Emergency Department Patients Research Articles

Older Adults' Experiences of Emergency Department Admission Decisions: A Qualitative Study in a Public Safety Net Hospital.

Hospital admission is a significant event in the healthcare trajectory of older adults (age 60 +). Numerous harms such as delirium, falls, and adverse medication events can arise that outweigh the benefits of admission. Little is known about how older adults feel about being hospitalized or what they think admission will achieve for them. These issues are particularly important to understand in socioeconomically disadvantaged patients, who have poor access to outpatient care and higher hospitalization rates. We performed semi-structured interviews with emergency department (ED) patients aged 60 and older who were being admitted. The study site was a public hospital serving a socioeconomically disadvantaged, predominantly Hispanic and Black patient population. Interviews focused on experiences of the admission decision, expectations of hospitalization, and health outcome goals. We coded data using an inductive approach. Twenty-seven older adults were interviewed about their experiences. Most participants belonged to minoritized racial or ethnic groups (70%, n = 19), and 41% (n = 11) spoke Spanish as their primary language. Approximately one-third were admitted for ambulatory care-sensitive conditions, i.e., conditions that can be managed in the outpatient setting to prevent hospitalization. Four themes emerged: (1) participants felt that clinicians made admission decisions for, rather than with, them; (2) participants sought to avoid admission due to family caregiving and work obligations; (3) participants with chronic conditions viewed their admission as resulting from poor access to care over the longer term; (4) participants expected hospitalization to improve their chronic symptom burden, mobility, and abilities to perform activities of daily living. Older adults' expectations of hospitalization exceed stabilization of acute illness. Hospital admission of older adults presents an opportunity for shared decision-making and communication about likely outcomes of hospitalization. Incorporating patient-centered outcomes into admission decisions may help align care with older adults' priorities in the ED.

Development of a model predicting falls in older emergency department patients using smartphone-based mobility measures.

While emergency departments (EDs) are crucial for identifying patients at risk for falls, existing fall risk measures are often inaccurate. This study aimed to assess whether iPhone sensor-based mobility measures collected after ED discharge can improve fall prediction compared with traditional ED-based screening measures. This single-center, observational cohort study recruited ED patients aged 60 or older who owned an iPhone. Participants completed baseline assessments, downloaded a custom app to track mobility measures from the iPhone, and were followed for 90 days post-discharge. Fall outcomes were self-reported via the app or follow-up phone calls. Logistic regression and the LASSO technique were employed to identify significant predictors. The discriminative ability of the models was assessed by comparing the C-statistics. Of the 149 participants enrolled, 76.5% (N = 114) provided at least 7 days of post-discharge iPhone sensor-based mobility data. The cohort had a mean age of 73 years, with 16.7% (N = 19) experiencing a fall. Participants who fell showed a significantly greater increase in daily steps over time compared with those who did not (p = 0.002). The extended logistic regression model, by incorporating mean gait asymmetry and change in step count, demonstrated a higher but nonsignificant improvement in discriminative ability (C-statistic = 0.84) compared with the base model (C-statistic = 0.79). This study demonstrates that iPhone mobility measures collected after ED discharge can enhance fall prediction relative to self-reported fall risk screening questions in older adults. The strongest mobility predictors were gait asymmetry and changes in step count. While the findings suggest that post-discharge mobility monitoring could improve fall prevention strategies, further validation in diverse populations is necessary.

Factors Associated With Leaving-Without-Being-Seen in Pediatric Emergency Department Patients

Factors Associated With Leaving-Without-Being-Seen in Pediatric Emergency Department Patients

Integrating structured and unstructured data for predicting emergency severity: an association and predictive study using transformer-based natural language processing models

BackgroundEfficient triage in emergency departments (EDs) is critical for timely and appropriate care. Traditional triage systems primarily rely on structured data, but the increasing availability of unstructured data, such as clinical notes, presents an opportunity to enhance predictive models for assessing emergency severity and to explore associations between patient characteristics and severity outcomes. This study aimed to evaluate the effectiveness of combining structured and unstructured data to predict emergency severity more accurately.MethodsData from the 2021 National Hospital Ambulatory Medical Care Survey (NHAMCS) for adult ED patients were used. Emergency severity was categorized into urgent (scores 1–3) and non-urgent (scores 4–5) based on the Emergency Severity Index. Unstructured data, including chief complaints and reasons for visit, were processed using a Bidirectional Encoder Representations from Transformers (BERT) model. Structured data included patient demographics and clinical information. Four machine learning models—Logistic Regression, Random Forest, Gradient Boosting, and Extreme Gradient Boosting—were applied to three data configurations: structured data only, unstructured data only, and combined data. A mean probability model was also created by averaging the predicted probabilities from the structured and unstructured models.ResultsThe study included 8,716 adult patients, of whom 74.6% were classified as urgent. Association analysis revealed significant predictors of emergency severity, including older age (OR = 2.13 for patients 65 +), higher heart rate (OR = 1.56 for heart rates > 90 bpm), and specific chronic conditions such as chronic kidney disease (OR = 2.28) and coronary artery disease (OR = 2.55). Gradient Boosting with combined data demonstrated the highest performance, achieving an area under the curve (AUC) of 0.789, an accuracy of 0.726, and a precision of 0.892. The mean probability model also showed improvements over structured-only models.ConclusionsCombining structured and unstructured data improved the prediction of emergency severity in ED patients, highlighting the potential for enhanced triage systems. Integrating text data into predictive models can provide more accurate and nuanced severity assessments, improving resource allocation and patient outcomes. Further research should focus on real-time application and validation in diverse clinical settings.

Strategies to reduce 28-day mortality in adult patients with bacteremia in the emergency department

BackgroundBacteremia, a common emergency department presentation, has a high burden of mortality, cost and morbidity. We aimed to identify areas for potential improvement in emergency department bacteremia management.MethodsThis retrospective cohort study included adults with bacteremia in an emergency department in 2019 and 2022. The primary outcome was 28-day mortality. Descriptive analyses evaluated demographics, comorbidities and clinical characteristics. Univariate and multivariate analyses identified mortality predictors.ResultsOverall, 433 patients were included [217 males (50.1%), mean ± SD age: 74.1 ± 15.2 years]. The 28-day mortality rate was 15.2% (n = 66). In univariate analysis, age ≥ 70 years, arrival by ambulance, arrhythmia, congestive heart failure, recent steroid use, hypotension (< 90/60 mmHg), mechanical ventilation, cardiac arrest, intensive care unit (ICU) admission, intravenous antibiotics, pneumonia as bacteremia source, non-urinary tract infections, no infectious disease consultation, no antibiotic adjustment and no control blood cultures were significantly associated with 28-day mortality (p < 0.05). Malignancy showed a statistical trend (0.05 < p < 0.15). The above-stated sixteen variables, identified in univariate analysis, were assessed via multivariate analysis. Primarily, clinical relevance and, secondarily, statistical significance were used for multivariate model creation to prioritize pertinent variables. Five risk factors, significantly associated with mortality (p < 0.05), were included in the model: ICU admission [adjusted OR (95% CI): 6.03 (3.08–11.81)], pneumonia as bacteremia source [4.94 (2.62–9.32)], age ≥ 70 [3.16 (1.39–7.17)], hypotension [2.12 (1.02–4.40)], and no infectious disease consultation [2.02 (1.08–3.78)]). Surprisingly, initial antibiotic administration within 6 h, inappropriate initial antibiotic regimen and type of bacteria (Gram-negative, Gram-positive) were non-significant (p > 0.05).ConclusionsWe identified significant mortality predictors among emergency department patients presenting with bacteremia. Referral to an infectious disease physician is the only modifiable strategy to decrease 28-day mortality with long-term effect and should be prioritized.

Higher patient-to-physician ratios associated with worse outcomes in the emergency department

ObjectiveTo investigate the association between patient-to-physician ratios, a measure of physician workload, and various patient outcomes in the emergency department (ED). MethodsThis retrospective observational study analyzed 406,220 ED visits at a tertiary care center in Taipei, Taiwan, between January 2015 and December 2019. The dynamic patient-to-physician ratio was calculated using minute-by-minute data to reflect real-time physician workload. Multivariable regression models, adjusted for potential confounders, assessed the association between this ratio and 7-day mortality (primary outcome), ED length of stay, waiting time, and medical expenses (secondary outcomes). Generalized additive models were used to explore non-linear relationships. Sensitivity analyses evaluated alternative mortality timeframes, missing data handling, and a simplified patient-to-physician ratio. External validation was performed using data from two additional hospitals. ResultsHigher patient-to-physician ratios were significantly associated with increased odds of 7-day mortality. Compared to ratios of less than 10, the adjusted odds ratios were 1.46 (95% CI 1.16, 1.83) for ratios between 10 and 19, 1.79 (95% CI 1.43, 2.25) for ratios between 20 and 29, and 1.95 (95% CI 1.53, 2.49) for ratios of 30 and above. Similar trends of increased risk were observed for longer ED length of stay, prolonged waiting times, and higher medical expenses. Sensitivity analyses using alternative mortality timeframes, missing data handling methods, and the simplified patient-to-physician ratio yielded consistent results, supporting the main findings. ConclusionsHigher patient-to-physician ratios are associated with worse outcomes for ED patients. Our findings suggest that maintaining ratios below 10 may be ideal for optimizing care quality, while ratios exceeding 20 pose significant risks to patients.

The Risk for Violence Screening Tool: A Psychometric Validation and Reliability Study

BackgroundThere is a lack of high-quality evidence to support the recommendation of an instrument to screen emergency department patients for their risk for violence. ObjectiveTo demonstrate the content and predictive validity and reliability of the novel Risk for Violence Screening Tool to identify patients at risk for violence. Design and SettingThis retrospective risk screening study was conducted at a 100-bed emergency department in an urban, academic, safety net trauma center in Southern California. ParticipantsNine subject matter expert employees and 22,583 non-critical adult emergency patients. MethodsSubject matter experts rated the relevance of 30 risk items and 10 domains comprising the Risk for Violence Screening Tool. Content Validity Index/Average Content Validity and Universal Agreement analyses determined the tool's content validity. Predictive validity, analyzed with logistic regression, used data from a patient incidence of violence registry (an incident occurred or did not occur), compared with the Risk for Violence Screening Tool screening result (positive or negative). Response agreement among three nurses who independently utilized the Risk for Violence Screening Tool to assess the same patients upon their arrival at the emergency department determined inter-rater reliability. ResultsThe overall Content Validity Index was 0.84, and the item-level Content Validity Index and the universal agreement scores were 1.00, indicating perfect agreement on item relevance and a unanimous consensus among experts. Patients who screened positive on the Risk of Violence Screening Tool, indicating a high probability of violence, were 27.55 times more likely to commit an act of violence compared to those who screened negative (95% CI = 24.73 to 30.70). The logistic regression model was statistically significant, (χ2(1) = 1140.29, p < .0001), explaining a range from 4.9% (Cox & Snell R2) to 37.3% (Nagelkerke R2) of the variance and indicating that the Risk for Violence Screening Tool successfully predicted violent incidents. The calculated area under the curve of 0.843 (95% confidence interval, 0.812-0.873, p< 0.001) affirmed the Risk for Violence Screening Tool's discriminatory ability to distinguish between individuals with and without a risk for violent behavior. Cohen's Kappa statistic yielded a value of 0.86 (p < 0.001). ConclusionsThe Risk for Violence Screening Tool is valid and reliable. This standardized tool can be used in emergency departments as part of a robust violence prevention program, creating a safer workplace for both staff and patients. Tweetable abstractThe Risk for Violence Screening Tool (RVST) is a valid and reliable brief screener to identify emergency department patients at risk for violence. @dhs.lacounty @ijn2024

True cost estimation of common imaging procedures for cost-effectiveness analysis - insights from a Singapore hospital emergency department

ObjectivesThere is a lack of clear and consistent cost reporting for cost-effectiveness analysis in radiology. Estimates are often obtained using costing derived from hospital charge records. This study aims to evaluate the accuracy of hospital charge records compared to a Singapore hospital's true diagnostic imaging costs. MethodsA seven-step process involving a bottom-up micro-costing approach was devised and followed to calculate the cost of imaging using actual data from a clinical setting. We retrieved electronic data from a random sample of 96 emergency department patients who had CT brain, CT and X-ray cervical spine, and X-ray lumbar spine performed to calculate the parameters required for cost estimation. We adjusted imaging duration and number of performing personnel to account for variations. ResultsOur approach determined the average cost for the following imaging procedures: CT brain (€154.00), CT and X-ray cervical spine (€177.14 and €68.22), and X-ray lumbar spine (€79.85). We found that the true cost of both conventional radiography procedures was marginally higher than the subsidized patient charge, and all costs were slightly lower than the private patient charge except for X-ray lumbar spine (€73.49 vs.€79.85). We identified larger differences in cost for both CT procedures and smaller differences in cost for conventional radiography procedures, depending on the patient's private or subsidized status. For private status, the differences were: CT brain (Min: €194.20; Max: €264.40), CT cervical spine (Min: €219.54; Max: €399.05), X-ray cervical spine (Min: €5.27; Max: €61.94), and X-ray lumbar spine (Min: €6.36; Max: €108.04), while for subsidized status, the differences were: CT brain (Min: €7.56; Max: €62.64), CT cervical spine (Min: €47.02; Max: €132.49), X-ray cervical spine (Min: €15.88; Max: €103.44), and X-ray lumbar spine (Min: €13.66; Max: €149.44). Considering examination duration and the number of personnel engaged in a procedure, there were significant variations in the minimum, average, and maximum imaging costs. ConclusionThere is a modest gap between hospital charges and actual costs, and we must therefore exercise caution and recognize the limitations of utilizing hospital charge records as absolute metrics for cost-effectiveness analysis. Our detailed approach can potentially enable more accurate imaging cost determination for future studies.

Diagnostic performance of ChatGPT in tibial plateau fracture in knee X-ray.

Tibial plateau fractures are relatively common and require accurate diagnosis. Chat Generative Pre-Trained Transformer (ChatGPT) has emerged as a tool to improve medical diagnosis. This study aims to investigate the accuracy of this tool in diagnosing tibial plateau fractures. A secondary analysis was performed on 111 knee radiographs from emergency department patients, with 29 confirmed fractures by computed tomography (CT) imaging. The X-rays were reviewed by a board-certified emergency physician (EP) and radiologist and then analyzed by ChatGPT-4 and ChatGPT-4o. The diagnostic performances were compared using the area under the receiver operating characteristic curve (AUC). Sensitivity, specificity, and likelihood ratios were also calculated. The results indicated a sensitivity and negative likelihood ratio of 58.6% (95% CI: 38.9 - 76.4%) and 0.4 (95% CI: 0.3-0.7) for the EP, 72.4% (95% CI: 52.7 - 87.2%) and 0.3 (95% CI: 0.2-0.6) for the radiologist, 27.5% (95% CI: 12.7 - 47.2%) and 0.7 (95% CI: 0.6-0.9) for ChatGPT-4, and 55.1% (95% CI: 35.6 - 73.5%) and 0.4 (95% CI: 0.3-0.7) for ChatGPT4o. The specificity and positive likelihood ratio were 85.3% (95% CI: 75.8 - 92.2%) and 4.0 (95% CI: 2.1-7.3) for the EP, 76.8% (95% CI: 66.2 - 85.4%) and 3.1 (95% CI: 1.9-4.9) for the radiologist, 95.1% (95% CI: 87.9 - 98.6%) and 5.6 (95% CI: 1.8-17.3) for ChatGPT-4, and 93.9% (95% CI: 86.3 - 97.9%) and 9.0 (95% CI: 3.6-22.4) for ChatGPT4o. The area under the receiver operating characteristic curve (AUC) was 0.72 (95% CI: 0.6-0.8) for the EP, 0.75 (95% CI: 0.6-0.8) for the radiologist, 0.61 (95% CI: 0.4-0.7) for ChatGPT-4, and 0.74 (95% CI: 0.6-0.8) for ChatGPT4-o. The EP and radiologist significantly outperformed ChatGPT-4 (P value = 0.02 and 0.01, respectively), whereas there was no significant difference between the EP, ChatGPT-4o, and radiologist. ChatGPT-4o matched the physicians' performance and also had the highest specificity. Similar to the physicians, ChatGPT chatbots were not suitable for ruling out the fracture.

Screening for cognitive impairment in the emergency department: agreement between older adult patient- and informant-completed Ascertain Dementia 8 tool.

Introduction Emergency department (ED) screening for cognitive impairment (CI) is crucial for early intervention, yet guidance on dementia screening protocols remains limited. Our objective was to assess the concordance between the Ascertain Dementia 8 (AD8), a brief screening tool for CI, administered to ED patients and their informants. Methods We conducted a prospective observational study of dyads, including patients ≥65 years without a diagnosis of dementia seeking care in the ED and their informants (e.g. family, friend with close contact). Trained research assistants used the 4AT to exclude patients with concern for delirium. The AD8 was then administered to blinded patients (pAD8) and informants (iAD8), with scores ranging from 0-8 and scores of ≥2 indicating CI. We used the Intraclass Correlation Coefficient (ICC) to calculate the level of agreement between AD8 scores. Results Our analytic sample included 538 dyads, of which 63.3% of patients were female with a mean age of 73.5 years. A total of 131 (24.3%) patients without a diagnosis of dementia self-identified as having CI using the pAD8, in comparison to 110 (20.4%) informants using the iAD8. The ICC of 0.519 (95% CI 0.454-0.578) indicated moderate agreement between pAD8 and iAD8 scores. Conclusions When seeking emergency care, one in four older adults without a diagnosis of dementia and approximately 20% of informants indicated that patients were cognitively impaired. Our finding of moderate agreement between the pAD8 and iAD8 has important implications for clinicians providing care to patients with suspected CI and investigators conducting dementia-related studies.

Towards a Better Use of Safety Planning in Emergency Departments: An Exploratory Study of Patients and Clinicians' Perspectives.

Suicidality frequently leads to emergency department (ED) visits, yet few interventions are offered in EDs to mitigate suicide risk. This study uses a descriptive interpretative design to evaluate the key components for a successful use of such an intervention, the Stanley-Brown safety plan, in EDs. Semi-structured interviews were conducted with patients and ED clinicians and were analyzed using a thematic analysis approach. Participants' perspectives revealed 6 key recommendations for a successful use of the safety plan in EDs: (1) personalize the content of the safety plan, (2) offer a variety of formats, (3) avoid periods of high emotional intensity, (4) engage a broad range of professionals in safety planning, (5) use limited time to make meaningful interventions, (6) propose alternative interventions. A change in the ED culture is needed to ensure that the management of suicidal patients in EDs includes brief therapeutic interventions like safety planning, to mitigate suicide risk.

Evaluating Large Language Model-Assisted Emergency Triage: A Comparison of Acuity Assessments by GPT-4 and Medical Experts.

To evaluate the accuracy of the Emergency Severity Index (ESI) assignments by GPT-4, a large language model (LLM), compared to senior emergency department (ED) nurses and physicians. An observational study of 100 consecutive adult ED patients was conducted. ESI scores assigned by GPT-4, triage nurses, and by a senior clinician. Both model and human experts were provided the same patient data. GPT-4 assigned a lower median ESI score (2.0) compared to human evaluators (median 3.0; p < 0.001), suggesting a potential overestimation of patient severity by the LLM. The results showed differences in the triage assessment approaches between GPT-4 and the human evaluators, including variations in how patient age and vital signs were considered in the ESI assignments. While GPT-4 offers a novel methodology for patient triage, its propensity to overestimate patient severity highlights the necessity for further development and calibration of LLM tools in clinical environments. The findings underscore the potential and limitations of LLM in clinical decision-making, advocating for cautious integration of LLMs in healthcare settings. This study adhered to relevant EQUATOR guidelines for reporting observational studies.

Hyperkalemia or Not? A Diagnostic Pitfall in the Emergency Department

Introduction: Hyperkalemia, a potentially life-threatening electrolyte disturbance, is commonly encountered in the Emergency Department (ED). However, the frequency of factitious hyperkalemia, an artificially elevated potassium level in hyperkalemic ED patients, is unknown. This study aims to detect the rate of factitious hyperkalemia among patients with a potassium concentration of ≥5.0 mmol/l in an all-comer ED population. Methods: This retrospective, monocentric chart review analyzed data of 2,440 ED patients who presented with a potassium concentration of ≥5.0 mmol/L in their initial whole blood or plasma sample, who also underwent a repeat potassium measurement on the same day. Two groups were established based on potassium levels in the initial and repeat blood tests: 1) True hyperkalemia, characterized by consistently elevated potassium levels in both the initial and repeat samples; and 2) Factitious hyperkalemia, defined by an elevated initial potassium level while the repeat blood test showed a normal potassium level. A subset of factitious hyperkalemia was spurious hyperkalemia. In spurious hyperkalemia, the initial blood sample showed an elevated potassium level with evidence of hemolysis, but a repeat test revealed a normal potassium level without evidence of hemolysis. Results: Of the 2,440 patients, 1,576 (65%) had true hyperkalemia and 864 (35%) factitious hyperkalemia. Among the 864 patients with factitious hyperkalemia, 597 (69%) displayed hemolysis in their initial blood sample, indicating spurious hyperkalemia due to in-vitro hemolysis. Conclusion: These data show that about one third of all hyperkalemic blood samples drawn in the ED were due to factitious hyperkalemia. The leading cause of factitious hyperkalemia was spurious hyperkalemia due to in-vitro hemolysis.

Outcomes of ED chest pain visits: the prognostic value of negative but measurable high-sensitivity cardiac troponin (hs-cTn) levels.

Chest pain is a common condition in the emergency department (ED). High-sensitivity cardiac troponin (hs-cTn) assays are crucial for diagnosing acute coronary syndrome, but the implications of "negative but measurable" hs-cTn levels are not well understood. This study assesses the outcomes of patients with acute chest pain discharged from the ED based on their hs-cTn levels. This retrospective cohort study analyzed medical records of patients aged 18 and older presenting with chest pain to the Tel Aviv Sourasky Medical Center ED from 2017 to 2022. We compared patients with negative but measurable hs-cTn levels (3-50 ng/L) to those with very low hs-cTn levels (< 3 ng/L). Primary outcomes included 90- days coronary angiogram (CAG), and secondary outcomes were 7- days ED revisits, 14-days hospital admissions, and 30- days mortality. Of 32,162 eligible patients, 23,297 had hs-cTn levels ≤ 50 ng/L. Patients with negative but measurable hs-cTn levels had higher rates of 90-days CAG (1.8% vs. 0.5%, p < 0.001), 7-day ED revisits (5.2% vs. 3.3%, p < 0.001), 14-day hospital admissions (3.1% vs. 0.9%, p < 0.001), and 30-day mortality (0.3% vs. 0.01%, p < 0.001) compared to those with very low hs-cTn levels. Independent predictors for 90 days CAG included age ≥ 57 years, male sex, and hs-cTn ≥ 3.5 ng/L. Negative but measurable hs-cTn levels are linked to worse outcomes than very low hs-cTn levels in discharged ED patients. Closer follow-up and further cardiac evaluation may be warranted for these patients.

Recovery Capital and Subsequent Overdose Risk and Addiction Treatment Engagement Among Emergency Department Patients at High Risk of Opioid Overdose

Background Emergency department (ED) visits are an opportunity to provide prevention services to people at high risk of overdose. Considering patients’ resources to initiate and sustain recovery ("recovery capital”) may be useful for tailoring ED services, although its relevance in this population is unknown. Methods This secondary analysis used data from ED patients at high risk of opioid overdose enrolled in a randomized controlled trial in Rhode Island (2018–2021). We assessed baseline recovery capital using the Brief Assessment of Recovery Capital (BARC-10), dichotomized as a total score <47 versus ≥47. Post-discharge addiction treatment engagement within 30 days and non-fatal opioid overdose and fatal overdose within 18 months were assessed using statewide administrative data. We used modified Poisson regression and Cox proportional hazards models to estimate the association between recovery capital and (1) treatment engagement and (2) overdose risk, respectively, adjusting for potential confounders. Results Among 543 participants, 32.2% had a baseline BARC-10 total score of ≥47, 32.6% engaged in treatment within 30 days, and 25.6% had a non-fatal opioid overdose and 4.2% had a fatal overdose within 18 months. BARC-10 total score was not associated with treatment engagement within 30 days (adjusted relative risk = 0.79, 95% confidence interval [CI] = 0.60–1.05) or non-fatal opioid overdose (adjusted hazard ratio [aHR] = 0.83, 95%CI = 0.57–1.20) or fatal overdose (aHR = 0.45, 95%CI = 0.14–1.40) within 18 months. Conclusion The majority of ED patients at high risk of opioid overdose had a BARC-10 total score of <47, suggesting low recovery capital. BARC-10 total score was not associated with post-discharge treatment engagement or overdose risk.

Hepatic artery peak systolic velocity compared to non-Doppler ultrasound observations for predicting acute cholecystitis: diagnostic performance and impact on a risk categorization approach.

Compare HAv to non-Doppler ultrasound observations for diagnosing acute cholecystitis in a large consecutive cohort of emergency department (ED) patients and establish a method to combine HAv assessment with non-Doppler observations for diagnosing acute cholecystitis. Consecutive ED patients at one institution undergoing gallbladder (GB) ultrasound (US) for acute cholecystitis between 1/1/2020 and 8/31/2022 had assessments of GB diameter, GB wall thickness, GB contents, pericholecystic irregular collection, and hepatic artery peak systolic velocity (HAv). The non-Doppler observations were scored and summed. Non-Doppler risk categorization was based on rate of acute cholecystitis associated with summed scores. The impact of HAv stratification on the rate of acute cholecystitis in the non-Doppler risk categories was evaluated, with regrouping when subgroups had changes in the acute cholecystitis rate; the regrouping established the HAv-adjusted risk model. Receiver-operator curves for acute cholecystitis diagnosis for individual parameters, the non-Doppler risk categorization, and the HAv-adjusted risk model were compared using area-under-curve (AUC) calculations. Of the 885 patients in the study cohort, 117 (13.2%) had acute cholecystitis. The AUC for diagnosing acute cholecystitis using GB distention (83.8%, p < 0.001), GB wall thickness (79.1%, p < 0.001), and GB contents (75.0%, p 0.02) were higher than HAv (66.3%). HAv assessment adjusted risk for 195 patients. The non-Doppler risk categorization and the HAv-adjusted risk model had the same sensitivity (84.6%) and specificity (85.2%) for diagnosing acute cholecystitis, but the HAv-adjusted risk model showed higher AUC (91.3%, p 0.03) due to increased ability to exclude acute cholecystitis. The diagnostic performance of HAv for acute cholecystitis was lower than other assessments. A categorization scheme based on summed points assigned to each non-Doppler observation was improved with HAv assessment. This risk categorization approach using formulaic integration of non-Doppler and Doppler assessments on ED patients allows radiologists to convey one of five levels of disease probability based solely on sonographic features ranging from effectively excluding acute cholecystitis to substantially elevating the chance the patient has the condition.

A novel predictive model for Intensive Care Unit admission in Emergency Department patients with upper gastrointestinal bleeding

Acute upper gastrointestinal bleeding (UGIB) is a critical emergency. Conventional scoring models for patients with UGIB have limitations; thus, more suitable tools for the Emergency Department are necessary. We aimed to develop a new model that can identify significant predictors of Intensive Care Unit (ICU) admission in Emergency Department patients with UGIB and to compare its predictive accuracy with that of existing models. We retrospectively analyzed data from patients with UGIB treated between January 2020 and July 2022 at the Emergency Department of a single tertiary medical center. Using multivariable logistic regression and the area under the receiver operating characteristic curve (AUROC), we developed a new model to predict the probability of ICU admission. Among 433 patients, multiple logistic regression analysis identified sex, systolic blood pressure, diastolic blood pressure, hemoglobin level, platelet count, alanine transaminase level, and prothrombin time as significant predictors of ICU admission. Our model demonstrated superior predictive accuracy with an AUROC of 0.8539 (95% confidence interval [CI]: 0.8078–0.8999), outperforming the Glasgow–Blatchford score and AIMS65 score, which had AUROCs of 0.7598 (95% CI: 0.7067–0.8130) and 0.6930 (95% CI: 0.6324–0.7537), respectively. We implemented this model in a user-friendly calculator for clinical use. We identified key predictors of ICU admission that are crucial for hemodynamic stabilization in patients with UGIB. Our model, combined with this probability calculator, will enhance clinical decision-making and patient care for UGIB in emergency settings.

Written discharge instruction evaluation for mild traumatic brain injury from emergency departments Evaluating written discharge instructions from emergency departments for mild traumatic brain injury

Aim of studyThis study aimed to evaluate the completeness and quality of information in written discharge instructions for patients with mild traumatic brain injury (mTBI) discharged from the emergency department (ED). MethodsCopies of written discharge instructions provided to patients with mTBI from academic EDs in South Korea were collected in May 2023. We assessed the completeness of the content based on the National Institute for Health and Clinical Excellence guidelines, which categorize discharge instructions into four parts: general advice, emergencies, common post-concussion symptoms and signs, and advice for recovery, with one point for each item. The quality of information was evaluated using DISCERN, a validated 16-item questionnaire assessing reliability (eight questions), quality of information (seven questions), and overall quality (one question) on a 5-point Likert scale. Completeness and quality of discharge information were analyzed by ED level and annual ED visits as proxies for hospital resources. ResultsTwenty-two (44%) written discharge instructions were collected from the 55 EDs contacted, with a mean (standard deviation) content completeness score of 10.1 (2.7) out of a maximum of 30. The mean scores for each section were as follows: general advice, 0.1 (0.23) out of 2; emergencies, 6.0 (1.39) out of 10; common post-concussion symptoms and signs, 0.4 (0.9) out of 8; and advice for recovery, 3.2 (1.9) out of 10. Regarding the quality of information, the mean reliability score was 3.5 (0.3), and the mean information quality score was 1.8 (0.7), with both assessed on a scale from 1 ("very poor") to 5 ("excellent"). Significant differences were found in content completeness for emergency features and in the general scores for quality of information between different ED levels (p = 0.04 and p = 0.01, respectively). However, no significant differences were observed by the number of annual ED visits. ConclusionThe completeness and quality of written discharge instructions for mTBI patients in South Korean EDs were low and varied across hospitals, suggesting a potential association to hospital resources.

Patient assessment of the CAPE: A solution to negative pressure isolation in an emergency department

IntroductionThe Collapsible Aerosolized Particle Enclosure (CAPE) is a negative pressure patient isolation device designed to protect patients and clinicians from aerosolized infectious particles. The CAPE is intended to provide a safe environment for care receipt and delivery when isolation capacity is limited. The goal of this study was to evaluate the acceptability of receiving care in the CAPE from the emergency department (ED) patient perspective. MethodsFor this prospective, observational study, adult ED patients receiving care in the CAPE were asked to participate in an anonymous survey upon conclusion of the patient encounter. Survey domains included comfort, ability to see and communicate with care team members, space adequacy, perceptions of safety, and the ease of entering and exiting the device. Participants provided responses using a five-point Likert-type scale. ResultsTen adult patients participated during a 68-day evaluation period in a tertiary care ED. A total of seven completed the survey (70 %); the remaining three did not complete the survey due to illness severity. The median time spent in the device was 190 min. The median degree of comfort inside the CAPE was 5.0. Participants rated their ability to see their surroundings as median 5.0. The median score for ability to communicate with their medical team inside the CAPE was 5.0. Patients reported feeling safe inside the device with a median of 5.0 and most felt there was enough space inside with a median 5.0. The IQR for each of the above metrics was 5.0 and 5.0. Additionally participants also found it easy to mobilize in and out of the CAPE, with a median score of 5.0, IQR 4.0, 5.05. ConclusionsIn this pilot, prospective, observational study with adult ED patients, the majority of patients found the CAPE comfortable and safe, providing adequate space, and easily accessed. Use of the CAPE with ED patients was feasible and acceptable in our setting, supporting its use as a promising method for expanding isolation space during times of limited negative pressure capacity.

Case-control study of clotting differences using ROTEM testing in pregnant patients with early vaginal bleeding

BackgroundVaginal bleeding in early pregnancy is a common presentation in the Emergency Department (ED), often resulting in pregnancy loss. Hypercoagulability exceeding normal physiological changes may be associated with miscarriage, but conventional clotting tests do not reliably detect this effect. Rotational thromboelastometry (ROTEM), which performs a more comprehensive clotting evaluation, may demonstrate coagulopathic abnormalities contributing to vaginal bleeding and miscarriage in early pregnancy that are not present in normal gestation. ObjectiveThis study aimed to evaluate the relationship between coagulation results from ROTEM testing in patients undergoing active evaluation for possible miscarriage compared to samples taken from asymptomatic patients with healthy pregnancies. Study DesignThis was a prospective case control study from a single center. Patients with chief complaint of vaginal bleeding in early pregnancy (less than 20 weeks) were recruited from the ED for ROTEM testing. These results were compared to healthy pregnant women presenting for routine prenatal care at our hospital’s obstetrical clinic. Crude results were analyzed using t-test for ROTEM measures, and differences were then compared using multiple linear regression, controlling for patient age, race, ethnicity, number of prior pregnancies, and estimated gestational age (EGA) in weeks. ROTEM measurements of interest were the clot formation kinetics using EXTEM, INTEM, and NATEM tracings. ResultsOver the study, 46 patients were recruited from the ED and 51 from the obstetric clinic. Both groups had similar mean ages, and racial and ethnic distribution. ED patients had earlier EGA than OB clinic patients, 7.6 weeks vs. 10.7 weeks, but higher patient age and higher number of prior pregnancies. ROTEM results were not significantly different between groups on univariate analysis except for INTEM CFT and INTEM MCF. After controlling for the patient age and estimated gestational age, no ROTEM result differed between groups. ConclusionIn pregnant patients presenting to the ED with vaginal bleeding before 20 weeks, ROTEM differences were not different in comparison to healthy pregnant patients at the same gestation stage. This suggests that ROTEM clotting profiles may not be useful in the evaluation of vaginal bleeding within this population.