Articles: emergency-medicine.
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Multicenter Study
Six Diagnoses of Separation: Impact of COVID-19 on Pediatric Emergency Department Visits: A Multicenter Study.
Coronavirus disease 2019 (COVID-19) arrived in the New York metropolitan area in early March 2020. Recommendations were made to self-quarantine within households and limit outside visits, including those to clinics and hospitals, to limit the spread of the virus. This resulted in a decrease in pediatric emergency department (ED) visits. However, it is unclear how this affected visits for some common diagnoses such as anxiety, appendicitis, asthma, headaches, seizures, and urinary tract infection (UTI). These diagnoses were chosen a priori, as they were felt to represent visits to the ED, for which the diagnoses would likely not be altered based on COVID exposure or quarantine due to their acute nature. ⋯ We found a marked decrease in ED visits for six common pediatric diagnoses after COVID-19 arrived in our area. We suspect that this decrease was due to recommendations to quarantine and fear of contracting the virus. Further studies on other diagnoses and potential complications due to the delay in seeking care are needed.
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Multicenter Study
Establishing the International Research Priorities for Pediatric Emergency Medicine Point-of-Care Ultrasound: A Modified Delphi Study.
The Pediatric Emergency Medicine (PEM) Point-of-care Ultrasound (POCUS) Network (P2Network) was established in 2014 to provide a platform for international collaboration among experts, including multicenter research. The objective of this study was to use expert consensus to identify and prioritize PEM POCUS topics, to inform future collaborative multicenter research. ⋯ This consensus study has established a research agenda to inform future international multicenter PEM POCUS trials. This study has highlighted the ongoing need for high-quality evidence for PEM POCUS applications to guide clinical practice.
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Multicenter Study Comparative Study
Comparison of 4F-PCC and aPCC time to administration and outcomes for oral anticoagulant-related ICH.
Intracranial hemorrhages (ICHs) are associated with increased morbidity and mortality. Use of oral anticoagulants are a potential risk factor for ICH, and reversal of the anticoagulant with agents such as Four-Factor Prothrombin Complex Concentrate (4F-PCC) or Activated Prothrombin Complex Concentrate (aPCC) is vital to prevent hematoma expansion. The objective of the study was to the compare the time to administration and outcomes of 4F-PCC or aPCC in patients with ICH taking an oral anticoagulant. ⋯ In patients with ICH taking oral anticoagulants, there was no significant difference in the time to administration between 4F-PCC and aPCC. More prospective randomized controlled trials are warranted to determine an ideal reversal time to improve patient outcomes.
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Multicenter Study
Emergency medicine patient wait time multivariable prediction models: a multicentre derivation and validation study.
Patients, families and community members would like emergency department wait time visibility. This would improve patient journeys through emergency medicine. The study objective was to derive, internally and externally validate machine learning models to predict emergency patient wait times that are applicable to a wide variety of emergency departments. ⋯ Electronic emergency demographic and flow information can be used to approximate emergency patient wait times. A general model is less accurate if applied without site-specific factors.
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Multicenter Study
Emergency medicine pharmacist interventions reducing exposure to costs (EMPIRE-C).
Emergency Medicine (EM) pharmacists are considered essential healthcare providers in the Emergency Department (ED). Limited data are available representing the types of interventions performed by ED pharmacists, especially in community-based health systems. ⋯ EM pharmacists practicing in community settings have a substantial impact on patients as evidenced by the large quantity and variety of interventions logged which also results in significant cost avoidance to the healthcare system.