Literature DB >> 29574777

Doppler Renal Resistance Index for the Prediction of Response to Passive Leg-Raising Following Cardiac Surgery.

William Beaubien-Souligny1,2, Gabriel Huard3,4, Josée Bouchard3,5, Yoan Lamarche4,6, André Denault1, Martin Albert3,4.   

Abstract

PURPOSE: Doppler-based renal resistance index (RI) can be measured at the bedside of critically ill patients. This study was designed to assess if the RI predicted an increase in cardiac output (CO) following passive leg-raising (PLR) in patients admitted to the intensive care unit after cardiac surgery.
METHODS: During this single center prospective study, Doppler assessment of RI and measurements of CO using the thermodilution method were performed, after surgery, in the intensive care unit before and after PLR. A positive response to PLR was defined as a ≥10% increase in CO.
RESULTS: We included 30 patients. The mean RI was higher before (0.694 ±0.069) than after PLR (0.679 ± 0.069) (P = .02) with a median change of -0.012 (IQR: -0.042;0.000). Following PLR, 9 patients (30%) had a >10% increase in CO. In patients with a positive PLR response, the decrease in the RI during PLR was more pronounced than in patients who did not respond to PLR (PLR ± 0.042 (IQR: -0.051; -0.040) vs PLR ± -0.008 (IQR: -0.032; 0.015) (P = .004). There was a significant negative association between RI change in response to PLR and a 10% increase in CO following PLR (OR: 1.63 (CI:1.07-2.47) (P = .02) per -0.01 change).
CONCLUSION: An increase in CO following PLR was associated with a significant decrease in RI. Variations of RI in response to PLR should be further studied as a tool to predict fluid responsiveness. However, their clinical utility could be limited by the small magnitude of the variations.
© 2018 Wiley Periodicals, Inc.

Entities:  

Keywords:  Doppler ultrasonography; cardiac surgery; fluid responsiveness; passive leg-raising; point-of-care ultrasound; renal artery; resistance index

Mesh:

Year:  2018        PMID: 29574777     DOI: 10.1002/jcu.22591

Source DB:  PubMed          Journal:  J Clin Ultrasound        ISSN: 0091-2751            Impact factor:   0.910


  1 in total

1.  Artificial Intelligence Pulse Coupled Neural Network Algorithm in the Diagnosis and Treatment of Severe Sepsis Complicated with Acute Kidney Injury under Ultrasound Image.

Authors:  Fu Ying; Shuhua Chen; Guojun Pan; Zemin He
Journal:  J Healthc Eng       Date:  2021-07-20       Impact factor: 2.682

  1 in total

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