| Autor: |
Heinz ER; Department of Anesthesiology and Critical Care Medicine, George Washington University; eheinz@mfa.gwu.edu., Bernardo R; The George Washington University School of Medicine and Health Sciences Washington., Birk SE; Vanderbilt University Medical Center., Manson W; Department of Anesthesiology, UVA Health., MacLeod DB; Department of Anesthesiology, Duke University School of Medicine, Duke University Health System., Molinger J; Department of Anesthesiology, Duke University School of Medicine, Duke University Health System., Vincent A; Department of Anesthesiology and Critical Care Medicine, George Washington University., Bronshteyn YS; Department of Anesthesiology, Duke University School of Medicine, Duke University Health System. |
| Jazyk: |
angličtina |
| Zdroj: |
Journal of visualized experiments : JoVE [J Vis Exp] 2024 Jul 26 (209). Date of Electronic Publication: 2024 Jul 26. |
| DOI: |
10.3791/66803 |
| Abstrakt: |
Frailty is a significant predictor of a range of adverse outcomes in surgical patients, including increased mechanical ventilation time, longer hospital stays, unplanned readmissions, stroke, delirium, and death. However, accessible tools for screening in clinical settings are limited. Computed tomography of the psoas muscle is the current standard imaging device for measuring frailty, but it is expensive, time-consuming, and exposes the patient to ionizing radiation. Recently, the use of point-of-care ultrasound (POCUS) has emerged as a potential tool to determine the presence of frailty and has been shown to accurately predict frailty and postoperative outcomes. In this article, we will describe the image acquisition of the quadriceps muscles and explain how they can be used to determine frailty and predict postoperative adverse events. We will present information on probe selection, patient positioning, and troubleshooting. Images from a demonstration will be used to present the POCUS technique and example results. The article will culminate in a discussion of the use of these images in medical decision-making and potential limitations. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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