The Emergency Medicine Pharmacotherapy Literature of 2021.

Am J Emerg Med

Duquesne University School of Pharmacy, University of Pittsburgh Medical Center-Mercy Hospital, Room 311 Bayer Learning Center, 600 Forbes Avenue, Pittsburgh, PA 15282, United States of America.

Published: October 2022

This article highlights the most relevant emergency medicine (EM) pharmacotherapy publications indexed in 2021. A modified Delphi approach was utilized for selected journals to identify the most impactful EM pharmacotherapy studies via the GRADE system. After review of journal table of contents GRADE 1A and 1B articles were reviewed by authors. Twenty articles, 2 guidelines, 2 position papers, and 2 meta-analysis were selected for full summary. Articles included in this review highlight acute agitation management, acute appendicitis treatment, sexually transmitted infection updates, optimizing sepsis management and treatment, updates for the ideal thrombolytic agent in acute ischemic stroke and endovascular therapy candidates, indications for tranexamic acid, calicium for out of hospital cardiac arrest, optimial inotrope for cardiogenic shock, awareness during rapid sequence intubation paralysis, comparison of propofol or dexmedetomidine for sedation, treatment of cannabis hyperemsis syndrome, and prophylactic use of diphenhydramine to reduce neuroleptic side effects. Selected articles are summarized to include design, results, limitations, conclusions and impact.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ajem.2022.07.039DOI Listing

Publication Analysis

Top Keywords

emergency medicine
8
medicine pharmacotherapy
8
pharmacotherapy literature
4
literature 2021
4
2021 article
4
article highlights
4
highlights relevant
4
relevant emergency
4
pharmacotherapy publications
4
publications indexed
4

Similar Publications

We aimed to determine whether emergency department (ED) overcrowding affects the occurrence of in-hospital cardiac arrest (IHCA) requiring resuscitation in the ED. This retrospective study was conducted in the ED of a single hospital. We applied the propensity score-matching method to adjust for differences in clinical characteristics in patients who visited the ED during overcrowded conditions.

View Article and Find Full Text PDF

Objective: To develop a framework that models the impact of electronic health record (EHR) systems on healthcare professionals' well-being and their relationships with patients, using interdisciplinary insights to guide machine learning in identifying value patterns important to healthcare professionals in EHR systems.

Materials And Methods: A theoretical framework of EHR systems' implementation was developed using interdisciplinary literature from healthcare, information systems, and management science focusing on the systems approach, clinical decision-making, and interface terminologies.

Observations: Healthcare professionals balance personal norms of narrative and data-driven communication in knowledge creation for EHRs by integrating detailed patient stories with structured data.

View Article and Find Full Text PDF

Background: Febrile illness in returned travelers presents a diagnostic challenge in non-endemic settings. Chat generative pretrained transformer (ChatGPT) has the potential to assist in medical tasks, yet its diagnostic performance in clinical settings has rarely been evaluated. We conducted a preliminary validation assessment of ChatGPT-4o's performance in the workup of fever in returning travelers.

View Article and Find Full Text PDF

Background/objective: Systemic lupus erythematosus (SLE) is associated with increased dementia risk. Whether this association is present among older adults with SLE is unclear. Further, whether individuals with concomitant SLE and dementia are at increased risk of emergency department (ED) use has not been explored.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!