American Journal of Emergency Medicine最新文献

{"title":"Emergency department visits for undiagnosed pelvic organ prolapse.","authors":"Angela A Rutkowski, Fareesa Khan, Neeraj Chhabra, Cynthia Brincat, Michele O'Shea","doi":"10.1016/j.ajem.2025.01.059","DOIUrl":"https://doi.org/10.1016/j.ajem.2025.01.059","url":null,"abstract":"<p><strong>Objectives: </strong>To describe women presenting to the emergency department (ED) for previously undiagnosed pelvic organ prolapse (POP). Secondary objective was to determine rates of outpatient specialty follow-up and factors associated with accessing follow-up care.</p><p><strong>Study design: </strong>Retrospective study of patients who presented at 3 EDs affiliated with an urban academic health system that received a new diagnosis of POP between January 2016 and September 2022. Data on demographics, chief complaint, evaluation and interventions performed in the ED, and follow-up care within 3 months post-ED discharge were abstracted from the medical chart. Descriptive statistics and bivariate analyses were used to compare characteristics of women who did and did not follow-up for specialty or subspecialty care.</p><p><strong>Results: </strong>56 patients met inclusion criteria. Mean age was 61.2 ± 17.1 years. The majority identified as either non-Hispanic Black (51.8 %) or Hispanic or Latino (25.0 %). 57.1 % of patients had public insurance. Less than half (42.8 %) of patients underwent follow-up care with a urogynecologist or gynecologist within 3 months after ED discharge. Race was found to be significantly associated with follow-up rates (P = 0.03), with non-Hispanic Black women experiencing the lowest rates (20.7 %) of follow-up.</p><p><strong>Conclusions: </strong>POP causes sufficient distress to prompt an ED encounter. A subset of women overrepresented by Black and publicly insured women utilize the ED for initial POP evaluation, when compared to patients who access initial outpatient POP care. A minority of patients underwent outpatient follow-up. Further research is needed to understand care-seeking behaviors for POP and barriers to timely outpatient follow-up care.</p>","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":"90 ","pages":"164-168"},"PeriodicalIF":2.7,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143076581","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":"Unmasking CHANTER syndrome: A rare neurological consequence of opioid overdose.","authors":"Matthew C Johnson, Kavi Shankar","doi":"10.1016/j.ajem.2025.01.057","DOIUrl":"https://doi.org/10.1016/j.ajem.2025.01.057","url":null,"abstract":"<p><p>The opioid epidemic remains a major public health issue in the U.S., with over 100,000 overdose deaths in 2022, many linked to synthetic opioids. Emergency medicine plays a vital role in managing opioid overdoses, which typically cause CNS depression and respiratory failure. However, atypical presentations are becoming more common, complicating diagnosis and treatment. This case report discusses a patient who developed focal neurologic deficits after an opioid overdose and was found to have radiographic findings suggestive of CHANTER syndrome. Cerebellar-Hippocampal-Basal Nuclei Transient Edema with Restricted Diffusion (CHANTER syndrome), first described in 2019, is marked by restricted diffusion and edema in the cerebellum, hippocampus, and basal ganglia. While most cases involve comatose patients requiring intensive care, the emergency department presentation is less understood. The differential diagnosis includes hypoxic-ischemic encephalopathy, posterior reversible encephalopathy syndrome, and heroin-associated spongiform leukoencephalopathy. Unlike ischemic infarcts, CHANTER syndrome can show significant improvement with aggressive management. Given the rise of opioid use, emergency physicians are likely to encounter more cases with similar presentations. MRI imaging should be considered in patients who do not recover as expected following an opioid overdose. Early identification of complications like CHANTER syndrome can lead to closer neurologic monitoring and neurosurgical intervention that may prevent decompensation or even death.</p>","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143069562","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":"Leveraging artificle intelligence in emergency triage: Methodological insights and considerations.","authors":"Mustafa Altun, Erhan Altunbas, Mehmet Birkan Korgan, Emre Kudu","doi":"10.1016/j.ajem.2025.01.052","DOIUrl":"https://doi.org/10.1016/j.ajem.2025.01.052","url":null,"abstract":"","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048902","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":"Response to letter: Drones reduce the time to defibrillation in a highly visited non-urban area: A randomized simulation-based trial.","authors":"Michiel J van Veelen, Giovanni Vinetti, Tomas Dal Cappello, Frederik Eisendle, Abraham Mejia-Aguilar, Riccardo Parin, Rosmarie Oberhammer, Marika Falla, Giacomo Strapazzon","doi":"10.1016/j.ajem.2025.01.053","DOIUrl":"https://doi.org/10.1016/j.ajem.2025.01.053","url":null,"abstract":"","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048917","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":"Drones reduce the time to defibrillation in a highly visited non-urban area.","authors":"Hui-Wen Lin, Tien-You Hsu, Fu-Shan Jaw, Chien-Chieh Hsieh","doi":"10.1016/j.ajem.2025.01.050","DOIUrl":"https://doi.org/10.1016/j.ajem.2025.01.050","url":null,"abstract":"","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143069073","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":"Identifying risk factors and developing a nomogram for HFNC failure in patients with hypercapnic acute respiratory failure.","authors":"Chenlong Wang, Qingcheng Zhu, Liuzhao Cao, Joseph Walline, Bingxia Wang, Dingyu Tan","doi":"10.1016/j.ajem.2025.01.046","DOIUrl":"https://doi.org/10.1016/j.ajem.2025.01.046","url":null,"abstract":"<p><strong>Background: </strong>Currently, there is a deficiency in nomograms specifically designed for predicting the failure of high-flow nasal cannula (HFNC) oxygen therapy in patients with hypercapnic acute respiratory failure (hypercapnic ARF). The aim of this retrospective study is to develop and evaluate a nomogram that assesses the risk of HFNC failure in this patient population.</p><p><strong>Methods: </strong>Patients with ARF and hypercapnia (PaCO₂ ≥ 45 mmHg in the initial arterial blood gas) who received HFNC in the intensive care unit (ICU) from January 1, 2020 to December 31, 2023 were enrolled in this study. Risk factors were identified through least absolute shrinkage and selection operator regression analysis. A novel nomogram model was subsequently developed using multivariable logistic regression analysis. The model's predictive performance was assessed via receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA).</p><p><strong>Results: </strong>A total of 189 patients were included in the analysis, comprising 128 patients in the HFNC success group and 61 in the HFNC failure group. Multivariate logistic regression identified blood urea nitrogen, calcium, sepsis, and the respiratory rate oxygenation index (ROX) after 4 h of oxygen therapy as independent prognostic factors for HFNC failure. The nomogram exhibited superior performance compared to the Sequential Organ Failure Assessment score (P = 0.011) and the 4-h ROX index (P = 0.001). Additionally, the calibration curve demonstrated satisfactory predictive accuracy, while DCA highlighted the clinical utility of the nomogram.</p><p><strong>Conclusion: </strong>Key demographic and laboratory parameters associated with the failure of HFNC in patients with hypercapnic ARF have been identified. These parameters were used to develop a precise and user-friendly nomogram, which could serve as an effective clinical tool for clinicians.</p>","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":"90 ","pages":"157-163"},"PeriodicalIF":2.7,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143061690","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":"Comments on \"The smell of sepsis: Electronic nose measurements improve early recognition of sepsis in the ED\".","authors":"Hui Xie, Yaqiong Liu","doi":"10.1016/j.ajem.2025.01.049","DOIUrl":"https://doi.org/10.1016/j.ajem.2025.01.049","url":null,"abstract":"","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143068754","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":"ST-elevation myocardial infarction incidence in a high-risk seismic zone.","authors":"Jorge A Ortega-Hernández, Héctor González-Pacheco, Rodrigo Gopar-Nieto, Daniel Sierra-Lara-Martínez, Diego Araiza-Garaygordobil, Salvador Mendoza-García, Alfredo Altamirano Castillo, Leonel G López Villaseñor, Raul Rodrigo Neri-Bale, Anna Elisa Adib-Gracia, Alexandra Arias-Mendoza","doi":"10.1016/j.ajem.2025.01.044","DOIUrl":"https://doi.org/10.1016/j.ajem.2025.01.044","url":null,"abstract":"<p><strong>Introduction: </strong>Earthquakes are unpredictable natural events that can elicit acute physiological responses, potentially triggering cardiovascular events. This study investigates the association between seismic activity and ST-elevation myocardial infarction (STEMI) admissions in a tertiary care hospital in an earthquake-prone region over 19 years.</p><p><strong>Methods: </strong>We analyzed STEMI admissions at a tertiary center in Mexico City from October 2005 to August 2024. Earthquakes with a magnitude ≥6.0 and geographic relevance to Mexico were identified using the USGS database. Admission rates were compared for ±7 days surrounding each earthquake and control periods derived from the same date in the previous year, adjusted for overlaps and seismic events. Poisson regression analyses were used to compare admission rates.</p><p><strong>Results: </strong>Among 9611 STEMI patients, 904 admissions occurred near earthquake periods, with 863 during controls. Post-earthquake admissions rose significantly on the day earthquake (day 0) with an incidence rate ratio (IRR) = 1.49 (95 % CI 1.17-1.89, P = 0.001), and in the post-quake (+1 to +7 days) IRR = 1.19 (95 % CI 1.03-1.36, P = 0.015) compared to the pre-quake (-7 to -1 days) period. Notably, admissions on days +1 and + 2 (IRR = 1.54 [95 % CI 1.11-2.14] and 1.58 [95 % CI 1.07-2.34]) showed a significant increase compared to controls. Elevated systolic blood pressure was observed post-quake, while demographics, severity, and mortality showed no significant differences.</p><p><strong>Conclusions: </strong>Our findings suggest a significant association between earthquake events and increased STEMI admissions within the days following an earthquake in a high-seismic area. Compared to pre-earthquake and control periods, the observed rise in post-earthquake admissions indicates that seismic stress may contribute to STEMI events.</p>","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":"90 ","pages":"115-119"},"PeriodicalIF":2.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143042882","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":"Diagnostic accuracy of an automated classifier for the detection of pleural effusions in patients undergoing lung ultrasound.","authors":"Rushil Chaudhary, Jordan Ho, Delaney Smith, Saad Hossain, Jaswin Hargun, Blake VanBerlo, Niall Murphy, Ross Prager, Kiran Rikhraj, Jared Tschirhart, Robert Arntfield","doi":"10.1016/j.ajem.2025.01.041","DOIUrl":"https://doi.org/10.1016/j.ajem.2025.01.041","url":null,"abstract":"<p><strong>Rationale: </strong>Lung ultrasound, the most precise diagnostic tool for pleural effusions, is underutilized due to healthcare providers' limited proficiency. To address this, deep learning models can be trained to recognize pleural effusions. However, current models lack the ability to diagnose effusions in diverse clinical contexts, which presents significant challenges.</p><p><strong>Objective: </strong>To develop and validate a deep learning model for detecting pleural effusions in lung ultrasound images, with adaptable performance characteristics tailored to specific clinical scenarios.</p><p><strong>Methods: </strong>A retrospective study was conducted at two Canadian tertiary hospitals to evaluate the detection of pleural effusions of varying sizes and complexities using lung ultrasound. A deep learning model incorporating a frame-level convolutional neural network and a clip-level prediction algorithm was developed and validated against expert annotations.</p><p><strong>Results: </strong>The model was evaluated using a holdout dataset of 103 lung ultrasound clips from 46 patients with pleural effusion and 136 clips from 83 patients without effusion. The general model achieved a sensitivity of 0.90 for small-to-large effusions, with a specificity of 0.89. The large effusion model demonstrated a sensitivity of 0.97 for large effusions while maintaining a specificity of 0.90. The trauma model showed high sensitivity to all effusions, including trace (0.91) and small (0.97) effusions.</p><p><strong>Conclusion: </strong>Our research highlights the development of a deep learning model that effectively detects pleural effusions of varying sizes and complexities on lung ultrasound in different clinical settings. This tool has the potential to enhance emergency physicians' ability to quickly and accurately diagnose effusions, particularly in time-sensitive situations.</p>","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":"90 ","pages":"142-150"},"PeriodicalIF":2.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143061633","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":"Authors reply: ChatGPT's ECG interpretations: Sensitivity or specificity? Which matters more in the emergency department?","authors":"Arian Zaboli, Gianni Turcato","doi":"10.1016/j.ajem.2025.01.026","DOIUrl":"https://doi.org/10.1016/j.ajem.2025.01.026","url":null,"abstract":"","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143042343","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}