Literature DB >> 30291377

Performance of Doppler-based resistive index and semi-quantitative renal perfusion in predicting persistent AKI: results of a prospective multicenter study.

Michael Darmon1,2,3, Aurelie Bourmaud4, Marie Reynaud5, Stéphane Rouleau6, Ferhat Meziani7,8, Alexandra Boivin7, Mourad Benyamina9, François Vincent10, Alexandre Lautrette11, Christophe Leroy11, Yves Cohen12, Matthieu Legrand13,9, Jérôme Morel5,14, Jeremy Terreaux15,16, David Schnell6,7.   

Abstract

PURPOSE: The Doppler-based resistive index (RI) and semi-quantitative evaluation of renal perfusion using color Doppler (SQP) have shown promising results for predicting persistent acute kidney injury (AKI) in preliminary studies. This study aimed at evaluating the performance of RI and SQP to predict short-term renal prognosis in critically ill patients.
METHODS: Prospective multicenter cohort study including unselected critically ill patients. Renal Doppler was performed at admission to the intensive care unit. The diagnostic performance of RI and SQP to predict persistent AKI at day 3 was evaluated.
RESULTS: Overall, 371 patients were included, of whom 351 could be assessed for short-term renal recovery. Two thirds of the included patients had AKI (n = 233; 66.3%), of whom 136 had persistent AKI (58.4%). Doppler-based RI was higher and SQP lower in AKI patients and according to AKI recovery. Overall performance in predicting persistent AKI was however poor with area under ROC curve of respectively 0.58 (95% CI 0.52-0.64) and 0.59 (95% CI 0.54-0.65) for RI and SQP. Optimal cutoff was respectively 0.71 and 2 for RI and SQP. At optimal cutoff, sensitivity and specificity were 50% (95% CI 41-58%) and 68% (62-74%) for RI and 39% (32-45%) and 75% (66-82%) for SQP.
CONCLUSION: Although statistically associated with AKI occurrence, RI and SQP perform poorly in predicting persistent AKI at day 3. Further studies are needed to adequately describe factors influencing Doppler-based assessment of renal perfusion and to delineate whether these indicators may be useful at the bedside. CLINICALTRIAL.GOV: NCT02355314.

Entities:  

Keywords:  Acute kidney injury; Doppler; Renal replacement therapy; Resistive index; Sensitivity; Specificity

Mesh:

Year:  2018        PMID: 30291377     DOI: 10.1007/s00134-018-5386-3

Source DB:  PubMed          Journal:  Intensive Care Med        ISSN: 0342-4642            Impact factor:   17.440


  37 in total

1.  Understanding the Doppler RI: impact of renal arterial distensibility on the RI in a hydronephrotic ex vivo rabbit kidney model.

Authors:  M E Murphy; M E Tublin
Journal:  J Ultrasound Med       Date:  2000-05       Impact factor: 2.153

2.  Short- and long-term survival after acute kidney injury.

Authors:  Sean M Bagshaw
Journal:  Nephrol Dial Transplant       Date:  2008-07       Impact factor: 5.992

3.  Resistive Index or color-Doppler semi-quantitative evaluation of renal perfusion by inexperienced physicians: results of a pilot study.

Authors:  D Schnell; M Reynaud; M Venot; A L Le Maho; M Dinic; M Baulieu; G Ducos; J Terreaux; F Zeni; E Azoulay; F Meziani; J Duranteau; M Darmon
Journal:  Minerva Anestesiol       Date:  2014-02-25       Impact factor: 3.051

4.  Noninvasive monitoring of renal blood flow characteristics during acute renal failure in man.

Authors:  P E Stevens; S J Gwyther; M E Hanson; J E Boultbee; W J Kox; M E Phillips
Journal:  Intensive Care Med       Date:  1990       Impact factor: 17.440

5.  Acute renal failure: possible role of duplex Doppler US in distinction between acute prerenal failure and acute tubular necrosis.

Authors:  J F Platt; J M Rubin; J H Ellis
Journal:  Radiology       Date:  1991-05       Impact factor: 11.105

6.  Use and misuse of the receiver operating characteristic curve in risk prediction.

Authors:  Nancy R Cook
Journal:  Circulation       Date:  2007-02-20       Impact factor: 29.690

7.  Renal resistive index better predicts the occurrence of acute kidney injury than cystatin C.

Authors:  David Schnell; Stéphane Deruddre; Anatole Harrois; Julien Pottecher; Claudine Cosson; Nadir Adoui; Dan Benhamou; Eric Vicaut; Elie Azoulay; Jacques Duranteau
Journal:  Shock       Date:  2012-12       Impact factor: 3.454

8.  Creatinine kinetics and the definition of acute kidney injury.

Authors:  Sushrut S Waikar; Joseph V Bonventre
Journal:  J Am Soc Nephrol       Date:  2009-02-25       Impact factor: 10.121

9.  Oliguria as predictive biomarker of acute kidney injury in critically ill patients.

Authors:  John R Prowle; Yan-Lun Liu; Elisa Licari; Sean M Bagshaw; Moritoki Egi; Michael Haase; Anja Haase-Fielitz; John A Kellum; Dinna Cruz; Claudio Ronco; Kenji Tsutsui; Shigehiko Uchino; Rinaldo Bellomo
Journal:  Crit Care       Date:  2011-07-19       Impact factor: 9.097

10.  Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury.

Authors:  Ravindra L Mehta; John A Kellum; Sudhir V Shah; Bruce A Molitoris; Claudio Ronco; David G Warnock; Adeera Levin
Journal:  Crit Care       Date:  2007       Impact factor: 9.097

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  14 in total

1.  Focus on critical care nephrology.

Authors:  Michaël Darmon; Michael Joannidis; Miet Schetz
Journal:  Intensive Care Med       Date:  2019-07-11       Impact factor: 17.440

2.  Renal resistive index as a predictor of postoperative complications in liver resection surgery. Observational study.

Authors:  Enrico Giustiniano; Fabio Procopio; Emanuela Morenghi; Yari Gollo; Laura Rocchi; Nadia Ruggieri; Valeria Lascari; Guido Torzilli; Maurizio Cecconi
Journal:  J Clin Monit Comput       Date:  2020-05-20       Impact factor: 2.502

3.  Monitoring of renal perfusion.

Authors:  Michael Darmon; David Schnell; Antoine Schneider
Journal:  Intensive Care Med       Date:  2022-09-02       Impact factor: 41.787

4.  Different applications of the KDIGO criteria for AKI lead to different incidences in critically ill patients: a post hoc analysis from the prospective observational SICS-II study.

Authors:  Renske Wiersema; Sakari Jukarainen; Ruben J Eck; Thomas Kaufmann; Jacqueline Koeze; Frederik Keus; Ville Pettilä; Iwan C C van der Horst; Suvi T Vaara
Journal:  Crit Care       Date:  2020-04-21       Impact factor: 9.097

5.  Renal echography for predicting acute kidney injury in critically ill patients: a prospective observational study.

Authors:  Hai Jun Zhi; Yong Li; Bo Wang; Xiao Ya Cui; Meng Zhang; Zhen Jie Hu
Journal:  Ren Fail       Date:  2020-11       Impact factor: 2.606

6.  Renal resistive index is associated with acute kidney injury in COVID-19 patients treated in the intensive care unit.

Authors:  Mårten Renberg; Olof Jonmarker; Naima Kilhamn; Claire Rimes-Stigare; Max Bell; Daniel Hertzberg
Journal:  Ultrasound J       Date:  2021-02-05

7.  Machine learning for early discrimination between transient and persistent acute kidney injury in critically ill patients with sepsis.

Authors:  Xiao-Qin Luo; Ping Yan; Ning-Ya Zhang; Bei Luo; Mei Wang; Ying-Hao Deng; Ting Wu; Xi Wu; Qian Liu; Hong-Shen Wang; Lin Wang; Yi-Xin Kang; Shao-Bin Duan
Journal:  Sci Rep       Date:  2021-10-12       Impact factor: 4.379

Review 8.  Acute kidney injury in the critically ill: an updated review on pathophysiology and management.

Authors:  Peter Pickkers; Michael Darmon; Eric Hoste; Michael Joannidis; Matthieu Legrand; Marlies Ostermann; John R Prowle; Antoine Schneider; Miet Schetz
Journal:  Intensive Care Med       Date:  2021-07-02       Impact factor: 17.440

9.  Prediction Efficiency of Postoperative Acute Kidney Injury in Acute Stanford Type A Aortic Dissection Patients with Renal Resistive Index and Semiquantitative Color Doppler.

Authors:  Huai Qin; Yaqiong Li; Nan Zhang; Tiezhu Wang; Zhanming Fan
Journal:  Cardiol Res Pract       Date:  2019-12-03       Impact factor: 1.866

10.  Multivariate analysis of CT imaging, laboratory, and demographical features for prediction of acute kidney injury in COVID-19 patients: a Bi-centric analysis.

Authors:  Stefanie J Hectors; Sadjad Riyahi; Hreedi Dev; Karthik Krishnan; Daniel J A Margolis; Martin R Prince
Journal:  Abdom Radiol (NY)       Date:  2020-10-24
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