Acute Medicine最新文献

Improving emergency department flow by introducing a simple time out moment (The TRAFFIC LIGHT study). 通过引入一个简单的暂停时刻来改善急诊科的流程（TRAFFIC LIGHT 研究）。

Acute Medicine Pub Date : 2024-01-01 DOI: 10.52964/AMJA.0966

Audrey Jc Overgaauw, Marijn Ligthart, Kaoutar Azilji, Tanca C Minderhoud, Jonne J Sikkens, Tessa H Biesheuvel, Prabath Wb Nanayakkara

{"title":"Improving emergency department flow by introducing a simple time out moment (The TRAFFIC LIGHT study).","authors":"Audrey Jc Overgaauw, Marijn Ligthart, Kaoutar Azilji, Tanca C Minderhoud, Jonne J Sikkens, Tessa H Biesheuvel, Prabath Wb Nanayakkara","doi":"10.52964/AMJA.0966","DOIUrl":"https://doi.org/10.52964/AMJA.0966","url":null,"abstract":"Background and importance: Long waiting times in the emergency department (ED) is an increasing problem in the recent years and is expected to become an even bigger problem in the future Objective: We aimed to test the hypothesis whether increasing awareness of the time lapse with the treating physician, 2 hours after patient arrival, can reduce long patient turnaround time (TAT).Method: In this prospective single-center cohort study we compared and analyzed patient TAT in the ED before and after implementation of a so called 'traffic light' moment 2 hours after patient arrival. At this 'traffic light' moment a team member contacted the treating physician to increased awareness over the time lapse. Difference in percentage of patients who stayed more than 4 hours in the ED before and after intervention was the primary outcome Results: Between October 2nd 2021 and January 2nd,2022 1494 patients were included for primary outcome analysis. A total of 419 patients (n=740, 56.6%) had a TAT of less than 4 hour in the ED before intervention, compared to 497 (n=754, 65.9%) after intervention (p <0.001). Median time spent in de ED before intervention was 3:40 (IQR 2:24 - 5:04) compared to 3:15 (IQR 2:03 - 4:38) after intervention (p<0.001).Conclusion: This simple and low-cost intervention reduces the ED length of stay significantly. Although multiple interventions will be required to ensure less patients spending more than 4-hours in the ED, a 'traffic light' moment can be a simple and an effective tool.","PeriodicalId":39743,"journal":{"name":"Acute Medicine","volume":"23 1","pages":"4-10"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140866825","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}

引用次数: 0

Do tools aimed at avoiding hospital admission operate at different mortality thresholds? A systematic review. 旨在避免入院的工具在不同的死亡率阈值下是否有效？系统回顾。

Acute Medicine Pub Date : 2024-01-01 DOI: 10.52964/AMJA.0990

Ciara Harris, Agnieszka Ignatowicz, Thomas Knight, Brian Willis, Daniel Lasserson

引用次数: 0

Balancing acute medical management of acute kidney injury and hyperkalaemia versus medicines optimisation for long-term Cardio-Renal-Metabolic (CaReMe) diseases: a narrative review. 平衡急性肾损伤和高钾血症的急性药物治疗与长期心肾代谢疾病（CaReMe）的药物优化：叙述性综述。

Acute Medicine Pub Date : 2024-01-01

Benjamin David James, Mark Holland, Darren Green

引用次数: 0

Point of Care Ultrasound Bladder Volume Calculation on the Acute Medical Unit. 急诊科护理点超声膀胱容量计算。

Acute Medicine Pub Date : 2024-01-01 DOI: 10.52964/AMJA.0970

Joseph Nunan, Tom Lister, Harriet Howgill, Mia Marie Merced Parreno, Guy Brown, Andrew Walden

引用次数: 0

Improving Telemetry use in the Acute Assessment Unit. 改善急性评估病房遥测技术的使用。

Acute Medicine Pub Date : 2024-01-01 DOI: 10.52964/AMJA.0969

Patrick Timmons, Lindsay Reid, Kathleen Clare, Daniel Beckett, Tegan Thomson, Lisa Fabisiak

引用次数: 0

The intensive care population profile in Denmark before and during the first wave of the SARS-CoV-2 pandemic; a national register-based study. SARS-CoV-2 第一波大流行之前和期间丹麦重症监护人群概况；一项基于国家登记册的研究。

Acute Medicine Pub Date : 2024-01-01

Søren Bie Bogh, Marianne Fløjstrup, Christian Fynbo Christiansen, Anne Craveiro Brøchner, Erika Christensen, Anders Perner, Thomas Strøm, Mikkel Brabrand

引用次数: 0

An unexpected case of acute intermittent porphyria. 一个意外的急性间歇性卟啉症病例。

Acute Medicine Pub Date : 2024-01-01 DOI: 10.52964/AMJA.0972

Aaron Jesuthasan, Michael Wride, Harriet Esdaile, Adam Daneshmend

引用次数: 0

Point-of-care ultrasound for the diagnosis of an atypical small bowel obstruction in a cannabis user: a case report. 用于诊断大麻使用者非典型小肠梗阻的护理点超声波：病例报告。

Acute Medicine Pub Date : 2024-01-01 DOI: 10.52964/AMJA.0971

Alaa Beshir, Jonas Bruyns, Maximilien Thoma, Florence Dupriez

引用次数: 0

Performance of AI-powered chatbots in diagnosing acute pulmonary thromboembolism from given clinical vignettes. 人工智能聊天机器人根据给定的临床案例诊断急性肺血栓栓塞症的性能。

Acute Medicine Pub Date : 2024-01-01

Banu Arslan, Mehmet Necmeddin Sutasir, Ertugrul Altinbilek

{"title":"Performance of AI-powered chatbots in diagnosing acute pulmonary thromboembolism from given clinical vignettes.","authors":"Banu Arslan, Mehmet Necmeddin Sutasir, Ertugrul Altinbilek","doi":"","DOIUrl":"","url":null,"abstract":"Background: Chatbots hold great potential to serve as support tool in diagnosis and clinical decision process. In this study, we aimed to evaluate the accuracy of chatbots in diagnosing pulmonary embolism (PE). Furthermore, we assessed their performance in determining the PE severity.Method: 65 case reports meeting our inclusion criteria were selected for this study. Two emergency medicine (EM) physicians crafted clinical vignettes and introduced them to the Bard, Bing, and ChatGPT-3.5 with asking the top 10 diagnoses. After obtaining all differential diagnoses lists, vignettes enriched with supplemental data redirected to the chatbots with asking the severity of PE.Results: ChatGPT-3.5, Bing, and Bard listed PE within the top 10 diagnoses list with accuracy rates of 92.3%, 92.3%, and 87.6%, respectively. For the top 3 diagnoses, Bard achieved 75.4% accuracy, while ChatGPT and Bing both had 67.7%. As the top diagnosis, Bard, ChatGPT-3.5, and Bing were accurate in 56.9%, 47.7% and 30.8% cases, respectively. Significant differences between Bard and both Bing (p=0.000) and ChatGPT (p=0.007) were noted in this group. Massive PEs were correctly identified with over 85% success rate. Overclassification rates for Bard, ChatGPT-3.5 and Bing at 38.5%, 23.3% and 20%, respectively. Misclassification rates were highest in submassive group.Conclusion: Although chatbots aren't intended for diagnosis, their high level of diagnostic accuracy and success rate in identifying massive PE underscore the promising potential of chatbots as clinical decision support tool. However, further research with larger patient datasets is required to validate and refine their performance in real-world clinical settings.","PeriodicalId":39743,"journal":{"name":"Acute Medicine","volume":"23 2","pages":"66-74"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141917612","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}

引用次数: 0

Additional value of geriatric parameters to Quick Sepsis Related Organ Failure Assessment score for predicting clinical deterioration in older emergency department patients with a suspected infection: post-hoc analysis of a prospective observational study. 快速败血症相关器官功能衰竭评估评分的老年参数对预测急诊科疑似感染的老年患者临床病情恶化的额外价值：一项前瞻性观察研究的事后分析。

Acute Medicine Pub Date : 2024-01-01 DOI: 10.52964/AMJA.0989

Agneta H Calf, Hjalmar R Bouma, Liann Weil, Emma M de Jong, Marije de Haan, Barbara C van Munster, Jan C Ter Maaten

{"title":"Additional value of geriatric parameters to Quick Sepsis Related Organ Failure Assessment score for predicting clinical deterioration in older emergency department patients with a suspected infection: post-hoc analysis of a prospective observational study.","authors":"Agneta H Calf, Hjalmar R Bouma, Liann Weil, Emma M de Jong, Marije de Haan, Barbara C van Munster, Jan C Ter Maaten","doi":"10.52964/AMJA.0989","DOIUrl":"10.52964/AMJA.0989","url":null,"abstract":"Aim: To investigate the additional value of geriatric parameters such as physical impairment to the quick Sequential Organ Failure Assessment (qSOFA) tool for predicting clinical deterioration in older ED patients with a suspected infection and to validate the final prediction model.Methods: Post-hoc multivariable regression analysis from a prospective observational cohort study of adult patients visiting the ED of a university hospital to develop a prediction model. External validation of the prediction model was performed using the prospective data-biobank Acutelines.Results: In older patients, qSOFA (OR 1.47 (95% CI 1.12-1.95)) and physical impairment (OR 1.84 (95% CI 1.20-2.82)) were independently associated with clinical deterioration within 72 hours. This resulted in a prediction model with an area under the curve of 0.62 (95% CI 0.56-0.68) in the derivation cohort, and of 0.62 (95% CI 0.56-0.68) in the validation cohort. Calibration of the model was poor.Conclusion: In older ED patients with a suspected infection, not only disease severity scores, but also presence of physical impairment is independently associated with clinical deterioration.","PeriodicalId":39743,"journal":{"name":"Acute Medicine","volume":"23 3","pages":"140-151"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142606658","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}

引用次数: 0