Academic Emergency Medicine最新文献

{"title":"Diagnostic Yield of Hospitalization for Emergency Department Patients With Syncope and Presyncope.","authors":"Christopher W Baugh, Carolyn Winskill, Edward H Suh, Dana L Sacco, John DeAngelis, Daniel K Nishijima, Jonathan Schimmel, Alan B Storrow, Nancy Wood, Robert E Weiss, Marc A Probst","doi":"10.1111/acem.70393","DOIUrl":"10.1111/acem.70393","url":null,"abstract":"<p><strong>Objectives: </strong>Syncope and presyncope are common emergency department (ED) presentations that may indicate dangerous underlying conditions. For patients without serious ED diagnoses, hospitalization for monitoring and further workup is common, yet the benefits remain unclear. We sought to determine the diagnostic yield of hospitalization among adults with unexplained syncope or presyncope.</p><p><strong>Methods: </strong>We conducted a secondary analysis of data from a prospective, multicenter, observational study enrolling ED patients aged ≥ 40 years with syncope or presyncope and no serious ED diagnosis. We collected 30-day serious adverse outcomes (SAOs), both cardiac and non-cardiac, including only in-hospital SAOs for admitted patients and all SAOs for discharged patients. Logistic and Cox regression analyses compared admitted and discharged participants using propensity score adjustment and matching.</p><p><strong>Results: </strong>Among 1263 patients (mean age 64.8 ± 13.1 years), 74 (5.9%) experienced any SAO, including 62 (4.9%) with serious cardiac outcomes. After propensity-score adjustment, Bayesian logistic regression showed a significant difference in diagnostic yield (OR 3.70 [95% CrI 1.85-6.82]) in the hospitalized cohort. In a propensity-score-matched Cox regression analysis, hospitalization was associated with a shorter time to SAO diagnosis, with an HR of 12.43 (95% CI 2.94-52.48).</p><p><strong>Conclusion: </strong>Hospitalization increased the diagnostic yield for SAOs and accelerated time to diagnosis. It is reasonable to hospitalize select, higher-risk adult patients over 40 years old with presyncope or syncope, even if no dangerous diagnosis is found in the ED.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov identifier: NCT04533425.</p>","PeriodicalId":7105,"journal":{"name":"Academic Emergency Medicine","volume":"33 8","pages":"e70393"},"PeriodicalIF":3.2,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13455808/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148700376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transforming Human-AI Collaboration in Emergency Care: The Role of AI in Adaptive Support Across Diagnostic Reasoning Modes.","authors":"Colin John Greengrass, Mike Clancy, Samuel G Campbell, Pat Croskerry","doi":"10.1111/acem.70398","DOIUrl":"https://doi.org/10.1111/acem.70398","url":null,"abstract":"","PeriodicalId":7105,"journal":{"name":"Academic Emergency Medicine","volume":"33 8","pages":"e70398"},"PeriodicalIF":3.2,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13494691/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148786859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Age as a Predictor of Mortality, Disability, or Need for Acute Resuscitative Care in Trauma Patients.","authors":"Matthew J Bivens, Ryan C Burke, Christie L Fritz, Michael Skaggs, James Sargent, Alok Gupta, Charles Parsons, Emily Moore, Stephen H Thomas, Carlo L Rosen","doi":"10.1111/acem.70356","DOIUrl":"10.1111/acem.70356","url":null,"abstract":"<p><strong>Objective: </strong>Geriatric trauma patients are at increased risk of death or disability, and some have proposed trauma team activations based on advanced age alone. We sought to determine if there is a specific age at which a different approach to the trauma patient should be taken, based on their age-related risk for death, disability, or for needing acute resuscitative care.</p><p><strong>Methods: </strong>We conducted a retrospective review of one year of data (2022) abstracted from the National Trauma Data Bank, including 984,335 adult trauma patients. The primary outcome was in-hospital mortality. Secondary outcomes were non-functional status at discharge, and a composite outcome created to capture the need for acute trauma interventions that included death in the ED, admission to the ICU, or need for emergent surgery, intubation, angioembolization, blood transfusions or procedures.</p><p><strong>Results: </strong>Analyses adjusted for covariates showed the risk of receiving any acute intervention, including transfusions, surgeries, intubations and bedside procedures, all fell steadily with advancing age, as did risk of immediate death in the emergency department. Risk of death later during hospitalization, or of discharge to a non-functional status, rose steadily with advancing age.</p><p><strong>Conclusion: </strong>Trauma patients have rising mortality with advancing age, and a rise in likelihood of being sent to the ICU for care, but a falling rate of immediate, up-front death in the trauma bay, and a falling rate of receiving the acute, life-saving interventions associated with a trauma team activation. Further investigation is needed to determine the extent to which these findings illustrate differences in injury mechanism and severity, or age-related bias and differences in care.</p>","PeriodicalId":7105,"journal":{"name":"Academic Emergency Medicine","volume":"33 8","pages":"e70356"},"PeriodicalIF":3.2,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13429948/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148663372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Caring for Patients in Immigration Custody: Clinical and Legal Considerations for Emergency Medicine Clinicians.","authors":"Ellen Shank, Jennifer Whitlock, Matthew Lopas, Amy Zeidan, Theresa Cheng","doi":"10.1111/acem.70397","DOIUrl":"https://doi.org/10.1111/acem.70397","url":null,"abstract":"<p><p>Emergency departments (EDs) are increasingly sites of interaction between clinicians and federal immigration authorities. Recent shifts in federal enforcement policy have intensified these encounters. Patients now more frequently arrive in custody, accompanied by immigration enforcement officers who may assert control over communication, decision-making, or access to patients. These circumstances introduce challenges for maintaining standard clinical practice. Clinicians may encounter situations in which patient confidentiality, informed consent, and independent medical judgment are difficult to operationalize in the presence of immigration enforcement officers. In addition to impacts on patient care, these encounters may contribute to clinician moral injury and distress, particularly when emergency medicine (EM) clinicians feel pressured to compromise patient privacy, deviate from standard practices, or navigate conflicts between enforcement priorities and patient care priorities. Uncertainty regarding institutional policy and the appropriate limits of immigration enforcement authority may exacerbate tensions related to liability and compliance. For patients, disruptions in care and delays in treatment may increase the risk of adverse outcomes. In response to these urgent concerns, the National Immigration Law Center (NILC), a leading advocacy organization in U.S. immigration, has developed Advocating On Behalf of Patients in ICE Custody: A Resource for Health Care Providers and Medical Staff, a national resource guide outlining practical considerations for clinicians and healthcare institutions caring for patients in immigration custody. In this commentary, we build on this resource to provide practical, bedside-oriented guidance for EM clinicians when interacting with immigration enforcement officers or caring for patients in immigration custody. We examine the implications of immigration enforcement within healthcare settings while articulating a path forward that protects patient rights, clinical integrity, and the ethical foundations of medical practice. The following highlights clinical questions that EM clinicians may have when caring for patients in immigration custody or interacting with immigration enforcement officials in hospital settings.</p>","PeriodicalId":7105,"journal":{"name":"Academic Emergency Medicine","volume":"33 8","pages":"e70397"},"PeriodicalIF":3.2,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13494437/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148786823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Racial and Ethnic Composition of the U.S. Emergency Medicine Workforce, Change From 2013 to 2023.","authors":"Cameron J Gettel, Michael Gottlieb, Yvette Calderon, Deborah B Diercks, Michelle D Lall, Craig Rothenberg, Pooja Agrawal, Arjun K Venkatesh","doi":"10.1111/acem.70394","DOIUrl":"10.1111/acem.70394","url":null,"abstract":"","PeriodicalId":7105,"journal":{"name":"Academic Emergency Medicine","volume":"33 8","pages":"e70394"},"PeriodicalIF":3.2,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13455769/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148700346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thirty-Eight Years a Clinician … and What's Next?","authors":"Jonathan A Edlow","doi":"10.1111/acem.70396","DOIUrl":"10.1111/acem.70396","url":null,"abstract":"","PeriodicalId":7105,"journal":{"name":"Academic Emergency Medicine","volume":"33 8","pages":"e70396"},"PeriodicalIF":3.2,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13488536/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148786847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Team Approach to Patient-Centered Communication in the Emergency Department.","authors":"Colleen K Gutman, Joseph R Keebler, Rosemarie Fernandez, Carma L Bylund, Lauren Hamel, Maritza Plaza, Cameron Busk, Elizabeth H Lazzara","doi":"10.1111/acem.70382","DOIUrl":"10.1111/acem.70382","url":null,"abstract":"<p><p>Patient-centered communication (PCC) underpins high-quality medical care, yet its traditional dyadic, longitudinal models are ill-suited to the emergency department (ED). In the ED, visits are brief, unpredictable, and often involve clinicians and patients with no prior relationship. This mismatch creates a paradox: the fast-paced, high-uncertainty environment heightens the need for PCC while simultaneously impeding its enactment. Drawing on the science of teamwork, we propose conceptualizing PCC as a team process. Our approach reconceptualizes communication as a coordinated, interdisciplinary process. In this model, an ED PCC team-comprising physicians, nurses, ancillary staff, and the patient (and caregivers when appropriate)-functions as a \"swift-starting action team,\" required to achieve high-stakes goals shortly after formation. By integrating teamwork constructs, including the input-process-outcome-input model and the consideration of team cognition, our proposed conceptualization expands the scope of PCC research and creates a pathway to design interventions that facilitate PCC in the fast-paced ED setting. This opens new avenues for research, education, and quality improvement across emergency settings.</p>","PeriodicalId":7105,"journal":{"name":"Academic Emergency Medicine","volume":"33 7","pages":"e70382"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13422259/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148617955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond a Diagnosis: A Qualitative Study Exploring Patient and Caregiver Expectations About Emergency Department Visits Amid Uncertainty.","authors":"Laura J Chien, Jennifer Morris, Ann Lawless, Sam Scanlan, Carmel Crock, Maria R Dahm","doi":"10.1111/acem.70376","DOIUrl":"10.1111/acem.70376","url":null,"abstract":"<p><strong>Objectives: </strong>Patients presenting to emergency departments (EDs) have been described as expecting a diagnosis or explanation for symptoms, yet diagnostic uncertainty is especially prevalent for those with nonspecific symptoms like headache, dizziness, abdominal pain, and chest pain. Given limited research examining patient and caregiver expectations about diagnosis when uncertainty exists, we aimed to investigate these expectations to inform safe, high quality, patient-centered diagnostic communication in emergency settings.</p><p><strong>Methods: </strong>We conducted a qualitative study in two Australian metropolitan EDs using semi-structured interviews with patients presenting with nonspecific symptoms (n = 24) and their caregivers (n = 11) about their expectations regarding the visit and diagnosis. We analyzed interview transcripts in NVivo using content and thematic analysis.</p><p><strong>Results: </strong>Participant expectations about their ED visit and diagnosis were shaped by previous healthcare experiences, understanding of symptom characteristics, familiarity with medical knowledge and uncertainty tolerance. Three themes captured expectations by content: outcomes (understanding, treatment and guidance), processes (diagnostic investigations and being taken seriously), and the health service (timely, integrated care). While most participants reported wanting a diagnosis or explanation, many demonstrated awareness of diagnostic uncertainty and its implications, revealing diverse expectations across a certainty spectrum. Many expected diagnostic investigations, regarding them as integral to determining outcomes but recognized they may not resolve uncertainty. Some regarded EDs as a 'one-stop shop' providing timely diagnostic outcomes. Patients who had previously experienced symptom invalidation expressed strong expectations about being taken seriously.</p><p><strong>Conclusions: </strong>Patient and caregiver expectations about their ED visit and diagnosis are more nuanced than previously recognized. Findings highlight the importance of clinicians soliciting and responding to hopes and expectations in ways that address the uncertainty inherent in diagnosis. Understanding patient and caregiver hopes and expectations better equips clinicians to communicate in a patient-centered way about diagnosis and the diagnostic process in EDs, to enhance care even when uncertainty persists.</p>","PeriodicalId":7105,"journal":{"name":"Academic Emergency Medicine","volume":"33 7","pages":"e70376"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13422665/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148617888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Validation of Machine Learning Models to Optimize Imaging and Referrals for Dizziness in the Emergency Department.","authors":"Danielle Carole Roy, David Savage, Saswata Deb, Salimur Choudhury, Robert Ohle","doi":"10.1111/acem.70369","DOIUrl":"10.1111/acem.70369","url":null,"abstract":"<p><strong>Background: </strong>Dizziness and vertigo are common emergency department (ED) presentations, but only 2%-5% receive a serious diagnosis, such as stroke or transient ischemic attack (TIA). Due to the lack of reliable validated prediction tools, many undergo unnecessary imaging and consultations, highlighting the need for improved risk stratification.</p><p><strong>Objective: </strong>To develop machine learning (ML) models that predict serious diagnoses in ED patients presenting with dizziness or vertigo.</p><p><strong>Methods: </strong>This multicenter cohort study included 6637 ED patients with dizziness, vertigo, or imbalance from September 2014-December 2022. The primary outcome was a serious diagnosis-stroke, TIA, vertebral artery dissection, or brain tumor-within 30 days, adjudicated by a blinded committee. Data were split 80/20 into training and test sets. Four ML models (decision tree, LASSO logistic regression, random forest, XGBoost) were trained on 17 variables using 5-fold cross-validation and evaluated alongside the Sudbury Vertigo Risk score. Performance was assessed using area under the curve (AUC) and diagnostic accuracy measures. Computed tomography (CT) and referral rates were hypothetically compared pre- and post-model application.</p><p><strong>Results: </strong>Among 6637 patients (mean age 78.1; 57.8% female), 3.3% had a serious diagnosis. All ML models demonstrated strong discrimination, with AUCs ranging from 0.92 to 0.97. At a 5% predicted probability threshold, sensitivities ranged from 53%-97% and specificities from 84% to 96%. Logistic regression with LASSO demonstrated a favorable balance between discrimination (AUC: 0.97, sensitivity: 97% and specificity: 91%), although confidence intervals overlapped substantially across models. In a hypothetical model-based analysis, ML-guided classification corresponded to projected reductions in CT utilization and referrals ranging from 53%-85% and 11%-73%, respectively.</p><p><strong>Conclusions: </strong>Select ML models demonstrated discrimination comparable to the Sudbury Vertigo Risk Score while potentially improving specificity and reducing projected resource utilization. These tools show promise, but external validation is needed.</p>","PeriodicalId":7105,"journal":{"name":"Academic Emergency Medicine","volume":"33 7","pages":"e70369"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148358934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evidence-Based Medicine Meets Artificial Intelligence: Reframing Critical Appraisal in Emergency Medicine.","authors":"Sangil Lee, Michael Brown, Rebekah Richards, Moira Smith","doi":"10.1111/acem.70381","DOIUrl":"10.1111/acem.70381","url":null,"abstract":"","PeriodicalId":7105,"journal":{"name":"Academic Emergency Medicine","volume":"33 7","pages":"e70381"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13373350/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148454213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}