Jason J. Bischof

Objectives Hyperkalaemia (HK) is common in the emergency department (ED) and can cause life-threatening arrhythmias. Patiromer is a potassium binder whose role in acute HK management is uncertain; therefore, we investigated the efficacy and safety of patiromer as an adjunct to the standard of care treatment of HK in the ED. Design A prospective, randomised, double-blind, placebo-controlled study. Setting 16 ED sites across the USA. Participants Patients aged ≥18 years treated at a participating ED who were found to have serum potassium ≥5.8 mEq/L. Interventions Participants were randomised 1:1 to standard combination therapy (25 g intravenous dextrose, 5 units intravenous insulin and 10 mg albuterol) with either patiromer or placebo. The initial dose was given within 1 hour of the potassium result, and the second dose 24 hours later. Primary and secondary outcome measures The primary endpoint was net clinical benefit (NCB) at 6 hours, defined as the change in number of potassium-lowering interventions minus change in serum potassium. Adverse events (AEs) were also recorded. Results The study was terminated early and did not reach the prespecified sample size. Overall, 111 patients (53 patiromer and 58 placebo) were analysed. Mean (SD) age was 61.34 (15.21) years, 34% were female, 48% white and 22.5% received chronic haemodialysis. Mean baseline potassium was 6.5 mmol/L. NCB at 6 hours was similar between patiromer and placebo (−0.6 vs −0.4; p=0.44). Potassium levels at 2, 4 and 6 hours were similar between the groups (5.50 vs 5.70, 5.45 vs 5.65, 5.50 vs 5.60; patiromer and placebo (all p>0.05)). The number of interventions per patient was similar (p>0.05) between groups at each time point. The proportion of patients experiencing AEs was not significant between the patiromer and placebo groups (16.98% vs 32.76%; p=0.08). Conclusions No differences in efficacy were reported in this study, which was underpowered to detect statistical efficacy of patiromer over placebo. Trial registration number NCT04443608.

Objective: Providing high-quality, safe, and consistent care for patients with cancer in the emergency department (ED) poses unique challenges. To better understand these challenges, we surveyed oncologists and emergency medicine (EM) physicians across five institutions to identify key areas for improvement in oncologic EM. Methods: In this multi-institutional, cross-sectional qualitative study, a semi-structured survey was administered to EM attending and resident physicians and medical and surgical oncologists across five institutions in 2023. We assessed the open-ended questionnaire responses using thematic analysis; codes were created and collated to generate initial themes. The themes were then reviewed according to specialty for coherence and non-repetition and finalized. Results: Of the 302 surveys accessed, 185 (61.3%) had complete responses. Three main domains of issues emerged: systems-based challenges, direct patient care-related issues, and knowledge gaps. The issues most frequently perceived by oncologist survey respondents were long delays in care (41%), variability in care (25%), and communication issues between the EM physician and oncologist (14%). The issues most frequently perceived by EM physician survey respondents were knowledge gaps in cancer therapeutics (40%) and in general oncologic emergencies (23%); physician comfort level (14%); the timing and/or location of initial discussions about goals of care (13%); and challenges with the follow-up process (12%). Conclusions: Incorporating an interdisciplinary approach to patient care in the ED, improved EM oncologic education, and the development of oncologic specialized EDs may enhance the quality, safety, and consistency of care for patients with cancer in the ED.

Background: An accurate prognostic tool is essential to aid clinical decision-making (e.g., patient triage) and to advance personalized medicine. However, such a prognostic tool is lacking for acute pancreatitis (AP). Increasingly machine learning (ML) techniques are being used to develop high-performing prognostic models in AP. However, methodologic and reporting quality has received little attention. High-quality reporting and study methodology are critical for model validity, reproducibility, and clinical implementation. In collaboration with content experts in ML methodology, we performed a systematic review critically appraising the quality of methodology and reporting of recently published ML AP prognostic models. Methods/findings: Using a validated search strategy, we identified ML AP studies from the databases MEDLINE and EMBASE published between January 2021 and December 2023. We also searched pre-print servers medRxiv, bioRxiv, and arXiv for pre-prints registered between January 2021 and December 2023. Eligibility criteria included all retrospective or prospective studies that developed or validated new or existing ML models in patients with AP that predicted an outcome following an episode of AP. Meta-analysis was considered if there was homogeneity in the study design and in the type of outcome predicted. For risk of bias (ROB) assessment, we used the Prediction Model Risk of Bias Assessment Tool. Quality of reporting was assessed using the Transparent Reporting of a Multivariable Prediction Model of Individual Prognosis or Diagnosis—Artificial Intelligence (TRIPOD+AI) statement that defines standards for 27 items that should be reported in publications using ML prognostic models. The search strategy identified 6,480 publications of which 30 met the eligibility criteria. Studies originated from China (22), the United States (4), and other (4). All 30 studies developed a new ML model and none sought to validate an existing ML model, producing a total of 39 new ML models. AP severity (23/39) or mortality (6/39) were the most common outcomes predicted. The mean area under the curve for all models and endpoints was 0.91 (SD 0.08). The ROB was high for at least one domain in all 39 models, particularly for the analysis domain (37/39 models). Steps were not taken to minimize over-optimistic model performance in 27/39 models. Due to heterogeneity in the study design and in how the outcomes were defined and determined, meta-analysis was not performed. Studies reported on only 15/27 items from TRIPOD+AI standards, with only 7/30 justifying sample size and 13/30 assessing data quality. Other reporting deficiencies included omissions regarding human–AI interaction (28/30), handling low-quality or incomplete data in practice (27/30), sharing analytical codes (25/30), study protocols (25/30), and reporting source data (19/30). Conclusions: There are significant deficiencies in the methodology and reporting of recently published ML based prognostic models in AP patients. These undermine the validity, reproducibility, and implementation of these prognostic models despite their promise of superior predictive accuracy. Registration: Research Registry (reviewregistry1727)

The influence of genetic variants related to opioid use disorder (OUD) was evaluated using multiple logistic regression analysis in self-reported assigned African American/Afro-Caribbean and European biogeographical ancestry groups (BGAGs) and by sex. From a sample size of 1301 adult patients (>18 years of age) seen in emergency departments of three medical centers in Ohio, six variants were found to be associated with OUD. Two of the variants, rs2740574 (CYP3A4) and rs324029 (DRD3), were included in the analysis having met criteria of at least five subjects for each BGAG, variant carrier status, and OUD status combinations. Variant carriers in the African/Afro-Caribbean BGAG had slightly lower predicted probabilities of OUD. Variant carriers in the European BGAG had slightly higher predicted probabilities of OUD. Relative to sex, all the six variants met evaluation criteria (five subjects for all sex, variant, and OUD status combinations). No statistically significant interactions were found between a given variant, BGAGs and sex. Findings suggest variant testing relative to OUD risk can be applied across BGAGs and sex, however, studies in larger populations are needed.

Objective: About one million United States emergency department (ED) visits annually are due to acute decompensated heart failure (ADHF) symptoms. Characterizing the presentation of ED symptoms among ADHF patients may improve clinical care; however, sex and age differences in ED chief complaints have not been thoroughly investigated. In this paper, we describe differences in chief complaints and comorbid conditions for ED patients with ADHF diagnoses, stratified by sex and age.Methods: We conducted a retrospective analysis of adults presenting to North Carolina EDs using the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT), a statewide syndromic surveillance system, between 2010 and 2016, screening for patients with a diagnosis of ADHF. We evaluated frequencies of chief complaint categories for ED visits and comorbid conditions, stratified by sex and age, and computed standardized differences.Results: The most common chief complaints were dyspnea (19.1%), chest pain (13.5%), and other respiratory complaints (13.4%). In the 18–44 years age group, women were more likely than men to report nausea/vomiting (6.7% vs. 4.1%) and headache (4.2% vs. 2.0%). In those 45–64 and ≥65 years, complaints were similar by sex. When stratified by age group alone, the 18–44 and 45–64 years age groups had more complaints of chest pain, whereas balance issues, weakness, and confusion were more common in the ≥65 years age group.Conclusion: Differences in atypical ADHF symptoms were seen in in ED patients based on sex and age. Understanding the variation in ADHF symptoms among ED patients can facilitate the identification of ED patients with ADHF and improve management of ADHF-related symptoms.

Objective: The core content of emergency medicine (EM) residency training includes the management of oncologic emergencies; however, documented knowledge gaps continue to exist in this subtopic. This study represents a targeted needs assessment as indicated by Step 2 of Kern's curriculum design to determine the specific training gaps to be addressed within the oncologic EM curriculum.Methods: A multi‐institutional cross‐sectional survey of oncologists (surgical and medical) and emergency physicians (attendings and residents) was conducted during 2023 at five institutions. The voluntary survey consisted of general and specialty‐specific questions exploring gaps in oncologic emergency–specific training/education topics. Descriptive statistics reported responses as frequencies and percentages.Results: Of the 833 surveys sent across the five sites, 302 (36.3%) were accessed by link; of these, 271 (89.7%) surveys were completed. There were no differences in the responses between early and later respondents and no differences in the characteristics of respondents between sites. A vast majority of the oncologist and EM groups (91.2% and 83.0%, respectively) reported a belief that emergency physicians would benefit from additional oncologic emergency training. Our survey identified 16 important topics for inclusion in an oncologic EM curriculum, including five topics not present on the 2022 Model of Clinical Practice of Emergency Medicine.Conclusions: Based on this needs assessment, an oncologic EM curriculum should include the topics listed under oncologic emergencies in the 2022 Model of the Clinical Practice of Emergency Medicine along with our respondent‐identified topics of radiation therapy adverse effects, stem cell transplant complications, and the management of cancer‐specific postsurgical complications, pain, and common diseases in patients with cancer.