010 and 2020. English and Persian keywords including "education," "training," "cardiopulmonary-cerebral resuscitation," "nurses," "knowledge," "skill," and "performance" were used. 21 articles were identified; after removing duplicates and screening for relevance, 10 studies were included in the final review. Quality assessment performed using appropriate critical appraisal tools.

Results: The review identified three main categories of CPCR training methods: conventional (lectures, pamphlets, and mannequin practice), modern (simulation, workshops, video-based, and flipped classroom), and integrated approaches. Conventional methods primarily improved knowledge but showed limited effects on skills retention. Modern and integrated methods demonstrated superior outcomes in enhancing both knowledge and practical skills. Simulation-based and workshop approaches yielded the highest skill acquisition and satisfaction levels among nurses.

Conclusions: Integrated training methods combining conventional and modern approaches are the most effective for improving nurses'' CPCR competence. Healthcare policymakers and educational managers should implement standardized, multifaceted training programs with regular refresher courses to maintain CPCR skills.

Abstract Dental caries is one of the most prevalent chronic diseases in childhood, significantly affecting preschool-aged children’s oral health, nutrition, and quality of life. Socioeconomic factors, including family income and residential environment, have been proposed as determinants influencing the prevalence and severity of dental caries. This systematic review aims to synthesize current evidence examining the relationship between preschool children’s dental caries experience and their place of residence (urban vs. rural) and family income levels. A structured literature (37 articles) search was performed using PubMed, Scopus, Web of Science, and Google Scholar databases for studies published from 2010 to 2025. Findings consistently indicate that children from lower-income families and rural areas exhibit higher caries prevalence and severity, reflecting disparities in access to dental care, dietary patterns, and oral hygiene practices. Interventions targeting vulnerable populations, including community-based preventive programs and socioeconomic policy measures, are warranted to reduce oral health inequalities.

Abstract Introduction: The importance of anesthesia management in epileptic patients lies in its direct impact on perioperative safety and neurologic outcomes. Inadequate anesthetic planning can precipitate breakthrough seizures, complicate recovery, and increase morbidity.

Material and methods: This systematic review and meta-analysis, conducted according to PRISMA guidelines, will evaluate randomized controlled trials and observational studies on anesthetic management in epileptic patients. Comprehensive database searches and standardized selection and extraction processes will be used. Outcomes include perioperative seizures and anesthetic complications. Study quality and heterogeneity will be rigorously assessed using validated tools and statistical analyses, ensuring reliable synthesis of current evidence to inform clinical anesthesia practices in this population.

Results: Based on the defined search strategy, 246 records were identified and narrowed through duplicate removal and rigorous screening to 8 studies included in the final qualitative synthesis. These studies, conducted internationally between 2014 and 2021, used varied designs and sample sizes to address perioperative seizure outcomes, anesthetic complications, recovery time, and hemodynamic stability, providing comprehensive and detailed evidence on anesthesia management in epileptic patients.

Conclusion: This systematic review demonstrates that, with careful selection of anesthetic protocols and individualized perioperative management, patients with epilepsy can undergo surgery with manageable rates of seizures and complications.

Abstract Introduction: This systematic review aims to synthesize evidence regarding medical and nursing care for patients with neurological diseases undergoing surgery, with a focus on pre- and post-operative considerations. This review underscores the need for standardized protocols that integrate medical and nursing perspectives in perioperative neurological care. While substantial progress has been made, gaps remain in consistent implementation of evidence-based practices and patient-centered approaches. Future research should focus on developing integrated care models and evaluating their effectiveness in enhancing surgical outcomes for patients with neurological diseases.

Methodology: Following PRISMA-based methodology, key areas include preoperative assessment, risk optimization, perioperative medication management, anesthetic strategies, and post-operative bundles of care such as hemodynamic control, secondary brain injury prevention, venous thromboembolism (VTE) prophylaxis, infection prevention, nutrition, pain management, early rehabilitation, and patient/family education.

Findings: Findings indicate that pre-operative considerations should prioritize accurate neurological assessment, optimization of comorbidities, psychological support, and patient education to enhance compliance and reduce anxiety. Pre-operative imaging, medication management (e.g., anticonvulsants, anticoagulants), and nutritional status evaluation were also identified as critical. Intraoperative nursing care, though less frequently studied, emphasizes the importance of hemodynamic stability, intracranial pressure monitoring, and prevention of complications such as hypoxia and infection.

Conclusion: Optimal perioperative care for neurosurgical patients requires a standardized, multidisciplinary, and nursing-centered approach. Critical elements include risk assessment, medication management, neuro-focused anesthesia and monitoring, structured post-op neurological checks, complication prevention, multimodal analgesia, nutrition/dysphagia management, early rehabilitation, and robust patient/family education. Adoption of ERAS pathways and quality monitoring can significantly improve outcomes and reduce healthcare costs.