Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias最新文献

{"title":"Analysis of comorbidity in an emergency department using diagnostic coding: The Elixhauser Index.","authors":"Adrià Calvet-Pujol, Josep Ris-Romeu, Marta Albacar-Ingla, Ferran Vicente-Díez, Pilar Navarro-Arranz, Mireia Puig-Campmany","doi":"10.55633/s3me/018.2026","DOIUrl":"10.55633/s3me/018.2026","url":null,"abstract":"<p><strong>Objective: </strong>To analyze the comorbidity of patients attending an emergency department (ED) using the Elixhauser Index (EI) and examine its association with the length of stay and discharge destination.</p><p><strong>Methods: </strong>We conducted aetrospective observational study based on the Emergency Department Minimum Basic Dataset for 2019, 2022, and 2023, excluding pandemic years. Diagnoses were coded using International Classification of Diseases-version-10 Clinical Modification (ICD-10-CM), and the EI was applied to assess comorbidity. Associations between comorbidity, length of stay (< 16 hours vs $ 16 hours), and discharge destination were analyzed.</p><p><strong>Results: </strong>More than 12% of patients had at least 1 comorbidity (EI $ 1). Among episodes < 16 hours, 92% showed no comorbidity, whereas among episodes $ 16 hours, nearly 50% had EI $ 1 (P < .001). Among patients admitted to the tertiary referral center, fewer than 7% had moderate or severe comorbidity (EI $ 2). Patients with greater comorbidity were referred to lower-complexity facilities or to hospital-at-home programs.</p><p><strong>Conclusions: </strong>The EI allows characterization of the heterogeneity of the ED population. The organizational model of Hospital de la Santa Creu i Sant Pau, oriented toward geriatric and network-based care, facilitates referral of complex patients to more appropriate resources, reducing admissions to high-technology hospitals. Incorporating comorbidity analysis may improve ED planning and funding.</p>","PeriodicalId":93987,"journal":{"name":"Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias","volume":"38 3","pages":"173-178"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148321137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic performance of structured telephone triage for detecting priority 1 in suspected prehospital stroke: a population-based analysis in Andalusia (Spain).","authors":"María José Luque-Hernández, Carlos Romero-Olóriz, Miguel Ángel Armengol de la Hoz, Cristina López-López, Álvaro Ritoré-Hidalgo, Ángel Serrano-Alarcón","doi":"10.55633/s3me/063.2026","DOIUrl":"10.55633/s3me/063.2026","url":null,"abstract":"","PeriodicalId":93987,"journal":{"name":"Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias","volume":"38 3","pages":"239-240"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148321212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of emergency services oriented toward the geriatric population: an urgent necessity.","authors":"Sira Aguiló","doi":"10.55633/s3me/032.2026","DOIUrl":"https://doi.org/10.55633/s3me/032.2026","url":null,"abstract":"","PeriodicalId":93987,"journal":{"name":"Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias","volume":"38 3","pages":"161-162"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148321184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Outcomes in older adults with acute heart failure according to sex.","authors":"Judith Fuentes, Irene Cabello, Alex Roset, Nieves López-Delmas, Pierre Malchair, Javier Jacob","doi":"10.55633/s3me/057.2026","DOIUrl":"https://doi.org/10.55633/s3me/057.2026","url":null,"abstract":"","PeriodicalId":93987,"journal":{"name":"Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias","volume":"38 3","pages":"234-235"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148321271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated detection of sepsis in emergency departments and its clinical impact: a pre-post study.","authors":"Ana María Ros Gálvez, Santiago Diéguez Zaragoza, José Luis Muñoz Bravo, Antoni Thomas Barrilado Jackson, Emilio Flores Pardo, Elena Díaz Fernández","doi":"10.55633/s3me/064.2026","DOIUrl":"https://doi.org/10.55633/s3me/064.2026","url":null,"abstract":"","PeriodicalId":93987,"journal":{"name":"Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias","volume":"38 3","pages":"240"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148321084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Authors' reply.","authors":"Javier Millán Soria, Javier Medina Álvarez, Laura Sánchez Suárez, César Cano Cerviño, Leticia Serrano Lázaro, M ª Carmen García-Minguillán Castillo, Vanesa Ginestar Miravet","doi":"10.55633/s3me/050.2026","DOIUrl":"https://doi.org/10.55633/s3me/050.2026","url":null,"abstract":"","PeriodicalId":93987,"journal":{"name":"Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias","volume":"38 3","pages":"231-232"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148321089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The 2017 Barcelona terrorist attack: Real-time appropriateness and lessons learned from the management of an intentional vehicle-ramming mass-casualty incident.","authors":"Eva M ª Valiño, Youcef Azeli, Joaquin Ríos, Silvia Solà-Muñoz, Manel Riudor, Xavier Castillo, Jorge Morales-Álvarez","doi":"10.55633/s3me/022.2026","DOIUrl":"10.55633/s3me/022.2026","url":null,"abstract":"<p><strong>Objective: </strong>To describe the appropriateness of triage according to safety conditions, incident characteristics, and observed injury patterns in an intentional vehicle-ramming (VR) mass-casualty incident (MCI).</p><p><strong>Methods: </strong>We conducted a retrospective observational study of the intentional VR-MCI that occurred on August 17th, 2017, in Barcelona (Spain). Data were collected from emergency medical services and hospital records regarding decision-making processes, triage strategies, and hospital diagnoses.</p><p><strong>Results: </strong>A total of 153 victims were attended, including 14 fatalities (9%) and 139 injured patients (91%), across a large affected area of 13,608 m2. Initially, due to compromised safety conditions and the high number of casualties, a triage strategy based on expert visual assessment using surgical priority criteria (VIVE-Q) with immediate transport was implemented. Once safety in the healthcare area was established, the advanced prehospital triage model (META) was applied. Both triage strategies allowed appropriate prioritization and correct destination assignment in 98.1% of patients, with no associated in-hospital mortality. Assistance time was shorter in patients triaged with VIVE-Q vs META [19 (IQR 21) vs 28 (IQR 47) minutes; P = .001]. Regarding injury patterns, 25% of the injured patients were categorized as severe (red), with 87% presenting $ 2 injuries, predominantly involving the head and thoracoabdominal regions.</p><p><strong>Conclusions: </strong>Security compromise during an intentional VR-MCI required adaptation of emergency response and triage plans, which proved to be effective.</p>","PeriodicalId":93987,"journal":{"name":"Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias","volume":"38 2","pages":"131-139"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147517831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative analysis between high- and low-resource hospitals to identify factors associated with sepsis-related mortality.","authors":"Erin Simon, Augusto Maldonado, Abdoulie Gaye, Caroline Mangira, Jessica Krizo","doi":"10.55633/s3me/023.2026","DOIUrl":"10.55633/s3me/023.2026","url":null,"abstract":"<p><strong>Objective: </strong>To compare sepsis-related mortality between a limited-resource setting in South America and a high-resource setting in North America, and examine differences in early sepsis management processes.</p><p><strong>Methods: </strong>This retrospective review included adult patients presenting to 2 tertiary emergency departments (EDs) from June 1st, 2021 through May 31st, 2022, with a diagnosis of sepsis or septic shock. Sepsis mortality and ED time metrics relevant to early sepsis identification and management were evaluated as associations with the type of hospital rather than causal relationships. A 2:1 propensity score matching approach was used for the analysis. Logistic regression was performed to assess the effect of the hospital system on mortality after adjustment for significant confounders.</p><p><strong>Results: </strong>A total of 297 patients were diagnosed with sepsis, of whom 68 (23%) exhibited septic shock. Overall, 198 patients (67%) were treated in the high-resource ED and 99 (33%) in the limited-resource ED. In-hospital mortality was substantially lower in the high-resource setting (6.1% vs 42.4%; P < .001). After adjustment for lactate levels, the odds of death were 13.61 and 7.69 times higher for patients with sepsis and septic shock, respectively, treated in the limited-resource setting (P < .001). Time to antibiotic administration (119 vs 200 minutes; P < .001) and time to IV fluid administration (23 vs 54 minutes, P < .001) were both significantly shorter in the high-resource setting. The median length of the ICU stay was 2.53 days in the high-resource setting vs 6 days in the limited-resource setting (P = .007).</p><p><strong>Conclusions: </strong>The high-resource ED demonstrated lower mortality, a shorter length of the ICU stay, and shorter times to antibiotic and IV fluid administration vs the limited-resource ED. However, causal inferences cannot be drawn due to baseline differences in illness severity and the retrospective study design.</p>","PeriodicalId":93987,"journal":{"name":"Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias","volume":"38 2","pages":"107-113"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147517865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-time prediction of emergency department admissions using an AI model and its integration into hospital bed-planning.","authors":"Javier Millán Soria, Javier Medina Álvarez, Laura Sánchez Suárez, Cesar Cano Cerviño, Leticia Serrano Lázaro, M ª Carmen García-Minguillán Castillo, Vanesa Ginestar Miravet","doi":"10.55633/s3me/009.2026","DOIUrl":"10.55633/s3me/009.2026","url":null,"abstract":"<p><strong>Objective: </strong>To design, validate, and implement a tool based on a machine-learning model capable of predicting emergency patient admissions in real time, and to develop an application that integrates the model together with traditional indicators of health care pressure.</p><p><strong>Methods: </strong>We analyzed anonymized data from a total of 328,696 emergency episodes. Fifteen variables with the highest predictive capacity were identified through Pearson correlation analysis. The RandomForest model was selected. Python was used for model construction, and \"Jupyter Notebook\" for design and validation. A total of 209,530 episodes (64%) were used for training, 52,383 (16%) for validation, and 66,783 (20%) for testing. The model was integrated into a Control Panel using Microsoft Power BI.</p><p><strong>Results: </strong>The model showed a high predictive ability to identify patients who would require admission, with a receiver operating characteristic (ROC) area under the curve (AUC) of 0.97. For each metric, a decrease in training score and a concurrent increase in validation score were observed, ruling out overfitting behaviors. The saturation point in the learning curves was reached at 130,000 episodes. Model calibration yielded a Brier score of 0.0414.</p><p><strong>Conclusions: </strong>The model demonstrates excellent performance and significant potential for predicting hospital admissions among emergency department patients. Combining machine-learning algorithms with interactive visualization systems represents a major step toward more efficient management and planning, helping avoid bottlenecks and overcrowding.</p>","PeriodicalId":93987,"journal":{"name":"Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias","volume":"38 2","pages":"98-106"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147517819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic algorithm for urgent causes of dyspnea based on lung auscultation and ultrasound: The CLINIC-LUS Prospective Study.","authors":"Davide Bernaudo, María de Los Ángeles Guerrero-León, Milagros Rodríguez-Cortés, David Tártalo-Hernández, Rosario de Mora-Alfaro, Lamberto Landete Martín, Francesco Ronchetti, Miriam Motilla-Fraile, Neus Robert-Boter, María Jesús Domínguez-Tordable, Anna Carreres-Molas, Antonia Segura-Egea, Sebastián Videla, Ramón Nogué-Bou","doi":"10.55633/s3me/020.2026","DOIUrl":"10.55633/s3me/020.2026","url":null,"abstract":"<p><strong>Objective: </strong>Dyspnea is a frequent reason for consultation in emergency departments (EDs). Ultrasound artifacts generated within lung tissue can be interpreted for diagnostic purposes. The primary endpoint of this study was to provide evidence on the feasibility and applicability of the CLINIC-LUS algorithm, based on lung auscultation and lung ultrasound, for diagnosing causes of acute dyspnea in adult patients presenting to hospital.</p><p><strong>Methods: </strong>We conducted a prospective, multicenter feasibility study in patients evaluated for acute dyspnea in EDs. Lung auscultation and lung ultrasound patterns were assessed using a 12-point ultrasound protocol. Feasibility was evaluated by the time (in minutes) required to perform lung ultrasound and by the investigator's perception. Diagnostic accuracy (percentage of correct diagnoses) and the Cohen kappa coefficient for agreement of the algorithm were calculated.</p><p><strong>Results: </strong>A total of 95 patients with acute dyspnea presenting to EDs from January 2024 through June 2025 were included and eventually analyzed. The time required to perform lung ultrasound [median (range)] was 12 (9 16) minutes. Investigators unanimously reported that use of the CLINIC-LUS algorithm was straightforward and did not pose difficulties in clinical practice. Diagnostic accuracy was 78.1% (95% CI, 67.5-86.4). The kappa coefficient was 0.73 (95% CI, 0.52-0.82).</p><p><strong>Conclusions: </strong>Integrating physical examination with lung ultrasound into a single algorithm for diagnosing causes of acute dyspnea in the ED is feasible in clinical practice.</p>","PeriodicalId":93987,"journal":{"name":"Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias","volume":"38 2","pages":"123-130"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147517776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}