JOURNAL ARTICLE

Ten Influential Point-of-Care Ultrasound Papers: 2025 in Review.

  • Published In: Journal of Intensive Care Medicine, 2026, v. 41, n. 5. P. 436 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Millington, Scott J.; Arntfield, Robert T.; Mayo, Paul H.; Vieillard-Baron, Antoine 3 of 3

Abstract

This article summarizes ten influential recent studies on point-of-care ultrasound (POCUS) relevant to acute care clinicians, including emergency physicians and intensivists. Key topics include the prevalence and reversibility of left ventricular diastolic dysfunction in septic shock, the utility of dynamic parameters for fluid responsiveness in acute respiratory distress syndrome (ARDS), and the expanding role of transesophageal echocardiography during cardiac arrest. Additional studies address personalized hemodynamic resuscitation guided by capillary refill time, standardized lung ultrasound aeration scoring, and the diagnostic value of lung ultrasound for ventilator-associated pneumonia. The article also highlights the prognostic significance of the Venous Excess Ultrasound Grading System (VExUS) for kidney outcomes, the benefits of POCUS-guided resuscitation in shock, and the use of ultrasound to predict and manage weaning failure from mechanical ventilation. Collectively, these studies support the integration of focused ultrasound as a targeted, bedside tool to enhance diagnosis, guide therapy, and improve outcomes in critical care settings.

Additional Information

  • Source:Journal of Intensive Care Medicine. 2026/05, Vol. 41, Issue 5, p436
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2026
  • ISSN:0885-0666
  • DOI:10.1177/08850666261434215
  • Accession Number:193364209
  • Copyright Statement:Copyright of Journal of Intensive Care Medicine is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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