Literature DB >> 33899819

Hemodynamic clinical phenotyping in septic shock.

Anousone Daulasim1, Antoine Vieillard-Baron, Guillaume Geri.   

Abstract

PURPOSE OF REVIEW: Recent studies have failed to show significant benefit from a uniform strategy, suggesting that hemodynamic management must be individually adapted in septic shock depending on different phenotypes. Different approaches that may be used to this end will be discussed. RECENT
FINDINGS: Fluid management is a cornerstone of resuscitation, as the positive fluid balance has been associated with higher mortality and right ventricular failure. Myocardial evaluation is mandatory, as sepsis patients may present with a hyperkinetic state, left ventricular (systolic and diastolic) and/or right ventricular dysfunction, the latter being associated with higher mortality. Statistical approaches with the identification of hemodynamic clusters based on echocardiographic and clinical parameters might be integrated into daily practice to develop precision medicine. Such approaches may also predict the progression of septic shock.
SUMMARY: Different hemodynamic phenotypes can occur at any stage of sepsis and be associated with one another. The clinician must regularly assess dynamic changes in phenotypes in septic shock patients. Statistical approaches based on machine learning need to be validated by prospective studies.
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

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Year:  2021        PMID: 33899819     DOI: 10.1097/MCC.0000000000000834

Source DB:  PubMed          Journal:  Curr Opin Crit Care        ISSN: 1070-5295            Impact factor:   3.687


  3 in total

1.  Factors associated with left ventricular diastolic dysfunction in patients with septic shock.

Authors:  Wei-Dong Ge; Feng-Zhi Li; Bang-Chuan Hu; Li-Hong Wang; Ding-Yuan Ren
Journal:  Eur J Med Res       Date:  2022-07-27       Impact factor: 4.981

2.  Hemodynamic phenotype-based, capillary refill time-targeted resuscitation in early septic shock: The ANDROMEDA-SHOCK-2 Randomized Clinical Trial study protocol.

Authors:  Eduardo Kattan; Jan Bakker; Elisa Estenssoro; Gustavo Adolfo Ospina-Tascón; Alexandre Biasi Cavalcanti; Daniel De Backer; Antoine Vieillard-Baron; Jean-Louis Teboul; Ricardo Castro; Glenn Hernández
Journal:  Rev Bras Ter Intensiva       Date:  2022 Jan-Mar

3.  Fluid Overload Phenotypes in Critical Illness-A Machine Learning Approach.

Authors:  Anna S Messmer; Michel Moser; Patrick Zuercher; Joerg C Schefold; Martin Müller; Carmen A Pfortmueller
Journal:  J Clin Med       Date:  2022-01-11       Impact factor: 4.241

  3 in total

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