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Strehlow M, Alvarez A, Blomkalns AL, Caretta-Wyer H, Gharahbaghian L, Imler D, Khan A, Lee M, Lobo V, Newberry JA, Riberia R, Sebok-Syer S, Shen S, Gisondi MA. Precision emergency medicine. Acad Emerg Med 2024. [PMID: 38940478 DOI: 10.1111/acem.14962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 04/13/2024] [Accepted: 05/23/2024] [Indexed: 06/29/2024]
Abstract
BACKGROUND Precision health is a burgeoning scientific discipline that aims to incorporate individual variability in biological, behavioral, and social factors to develop personalized health solutions. To date, emergency medicine has not deeply engaged in the precision health movement. However, rapid advances in health technology, data science, and medical informatics offer new opportunities for emergency medicine to realize the promises of precision health. METHODS In this article, we conceptualize precision emergency medicine as an emerging paradigm and identify key drivers of its implementation into current and future clinical practice. We acknowledge important obstacles to the specialty-wide adoption of precision emergency medicine and offer solutions that conceive a successful path forward. RESULTS Precision emergency medicine is defined as the use of information and technology to deliver acute care effectively, efficiently, and authentically to individual patients and their communities. Key drivers and opportunities include leveraging human data, capitalizing on technology and digital tools, providing deliberate access to care, advancing population health, and reimagining provider education and roles. Overcoming challenges in equity, privacy, and cost is essential for success. We close with a call to action to proactively incorporate precision health into the clinical practice of emergency medicine, the training of future emergency physicians, and the research agenda of the specialty. CONCLUSIONS Precision emergency medicine leverages new technology and data-driven artificial intelligence to advance diagnostic testing, individualize patient care plans and therapeutics, and strategically refine the convergence of the health system and the community.
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Affiliation(s)
- Matthew Strehlow
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Al'ai Alvarez
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Andra L Blomkalns
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Holly Caretta-Wyer
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Laleh Gharahbaghian
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Daniel Imler
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Ayesha Khan
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Moon Lee
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Viveta Lobo
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Jennifer A Newberry
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Ryan Riberia
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Stefanie Sebok-Syer
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Sam Shen
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Michael A Gisondi
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
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Kuhl CK. Abbreviated Breast MRI: State of the Art. Radiology 2024; 310:e221822. [PMID: 38530181 DOI: 10.1148/radiol.221822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Abbreviated MRI is an umbrella term, defined as a focused MRI examination tailored to answer a single specific clinical question. For abbreviated breast MRI, this question is: "Is there evidence of breast cancer?" Abbreviated MRI of the breast makes maximum use of the fact that the kinetics of breast cancers and of benign tissue differ most in the very early postcontrast phase; therefore, abbreviated breast MRI focuses on this period. The different published approaches to abbreviated MRI include the following three subtypes: (a) short protocols, consisting of a precontrast and either a single postcontrast acquisition (first postcontrast subtracted [FAST]) or a time-resolved series of postcontrast acquisitions with lower spatial resolution (ultrafast [UF]), obtained during the early postcontrast phase immediately after contrast agent injection; (b) abridged protocols, consisting of FAST or UF acquisitions plus selected additional pulse sequences; and (c) noncontrast protocols, where diffusion-weighted imaging replaces the contrast information. Abbreviated MRI was proposed to increase tolerability of and access to breast MRI as a screening tool. But its widening application now includes follow-up after breast cancer and even diagnostic assessment. This review defines the three subtypes of abbreviated MRI, highlighting the differences between the protocols and their clinical implications and summarizing the respective evidence on diagnostic accuracy and clinical utility.
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Affiliation(s)
- Christiane K Kuhl
- From the Department of Diagnostic and Interventional Radiology, University Hospital Aachen, RWTH Pauwelsstr 30, 52074 Aachen, Germany
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Chaudhari PP, Pineda JA, Bachur RG, Khemani RG. Trends and variation in repeat neuroimaging for children with traumatic intracranial hemorrhage. J Am Coll Emerg Physicians Open 2021; 2:e12400. [PMID: 33733248 PMCID: PMC7936793 DOI: 10.1002/emp2.12400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 01/22/2021] [Accepted: 02/12/2021] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVES We aimed to determine trends and institutional variation in repeat neuroimaging in children with traumatic intracranial hemorrhage and to identify factors associated with neuroimaging modality (subsequent magnetic resonance imaging [MRI] vs computed tomography [CT]). METHODS We conducted a retrospective cross-sectional study of 35 hospitals in the Pediatric Health Information System database. We included children <18 years of age hospitalized from 2010-2019 with intracranial hemorrhage and who underwent a brain CT. We calculated repeat neuroimaging rates by modality and used regression analyses to examine temporal trends. We used hierarchical logistic regression to identify factors associated with subsequent MRI versus repeat CT, controlling for hospital. RESULTS We identified 12,714 children with intracranial hemorrhage, of which 5072 with repeat neuroimaging were studied. Of the 5072 children with repeat neuroimaging, repeat CT was performed in 67.6% (n = 3429) and subsequent MRI in 32.4% (n = 1643). Overall repeat neuroimaging with either a CT or MRI remained similar from 2010-2019 (P = 0.431); however, repeat CT scans significantly decreased (P = 0.001); whereas, MRIs significantly increased (P < 0.001). Repeat neuroimaging by hospital ranged from 20%-80%. After controlling for institution, subsequent MRI was more likely to be used in younger children and children who did not receive hyperosmotic agents, neurosurgical interventions, or intensive care unit admission (all P-values <0.001). CONCLUSIONS We found that repeat neuroimaging rates for children with intracranial hemorrhage vary substantially by institution. We also found that although MRI was increasingly used to re-image these children, overall repeat neuroimaging rates (CT or MRI) have not decreased over the past decade. Future work to implement optimal utilization of neuroimaging in these children is needed.
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Affiliation(s)
- Pradip P. Chaudhari
- Division of Emergency and Transport MedicineChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
- Keck School of Medicine of the University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Jose A. Pineda
- Keck School of Medicine of the University of Southern CaliforniaLos AngelesCaliforniaUSA
- Department of Anesthesia and Critical Care MedicineChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
| | - Richard G. Bachur
- Division of Emergency MedicineBoston Children's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Robinder G. Khemani
- Keck School of Medicine of the University of Southern CaliforniaLos AngelesCaliforniaUSA
- Department of Anesthesia and Critical Care MedicineChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
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