Academic Emergency Medicine最新文献

Objectives: This study sought to explore and externally validate the Carpenter instrument's efficacy in predicting postdischarge fall risk among older adults admitted to the emergency department (ED) for reasons other than falls or related injuries.

Methods: A prospective cohort study was conducted on 779 patients aged ≥ 65 years from a tertiary hospital in São Paulo, Brazil, who were monitored for up to 6 months post-ED hospitalization. The Carpenter instrument, which evaluates the four risk factors nonhealing foot sores, self-reported depression, inability to self-clip toenails, and prior falls, was utilized to assess fall risk. Follow-up by telephone occurred at 30, 90, and 180 days to identify falls and mortality. Fine-Gray models estimated the predictive power of Carpenter instrument for future falls, considering death as a competing event and sociodemographic factors, frail status, and clinical measures as confounders.

Results: Among 779 patients, 68 (9%) experienced a fall within 180 days post-ED admission, and 88 (11%) died. The majority were male (54%), with a mean age of 79 years. Upon utilizing the Carpenter score, those with a higher fall risk (≥2 points) displayed more comorbidities, greater frailty, and increased clinical severity at baseline. Regression analyses showed that every additional point on the Carpenter score increased the hazard of falls by 73%. Two primary contributors to its predictive potential were identified: a history of falls in the preceding year and an inability to self-clip toenails. However, the instrument's discriminative accuracy was suboptimal, with an area under the curve of 0.62.

Conclusions: While the Carpenter instrument associated with a higher 6-month postadmission fall risk among older adults post-ED visit, its accuracy for individual patient decision making was limited. Given the significant impact of falls on health outcomes and health care costs, refining risk assessment tools remains essential. Future research should focus on enhancing these assessments and devising targeted proactive strategies.

Background: Timely administration of systemic corticosteroids is a cornerstone of asthma exacerbation treatment, yet little is known regarding potential benefits of prehospital administration by emergency medical services (EMS) clinicians. We examined factors associated with prehospital corticosteroid administration with hospitalization and hospital length of stay (LOS).

Methods: We performed a retrospective study of EMS encounters for patients 2-50 years of age with suspected asthma exacerbation from a national data set. We evaluated factors associated with systemic corticosteroid administration using generalized estimating equations. We performed propensity matching based on service level, age, encounter duration, vital signs, and treatments to evaluate the association of prehospital corticosteroid administration with hospitalization and LOS using weighted logistic regression. We evaluated the association of prehospital corticosteroid administration with admission using Bayesian models.

Results: Of 15,834 encounters, 4731 (29.9%) received prehospital systemic corticosteroids. Administration of corticosteroids was associated with older age; sex; urbanicity; advanced life support provider; vital sign instability; increasing doses of albuterol; and provision of ipratropium bromide, magnesium, epinephrine, and supplementary oxygen. Within the matched sample, prehospital corticosteroids were not associated with hospitalization (odds ratio [OR] 0.86, 95% confidence interval [CI] 0.73-1.01) or LOS (multiplier 0.76, 95% CI 0.56-1.05). Administration of corticosteroids was associated with lower odds of admission and shorter LOS in longer EMS encounters (>34 min), lower admission odds in patients with documented wheezing, and shorter LOS among patients treated with albuterol. In a Bayesian model with noninformative priors, the OR for admission among encounters given corticosteroids was 0.86 (95% credible interval 0.77-0.96).

Conclusions: Prehospital systemic corticosteroid administration was not associated with hospitalization or LOS in the overall cohort of asthma patients treated by EMS, though they had a lower probability of admission within Bayesian models. Improved outcomes were noted among subgroups of longer EMS encounters, documented wheezing, and receipt of albuterol.

Background: To combat increasing levels of violence in the emergency department (ED), hospitals have implemented several safety measures, including behavioral flags. These electronic health record (EHR)-based notifications alert future clinicians of past incidents of potentially threatening patient behavior, but observed racial disparities in their placement may unintentionally introduce bias in patient care. Little is known about how patients perceive these flags and the disparities that have been found in their placement.

Objective: This study aims to investigate patient perceptions and perceived benefits and harms associated with the use of behavioral flags.

Methods: Twenty-five semistructured qualitative interviews were conducted with a convenience sample of patients in the ED of a large, urban, academic medical center who did not have a behavioral flag in their EHR. Interviews lasted 10-20 min and were recorded then transcribed. Thematic analysis of deidentified transcripts took place in NVivo 20 software (QSR International) using a general inductive approach.

Results: Participant perceptions of behavioral flags varied, with both positive and negative opinions being shared. Five key themes, each with subthemes, were identified: (1) benefits of behavioral flags, (2) concerns and potential harms of flags, (3) transparency with patients, (4) equity, and (5) ideas for improvement.

Conclusions: Patient perspectives on the use of behavioral flags in the ED vary. While many saw flags as a helpful tool to mitigate violence, concerns around negative impacts on care, transparency, and equity were also shared. Insights from this stakeholder perspective may allow for health systems to make flags more effective without compromising equity or patient ideals.

Objectives: The aim of this study was to describe the incidence of brief resolved unexplained events (BRUEs) and compare the impact of a national clinical practice guideline (CPG) on admission and diagnostic testing practices between general and pediatric emergency departments (EDs).

Methods: Using the Nationwide Emergency Department Sample for 2012-2019, we conducted a cross-sectional study of children <1 year of age with an International Classification of Diseases diagnostic code for BRUE. Population incidence rate was estimated using Centers for Disease Control and Prevention birth data. ED incidence rate was estimated for all ED encounters. We used interrupted time series to evaluate the associated impact of the CPG publication on the outcomes of ED disposition (discharge, admission, and transfer) and electrocardiogram (ECG) use.

Results: Of 133,972 encounters for BRUE, 80.0% occurred in general EDs. BRUE population incidence was 4.28 per 1000 live births and the annual incidence remained stable (p = 0.19). BRUE ED incidence was 5.06 per 1000 infant ED encounters (p = 0.14). The impact of the BRUE CPG on admission rates was limited to pediatric EDs (level shift -23.3%, p = 0.002). Transfers from general EDs did not change with the CPG (level shift 2.2%, p = 0.17). After the CPG was published, ECGs increased by 13.7% in pediatric EDs (p = 0.005) but did not change in general EDs (level shift -0.2%, p = 0.82).

Conclusions: BRUEs remain a common pediatric problem at a population level and in EDs. Although a disproportionate number of infants present to general EDs, there is differential uptake of the CPG recommendations between pediatric and general EDs. These findings may support quality improvement opportunities aimed at improving care for these infants and decreasing unnecessary hospital admissions or transfers.

Objectives: Natural language processing (NLP) represents one of the adjunct technologies within artificial intelligence and machine learning, creating structure out of unstructured data. This study aims to assess the performance of employing NLP to identify and categorize unstructured data within the emergency medicine (EM) setting.

Methods: We systematically searched publications related to EM research and NLP across databases including MEDLINE, Embase, Scopus, CENTRAL, and ProQuest Dissertations & Theses Global. Independent reviewers screened, reviewed, and evaluated article quality and bias. NLP usage was categorized into syndromic surveillance, radiologic interpretation, and identification of specific diseases/events/syndromes, with respective sensitivity analysis reported. Performance metrics for NLP usage were calculated and the overall area under the summary of receiver operating characteristic curve (SROC) was determined.

Results: A total of 27 studies underwent meta-analysis. Findings indicated an overall mean sensitivity (recall) of 82%-87%, specificity of 95%, with the area under the SROC at 0.96 (95% CI 0.94-0.98). Optimal performance using NLP was observed in radiologic interpretation, demonstrating an overall mean sensitivity of 93% and specificity of 96%.

Conclusions: Our analysis revealed a generally favorable performance accuracy in using NLP within EM research, particularly in the realm of radiologic interpretation. Consequently, we advocate for the adoption of NLP-based research to augment EM health care management.