Acute Medicine最新文献

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.

Objective: To determine whether front-door discharge decision tools operate at different mortality thresholds.

Methods: Three databases  searched, for studies testing, deriving or validating front-door risk prediction tools or discharge decision aids, with  defined discharge 'cut-off', reporting mortality or readmission rates. Studies supporting tools' inclusion in national guidelines were also included.

Results: Twenty-four studies were included, frequently for acute chest pain. Mortality rates among those discharged based on tools 0-1.7%. Eight studies reported readmission rates, 0-8% among those discharged early or deemed low-risk.

Conclusion: Although mortality rates were lower for those deemed low-risk by decision aids than those admitted or control groups, readmission rates tended to be higher among low-risk or discharged patients, than among control group or admitted patients.

Cardio-Renal-Metabolic (CaReMe) diseases, in the form of heart failure, chronic kidney disease and diabetes mellitus, justify prescription of multiple prognostically beneficial medications, specifically renin-angiotensin system inhibitors, mineralocorticoid receptor antagonists, and sodium-glucose co-transporter-2 inhibitors. Use of these medications is complicated by association with adverse effects, particularly acute kidney injury and hyperkalaemia. Balancing risk and benefit is a common dilemma in acute medicine, with increasingly frequent and complex treatment decisions. Physicians should contemplate adjustments to medications within the context of not just acute illness but also long-term benefit. In the setting of hyperkalaemia, potassium-binding medications can be utilised. At hospital discharge optimisation of therapy can be achieved through clear safety netting advice, scheduled biochemical follow-up, and planned clinical review.

Nursing staff, healthcare assistants (HCAs) and other healthcare professionals on the Acute Medical Unit (AMU) at Royal Berkshire Hospital (RBH) were taught a Point of Care Ultrasound (POCUS) skill during a twenty minute session. Practitioners learned how to take bladder volume measurements with the Butterfly iQ, a portable ultrasound device which provides a visually-aided method of volume measurement. A Likert scale was used to measure the confidence that staff had in performing volume measurements with the AMU automated scanners, and with the semi-automated Butterfly iQ. After the teaching session, confidence reported by practitioners in using the semi-automated visual method was significantly higher than confidence reported in using the automated non-visual scanners (t < 0.001). Minimal time and expense was required to teach practitioners how to perform this skill. Training nurses in POCUS for bladder visualisation and bladder volume calculation is easy and practicable.

Background and aims: Despite published guidelines, telemetry use is inappropriate in 25-43% of cases. This impacts patient safety and telemetry effectiveness. QI methodology was used to review telemetry in a hospital acute medical unit with the aim of reducing inappropriate use and addressing alarm fatigue.

Methods: A 'Telemetry Indication Form' was created. Eight weeks of baseline data was collated before introducing the 'Indication Form'. Four plan-do-study-act cycles were conducted. At each cycle, data was analysed using statistical process control charts.

Results: Inappropriate telemetry use significantly reduced from 32% to 4%. Total telemetry use also fell. Unfortunately, interventions to address alarm rates did not result in significant reduction in false alarms.

Conclusions: A 'Telemetry Indication Form' has significant potential to improve patient safety through reducing inappropriate use.

Objective: To describe the change in admission rate and demographic profile of patients admitted to ICUs throughout Denmark before and during first wave of the SARS-CoV-2 pandemic.

Methods: A register-based national observational study of all patients admitted to ICU from December 2019 until April 2020, comparing ICU admission before and after lockdown.

Results: The number of admissions declined, especially in the age groups below 18 and above 70. The sex distribution and the comorbidity-level remained unchanged. The length of hospital stay prior to ICU admission increased. Overall fewer patients were admitted electively.

Conclusion: Fewer patients were admitted to ICU and waited longer for admission during the first wave of the COVID-19 pandemic.

Acute Intermittent Porphyria (AIP) can be a challenging diagnosis to make, due to its rarity in actual practice and presenting symptoms often being attributed to more common conditions. This is particularly the case, since many patients will likely present to acute and general hospitals where the diagnosis may often not be considered. However, it remains pivotal to diagnose the condition as early as possible to prevent significant morbidity and even death. Here we present an unexpected case of AIP, illustrating the diagnostic delay that is commonly seen with the condition and yet emphasise the importance of its detection to commence urgent treatment.

This case report describes an atypical small bowel obstruction in a 71- years old cannabis user and how point-of-care of ultrasound (PoCUS) helped to its management by further orientating the physician toward the bowel obstruction etiology, namely intussusception. Intussusception is the invagination of an intestinal segment into the adjacent segment. The acute clinical presentation of intussusception often has non-specific symptoms, and the diagnosis can be challenging. While the most common etiology is neoplasm, intussusception also occurs in bowel motility disorder such as after cannabis use. Although this case report illustrates intussusception PoCUS findings, these should nevertheless be integrated into the clinical picture and CT-scan should remain the gold standard complementary examination in case of a suspected bowel obstruction.

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.

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.