Archives of Academic Emergency Medicine最新文献

{"title":"The Primary Sources of Interruptions Experienced by Physicians and Nurses in Emergency Departments: A Scoping Review.","authors":"Navaz Emadi, Rita Mojtahedzadeh, Seyyed Farshad Allameh, Kamal Basiri, Aeen Mohammadi","doi":"10.22037/aaem.v14i1.2919","DOIUrl":"10.22037/aaem.v14i1.2919","url":null,"abstract":"<p><strong>Introduction: </strong>Interruptions are common in emergency departments (ED) and frequently occur during critical clinical tasks. These interruptions disrupt workflow, reduce situational awareness, increase the risk of errors, and may compromise patient safety. Identifying and mapping their sources is therefore essential to guide targeted strategies and improve the quality of care. This scoping review aimed to identify and categorize the primary sources of work-related interruptions among physicians and nurses in the ED.</p><p><strong>Methods: </strong>The review question, developed using the PCC framework (physicians and nurses; work-related interruptions; EDs), sought to identify the primary sources of interruptions in ED settings. A comprehensive search was performed in PubMed, Scopus, Embase, Web of Science, and Google Scholar to locate peer-reviewed studies published up to September 2025. Two reviewers independently screened the studies and extracted the data.</p><p><strong>Results: </strong>A total of 12 studies met the inclusion criteria. Reported interruption rates varied across settings and professional roles. The primary sources of interruptions were grouped into six major categories: colleague interference, phone and pager alerts, patient-initiated interruptions, family or companion interference, technical failures and lack of resources, and environmental noise. Most interruptions occurred at nursing or physician workstations and during medication preparation, documentation, or direct patient care.</p><p><strong>Conclusion: </strong>This scoping review provides a comprehensive overview of the main sources of interruptions in ED. Understanding where and why these interruptions occur can guide the development of targeted educational, organizational, and environmental interventions. Reducing avoidable interruptions may enhance staff performance, improve patient safety, and optimize the quality of emergency care.</p>","PeriodicalId":8146,"journal":{"name":"Archives of Academic Emergency Medicine","volume":"14 1","pages":"e11"},"PeriodicalIF":2.8,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13265070/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148257149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of an Online Body Camera System for Medical Oversight in Prehospital Emergency Care: An 11-Year Retrospective Cohort Study.","authors":"Malivan Phontabtim, Chaiyaporn Yuksen, Satariya Trakulsrichai, Pungkava Sricharoen, Kasamon Aramvanitch, Welawat Tienpratarn, Siriporn Damdin, Suteenun Seesuklom, Natthaphong Thiamdao, Chantarat Palee, Chayapon Nontun, Paijit Bunta","doi":"10.22037/aaem.v14i1.2916","DOIUrl":"10.22037/aaem.v14i1.2916","url":null,"abstract":"<p><strong>Introduction: </strong>The online body camera system (OBCS) integrates telemedicine technology with real-time monitoring of on-scene operations, direct online medical direction, and coordinated patient care. This study aimed to evaluate its effectiveness compared with the traditional telephone-based medical oversight system.</p><p><strong>Methods: </strong>This retrospective cohort study evaluated the effectiveness of OBCS in prehospital emergency care of Ramathibodi Hospital by comparing outcomes (survival rate, length of stay) between the traditional telephone-based (2014-2021) and the OBCS periods (2022-2024) in emergency medical operation unit.</p><p><strong>Results: </strong>This 11-year retrospective cohort study analyzed 5,721 prehospital emergency care cases (3,398 cases managed under the traditional telephone-based system and 2,323 cases managed under the OBCS). The findings indicate that the implementation of the OBCS significantly improved overall survival to emergency department (ED) arrival (adjusted odds ratio (aOR) = 8.32, 95% CI: 1.47-47.14, P = 0.017), particularly among out-of-hospital cardiac arrest (OHCA) patients (aOR = 7.99, 95% CI: 1.28-50.03, P = 0.026). However, the new system did not result in significant improvements in survival to hospital admission or survival to hospital discharge. Furthermore, the length of stay (LOS) in the ED, intensive care unit (ICU), and overall hospital setting remained unchanged.</p><p><strong>Conclusions: </strong>The OBCS significantly enhanced survival to ED arrival, particularly among OHCA patients. However, the LOS in the ED, ICU, and overall hospital setting remained unchanged.</p>","PeriodicalId":8146,"journal":{"name":"Archives of Academic Emergency Medicine","volume":"14 1","pages":"e10"},"PeriodicalIF":2.8,"publicationDate":"2026-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13265074/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148257064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current Status and Determinant Factors of Telemedicine Adoption in Selected Commonwealth of Independent States (CIS) Countries; A Mix Method Study.","authors":"Safarov Mahir Alisa, Mammadzada Aytan Yagub, Polukhova Shahzada Musa, Abaszade Zumrud Amirgulu, Ismayilova Shalala Garib, Mammadov Fuad Yusir, Mahmudova Parvana Akbar","doi":"10.22037/aaem.v14i1.2893","DOIUrl":"10.22037/aaem.v14i1.2893","url":null,"abstract":"<p><strong>Introduction: </strong>The field of telemedicine has become an urgent innovation in the healthcare field worldwide, but there is still an unequal distribution of its implementation in transitional economies. This study aimed to evaluate the associated factors of telemedicine adoption in selected countries of the commonwealth of independent states (CIS) region.</p><p><strong>Methods: </strong>A validated survey was used to collect data on 600 healthcare professionals, patients, information technology (IT) specialists and policymakers from selected CIS countries, using a mixed-method design. Through a designed and validated questionnaire, solid statistical techniques, and cross-regional analyses, the barriers and facilitators of telemedicine adoption in studied countries were evaluated.</p><p><strong>Results: </strong>The general average score of telemedicine adoption was 3.84 ± 0.92. The highest mean adoption score was observed in Azerbaijan (4.02 ± 0.85), Russia (3.91 ± 0.88) and Ukraine (3.87 ± 0.91). There were significant differences between regions regarding mean adoption score (p < 0.001). Clinician acceptance (r = 0.64; p < 0.01), infrastructure readiness (r = 0.58; p < 0.01), regulatory maturity (r = 0.42; p < 0.01), and patient digital literacy (r = 0.36; p < 0.01) had the strongest correlation with telemedicine adoption. The most predictive factors of telemedicine adoption were infrastructure readiness (β (standard error; SE) = 0.42 (0.05), p < 0.001), then clinician acceptance (β (SE) = 0.39 (0.06), p < 0.001), patient digital literacy (β (SE) = 0.22 (0.05), p < 0.001), and regulatory maturity (β (SE) = 0.18 (0.04), p < 0.001). Professional experience had a minor yet significant impact (β = 0.09, t = 0.038). Logistic regression showed increased infrastructure readiness score (odds ratio (OR) = 1.48, 95% confidence interval (CI) = 1.21-1.81), clinician acceptance score (OR = 1.56, 95% CI = 1.28-1.92), regulatory maturity score (OR = 1.31, 95% CI = 1.09-1.58), and patient literacy score (OR = 1.22, 95% CI = 1.03-1.45) as the predictors of high telemedicine adoption (≥70%). The model accurately categorized 78.2% of data and the area under the curve 0.79 (95% CI: 0.75-0.83) meaning the model is a strong predictor.</p><p><strong>Conclusion: </strong>The findings showed that the structural investments cannot be made alone without the involvement of professionals. The research contributes to the existing body of transitional economies research by offering strong comparative evidence of telemedicine and provides policy recommendations on how to improve infrastructure, generate harmonization, and capacity building of clinicians and patients to support sustainable digital health ecosystems.</p>","PeriodicalId":8146,"journal":{"name":"Archives of Academic Emergency Medicine","volume":"14 1","pages":"e9"},"PeriodicalIF":2.8,"publicationDate":"2026-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13265075/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148257031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Knowledge and Willingness to Perform Cardiopulmonary Resuscitation by Bystanders in Jordan; A Nationwide Cross-sectional Study.","authors":"Alaa Oteir, Khader Almhdawi, Zainab Alqudah, Rani Shatnawi, Mohammad Al-Magableh, Ahlam Alqudah, Yu-Tung Chang, Brett Williams","doi":"10.22037/aaem.v14i1.2894","DOIUrl":"10.22037/aaem.v14i1.2894","url":null,"abstract":"<p><strong>Introduction: </strong>Bystander-initiated Cardiopulmonary Resuscitation (CPR) strongly influences the Out-of-hospital cardiac arrest (OHCA) survival outcomes; but substantial disparities persist in knowledge levels and willingness to perform CPR. This study aimed to evaluate the CPR knowledge and willingness of bystanders to perform standard versus hands-only CPR among Jordanian adults.</p><p><strong>Methods: </strong>A nationwide cross-sectional study was conducted using a validated questionnaire developed in accordance with American Heart Association (AHA) guidelines. The questionnaire assessed demographic characteristics, prior CPR training, knowledge (10 items), and willingness (attitude) of bystanders to perform CPR (12 items). Descriptive statistics were used to present the findings, while chi-square and McNemar tests were used to compare groups.</p><p><strong>Results: </strong>A total of 1,242 participants with a mean age of 27.38 ± 9.3 (range: 18-70) years, completed the survey (65.6% female). The mean knowledge score was 4.2 ± 2.3 (range: 0-10), with trained individuals scoring significantly higher than untrained participants (6.1 vs. 3.2, p<0.001). Trained participants exhibited greater willingness to perform CPR across all scenarios (p<0.001), whereas untrained individuals showed higher willingness to provide hands-only CPR, particularly for strangers and neighbors (p<0.01). Males were significantly more inclined to perform CPR across all scenarios (p<0.01), whereas females were more willing to provide hands-only CPR in certain scenarios (p<0.01). Nevertheless, most of the differences became statistically insignificant after restricting the analysis to respondents who witnessed a cardiac arrest event.</p><p><strong>Conclusion: </strong>Trained individuals showed higher levels of willingness, yet untrained participants demonstrated unexpected willingness to perform hands-only CPR, while female participants were consistently less willing to perform standard CPR. However, sensitivity analysis restricted to respondents who had witnessed a cardiac arrest showed that real-life exposure substantially reduces hesitation and narrows group disparities.</p>","PeriodicalId":8146,"journal":{"name":"Archives of Academic Emergency Medicine","volume":"14 1","pages":"e8"},"PeriodicalIF":2.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13265072/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148257073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing the Accuracy of Patient-Perceived Fever, Manual Fever Checking, and Non-Contact Frontal Infrared Thermometer; A Cross-sectional Study.","authors":"Moojan Shabani-Kakroudi, Mohammad Jalili, Ali Pasha Meysamie, Atousa Akhgar, Hamideh Akbari, Mahdi Zangi, Mehrnoosh Aligholi Zahraie, Saeed Aqavil-Jahromi, Mohammad Eftekhari","doi":"10.22037/aaem.v14i1.2883","DOIUrl":"10.22037/aaem.v14i1.2883","url":null,"abstract":"<p><strong>Introduction: </strong>Non-contact frontal infrared thermometers (NCFITs) have gained popularity following the COVID-19 pandemic, but their accuracy remains debated. This study compared the accuracy of three index tests of patient-perceived fever (PPF), manual fever checking (MFC) by emergency nurses, and NCFIT against tympanic thermometer (TT).</p><p><strong>Methods: </strong>This single center, diagnostic accuracy study evaluated adult patients in the triage area of the emergency department (ED) between May and September 2023. Five emergency nurses (ENs) examined patients using convenience sampling with index tests, followed by TT measurement for fever detection as standard test (T≥38°C). The sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR) and accuracy, of PPF, MFC, and NCFIT in detecting the fever were measured and reported with 95% confidence interval (CI). The inter-rater reliability of ENs for MFC among 10 patients (outside the study) was 100%.</p><p><strong>Results: </strong>We included 279 patients with the mean age of 52.2 ± 16.98 years (51.97% male). TT identified 147 as febrile and 132 as non-febrile. The most sensitive index test was MFC, achieving 100% (95%CI: 97.5-100.0) sensitivity, 0 NLR, and 8.25 (95%CI: 5.7-12.1) PLR, with moderate accuracy (93.9% (95%CI: 89.9-96.0)). NCFIT demonstrated the lowest sensitivity (85.71% (95%CI: 78.9-90.9)) but the highest specificity (98.48% (95%CI: 93.6-99.5)) and accuracy (97.5% (95%CI: 93.1-99.8)). When the fever threshold for NCFIT was lowered to 37.5°C, sensitivity increased to 99% (95%CI: 97.4-99.9), NLR decreased to 0.01 (95%CI: 0-0.6), and PLR rose to 49.5 (95%CI: 20.8-90.2), while specificity remained at 98% (95%CI: 94-99.6).</p><p><strong>Conclusion: </strong>MFC/PPF could rule out fever but required NCFIT/TT to rule it in. However, NCFIT achieved the highest NLR and PLR when its fever threshold was set at 37.5 °C.</p>","PeriodicalId":8146,"journal":{"name":"Archives of Academic Emergency Medicine","volume":"14 1","pages":"e7"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13265967/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148262966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of Artificial Intelligence in Diagnosing Pulmonary Embolism: A Systematic Review and Meta-analysis.","authors":"Alireza Farzaei, Fateme Hajzeinolabedini, Babak Sharif Kashani, Mohamad Sadegh Keshmiri, Alireza Khodayari Javazm, Yasaman Farzaei, Mohamad Fereidooni, Behrouz Emamjomeh, Amir Nezami-Asl","doi":"10.22037/aaem.v13i1.2720","DOIUrl":"10.22037/aaem.v13i1.2720","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Introduction: &lt;/strong&gt;Missed or delayed diagnosis of pulmonary embolism (PE) is associated with increased morbidity, mortality, and longer hospitalizations. This study aimed to evaluate the diagnostic accuracy of Artificial Intelligence (AI) models in detecting PE across imaging.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We systematically searched PubMed/MEDLINE, Scopus, Embase and Web of Science from inception to 1 January 2025 without language or regional limits. After removing duplicate results, the remaining records were screened through titles/abstracts, and two reviewers independently assessed full texts. Risk of bias was evaluated in duplicate with the QUADAS-2 tool. Pooled sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio and area under the ROC curve were calculated with random-effects models in STATA 17. Heterogeneity was quantified with Cochran's Q and I², while we explored its sources using subgroup analyses (for categorical moderators) and meta-regression (for continuous moderators). Publication bias was assessed with Deeks' funnel plot and trim-and-fill, and we examined robustness through leave-one-out sensitivity analyses.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 1,432 records were identified through database searches, with 654 duplicates removed. After screening titles and abstracts of 787 articles, 256 full-text articles were assessed for eligibility, and 28 studies met the inclusion criteria. Internal validation phases included 43,330 participants (4,866 PE-positive, 38,463 PE-negative), while external validation phases comprised 3,588 participants (1,699 PE-positive, 1,889 PE-negative). In the internal validation phase, the pooled sensitivity and specificity of AI in PE diagnosis across imaging were 0.91 (95% confidence interval (CI): 0.88-0.95; I²=9%) and 0.94 (95% CI: 0.86-0.98; I²=99.78%), respectively. The positive likelihood ratio (PLR) was 16.08, and the negative likelihood ratio (NLR) was 0.09, both statistically significant (P &lt; 0.001). The pooled diagnostic odds ratio (DOR) was 163.55 (95% CI: 71.30-375.14, I&lt;sup&gt;2&lt;/sup&gt;: 96.1), and the area under the curve (AUC) was 0.95 (95% CI: 0.93 to 0.97), indicating excellent accuracy. In external validation, the pooled sensitivity and specificity were slightly lower at 0.89 (95% CI: 0.79-0.95; I²=95.60%) and 0.88 (95% CI: 0.80-0.93; I²=91.48%), respectively. The DOR was 59.65 (95% CI: 23.53 to 151.17, I&lt;sup&gt;2&lt;/sup&gt;: 89.6) and AUC was 0.94 (95% CI: 0.92 to 0.96, I&lt;sup&gt;2&lt;/sup&gt;: 89.6). There was no significant publication bias detected.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;AI models achieved high diagnostic accuracy in detecting PE through imaging. However, this performance tends to decrease from internal to external validation, highlighting limitations in generalizability. Additionally, substantial heterogeneity was observed across studies, as indicated by high I² values, which should be considered when interpreting the pooled estimates.&lt;/p","PeriodicalId":8146,"journal":{"name":"Archives of Academic Emergency Medicine","volume":"13 1","pages":"e86"},"PeriodicalIF":2.0,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12883040/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146148949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting the Risk of Opioid-induced Respiratory Depression Using ChatGPT-4o and Machine Learning Techniques.","authors":"Mohammad Meshkini, Sayed Masoud Hosseini, Peyman Erfan Talab Evini, Mitra Rahimi, Babak Mostafazadeh, Pooya Eini, Nahal Babaeian Amini, Amirhossein Faghihi, Farhad Esmailsorkh, Sajede Karimi, Mohammad Asadi, Hadi Jalilvand, Nasibeh Rady Raz, Iman Alidadyani, Hadi Jafari, Faraz Zandiyeh, Kiandokht Khorshidi, Maryam Ahadi, Shayesteh Ashrafi-Esfahani, Shahin Shadnia","doi":"10.22037/aaem.v13i1.2832","DOIUrl":"10.22037/aaem.v13i1.2832","url":null,"abstract":"<p><strong>Introduction: </strong>Opioid-induced respiratory depression is a life-threatening complication of opioid overdose. This study aimed to develop a model for predicting the risk of respiratory depression following opioid overdose using ChatGPT-4o.</p><p><strong>Methods: </strong>A retrospective cross-sectional study was conducted on 2,005 patients admitted following opioid overdose at Loghman Hakim Hospital, Tehran, Iran, from February 2021 to February 2024. Demographic data, clinical presentations, interventions, and outcomes of patients were extracted from electronic medical records and a predictive model was developed using a no-code methodology with the assistance of ChatGPT-4o.</p><p><strong>Results: </strong>2,005 patients with the mean age of 32.97 ± 14.86 (Range: 1-100) years were studied (74.5% male). Respiratory depression was observed in 18% of patients upon admission. Naloxone was administered to 37.6% of patients, with higher usage in those requiring intubation. Key predictors included low oxygen saturation (SpO₂), low respiratory rate (RR), and increased heart rate (HR). The predictive model achieved an accuracy of 94.4% (95% confidence interval (CI): 87.0-96.3), a recall of 81.0% (95% CI: 78.0-84.0) for respiratory depression, and an area under the curve (AUC) of 0.98 (95% CI: 0.95-0.99).</p><p><strong>Conclusion: </strong>The study highlights critical clinical predictors of respiratory depression risk in opioid overdose patients and demonstrates the potential of machine learning models in enhancing early detection and intervention.</p>","PeriodicalId":8146,"journal":{"name":"Archives of Academic Emergency Medicine","volume":"13 1","pages":"e85"},"PeriodicalIF":2.0,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12883042/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146148897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accuracy and Clinical Utility of Clinical Predictive Models for Identifying Dizziness with Central Causes; A Retrospective Diagnostic Accuracy Study.","authors":"Shunsuke Soma, Katsunori Ito, Tsukasa Kamitani","doi":"10.22037/aaem.v13i1.2787","DOIUrl":"10.22037/aaem.v13i1.2787","url":null,"abstract":"<p><strong>Introduction: </strong>Although several clinical prediction models (CPMs) have been developed for identifying acute dizziness with central causes, their application in clinical practice remains unclear. This study aimed to evaluate the accuracy and clinical utility of four CPMs in identifying dizziness with central lesions.</p><p><strong>Methods: </strong>This single-center, retrospective, diagnostic accuracy study was conducted at the ED of Aomori Hospital, Japan, from April to March 2023. The area under the receiver operating characteristic curve (AUROC) of four risk stratification models (ABCD2, TriAGe+, PCI, and Sudbury) in predicting dizziness with central causes were evaluated considering the brain imaging (computed tomography (CT) scan and magnetic resonance imaging (MRI)) findings, interpreted by a neurologist or neurosurgeon, as the gold standard. Calibration was evaluated visually using calibration plots. Additionally, analyses of efficacy, safety, and clinical utility using a decision curve were conducted.</p><p><strong>Results: </strong>Of the 3,606 patients identified, 2,958 with the mean age of 65.3 ± 16.4 (range: 15-97.) years were included in the final analysis (64.7% female). 155 (5.2 %) were diagnosed with central lesions. The AUROCs were 0.67 (95% confidence interval (CI): 0.62-0.71) for ABCD2, 0.80 (95% CI: 0.76-0.84) for TriAGe+, 0.82 (0.78-0.86) for PCI, and 0.85 (95% CI: 0.82-0.88) for Sudbury. TriAGe+, PCI, and Sudbury demonstrated good calibration. Among these, the Sudbury model demonstrated the highest diagnostic efficiency, was the only model to meet safety criteria, and provided the highest net benefit in decision curve analysis, particularly at lower predicted prevalence thresholds.</p><p><strong>Conclusion: </strong>The TriAGe+, PCI, and Sudbury models demonstrated strong discriminatory performance and reliable calibration when applied during ED admission at a community hospital. Particularly, the Sudbury model may reduce false-negative outcomes for central lesions, thereby potentially minimizing the need for unnecessary neuroimaging in patients identified as low-risk.</p>","PeriodicalId":8146,"journal":{"name":"Archives of Academic Emergency Medicine","volume":"13 1","pages":"e84"},"PeriodicalIF":2.0,"publicationDate":"2025-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12883870/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146155871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying the Key Factors Influencing Risk Perception Among Healthcare Workers in the Context of Disasters; A Systematic Review.","authors":"Raziyeh Bakhshi Giv, Mohammadreza Amiresmaili, Hojjat Farahmandnia, Ali Sadatmoosavi, Seyed Mobin Moradi, Seyyed Mohammad Reza Hosseini, Samaneh Alinejad","doi":"10.22037/aaem.v13i1.2909","DOIUrl":"10.22037/aaem.v13i1.2909","url":null,"abstract":"<p><strong>Introduction: </strong>Risk perception is a cognitive, multidimensional process through which individuals identify and assess potential threats. This study aimed to systematically review the recent research to identify the key factors influencing the risk perception within healthcare workers operating in critical and disaster scenarios.</p><p><strong>Methods: </strong>This study was conducted as a systematic review in accordance with PRISMA guidelines. A search was performed for articles published between January 2014 and July 2025 in the PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases. Of the 2,154 initial articles, 10 eligible studies were included in the analysis following screening and quality assessment. Quantitative, qualitative, and mixed-methods studies addressing factors influencing healthcare workers' risk perception during disasters were selected, and the data were coded and categorized using thematic analysis.</p><p><strong>Results: </strong>The analysis of the 10 selected studies identified a central theme titled \"Factors Influencing Risk Perception,\" which was further divided into five key domains: 1) Demographic and individual factors, 2) Experience and exposure to risk, 3) Knowledge resources and information capital, 4) Cognitive-emotional attitudes and beliefs, and 5) Protective behaviors and measures.</p><p><strong>Conclusion: </strong>This review demonstrates that healthcare workers' risk perception during disasters is a multifaceted phenomenon shaped by the interaction of individual, experiential, knowledge-based, emotional, and behavioral factors. Understanding these dimensions is crucial for explaining responses and designing interventions to enhance resilience and preparedness among healthcare workers. Based on the conceptual framework, it is recommended that educational programs and organizational policies consider demographic differences, experiences, and the psychosocial needs of staff.</p>","PeriodicalId":8146,"journal":{"name":"Archives of Academic Emergency Medicine","volume":"13 1","pages":"e83"},"PeriodicalIF":2.0,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12883041/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146148977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of 10- and 30-minute Hepatic Ischemia on Total Protein, Albumin, Globulin Fractions, and LDH of Male Albino Rates; An Experimental Study.","authors":"Shalala Garib Ismayilova, Zumrud Amirgulu Abaszade, AygunVugar Kazimli, Nigar Taryel Guliyeva, Hijran Faramaz Khidirova, Maryam Rauf Abbasova, Kamil Sahib Alkishiev","doi":"10.22037/aaem.v13i1.2887","DOIUrl":"10.22037/aaem.v13i1.2887","url":null,"abstract":"<p><strong>Introduction: </strong>Hepatic ischemia results in the dysrhythmia of the intrahepatic hemodynamics. This study aimed to evaluate the changes occurring in the protein metabolism and serum lactate dehydrogenase (LDH) level after hepatic ischemia and assess the effects of antioxidant therapy in this regard.</p><p><strong>Methods: </strong>In this experimental study (with manipulation of ischemia time and antioxidant therapy) 120 male rats were divided into groups of acute hepatic ischemia; acute hepatic ischemia +antioxidant; chronic ischemia using tetra chloromethane; and sham or intact control to evaluate the changes occurring in the protein metabolism (total protein, albumin, and globulin fractions) and LDH level 3, 7, 15, and 30 days after 10- or 30-minute hepatic ischemia induction and effects of antioxidant therapy in this regard.</p><p><strong>Results: </strong>In the 10-minute ischemia group, total protein decreased to 34.69 ± 2.49 g/L at 3 days, while albumin fell to 12.36 ± 0.85 g/L. The inflammatory response was evident through elevated α1-globulin (9.02 ± 1.50 g/L) and LDH (3476.37 ± 324.89 U/L) at day 3, which gradually normalized by day 30. In the 30-minute ischemia group, the effects were more pronounced, with total protein reaching 54.57 ± 1.93 g/L and albumin 34.33 ± 2.20 g/L at day 3, alongside marked increases in α1-globulin (10.35 ± 1.30 g/L), α2-globulin (3.19 ± 0.43 g/L), β-globulin (8.09 ± 2.27 g/L), γ-globulin (5.64 ± 1.08 g/L), and LDH (2301.44 ± 80.07 U/L). After 10- and 30-minute ischemia, α1, α2, β, and γ globulins as well as LDH level were significantly increased at the post-ischemic recovery. The group that received antioxidant showed significantly lower increases in the globulin fractions and LDH level at 3, 7, 15, and 30 days after the procedure.</p><p><strong>Conclusion: </strong>Based on the findings, 10- and 30-minute acute hepatic ischemia had a profound negative effect on protein metabolism, which was reflected in decreased total protein and albumin, and increased globulin fractions and LDH, indicating the presence of continuous hepatocellular injury and a significant inflammatory reaction. Riditox antioxidant therapy had a consistent, albeit incomplete, hepatoprotective effect, which attenuated these biochemical imbalances.</p>","PeriodicalId":8146,"journal":{"name":"Archives of Academic Emergency Medicine","volume":"13 1","pages":"e82"},"PeriodicalIF":2.8,"publicationDate":"2025-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12928732/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147281974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}