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From Hemodynamics To Proteomics: Unraveling the Complexity of Acute Kidney Injury in Sepsis

  • M. Matejovic
  • P. Radermacher
  • V. Thongboonkerd
Conference paper

Abstract

Sepsis is a complex syndrome characterized by an uncontrolled and deregulated systemic inflammatory response to infection. This is mediated by a broad spectrum of endogenous mediators whose actions result in multiple organ dysfunction distant from the original focus of infection. The kidney is a common ‘victim organ’ of various insults in critically ill patients. Sepsis and septic shock are the dominant causes of acute kidney injury (AKI), accounting for nearly 50% of episodes of acute renal failure [1]. The incidence of AKI in sepsis increases proportionally with the severity of sepsis, with AKI developing in 19% of patients with sepsis, 23% of those with severe sepsis, and 51% of patients with septic shock [2]. The mortality of sepsis patients with co-existing acute renal failure reaches 70%, thereby outstripping that of patients with other causes of AKI [3]. Interestingly, even relatively minor increments in serum creatinine levels coincide with markedly increased morbidity and mortality [4], highlighting the potentially important role of kidney dysfunction during the natural history of critical illness. However, the precise understanding of the multifactorial mechanisms of sepsis-induced AKI that would allow the development of new therapeutic strategies to prevent AKI or to hasten its recovery remains a mystery. Here, we review the most recent advances in the understanding of the molecular mechanisms and pathophysiology of sepsis-induced AKI, focusing on renal hemodynamic and microvascular changes and on the importance of a rapidly evolving proteomics approach to evaluating sepsis-induced kidney dysfunction.

Keywords

Septic Shock Acute Renal Failure Acute Kidney Injury Renal Blood Flow Efferent Arteriole 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science + Business Media Inc. 2008

Authors and Affiliations

  • M. Matejovic
    • 1
  • P. Radermacher
    • 2
  • V. Thongboonkerd
    • 3
  1. 1.1st Medical Department, ICUChaires University Medical Schooland Teaching HospitalPlzenCzech Republic
  2. 2.Dept of AnesthesiaUniversity HospitalUlmGermany
  3. 3.Medical Molecular Biology Unit Office for Research and Development Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand

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