Renal Doppler ultrasound to predict acute kidney injury in critically ill patients with acute circulatory failure

  • Balaji Rajaraman
  • , Vanlal Darlong
  • , Kapil Dev Soni
  • , Richa Aggarwal
  • , Maya Dehran
  • , K. Devasenathipathy
  • , Anjan Trikha
  • , Dalim Kumar Baidya

Research output: Contribution to journalArticlepeer-review

Abstract

Renal Doppler ultrasonography may have an important role in the detection of acute kidney injury (AKI) in early stages. This study was aimed to determine whether renal Doppler parameters at day 1 can predict the development of AKI at day 5 in acute circulatory failure (ACF). After ethics committee approval and informed written consent from patients or legally acceptable representatives, we recruited n = 80 critically ill adult patients with ACF in this single-center, prospective observational study. Baseline demographic, clinical, and laboratory parameters were noted. Renal resistive index (RRI), power Doppler ultrasound (PDU) score, and their ratio (RRI/PDU) were measured at baseline and three consecutive days. The primary outcome was the development of AKI at day five, and the secondary outcomes were 28-day mortality, length of ICU stay, duration of ventilation, and vasopressor-free days. Out of 80 patients, n = 32 (40%) developed AKI. At baseline, fluid balance (ml/kg) and APACHE II score were higher and pH was lower in AKI group. RRI and RRI/PDU values were significantly higher, and PDU was significantly lower in the AKI group compared to the non-AKI group from day 1 to day 3. Moreover, changes in these parameters (ΔPDU and ΔRRI/PDU at day 2 and day 3) were significantly more in the AKI group. On regression analysis, all three Doppler parameters from day 1 to day 3 demonstrated very good to excellent accuracy in predicting the development of AKI. To conclude, renal Doppler parameters (RRI, PDU, and RRI/PDU) on day 1 through day 3 can predict the development of AKI by day 5 in critically ill adults with acute circulatory failure.

Original languageEnglish (US)
Pages (from-to)757-765
Number of pages9
JournalJournal of Clinical Monitoring and Computing
Volume39
Issue number4
DOIs
StatePublished - Aug 2025

All Science Journal Classification (ASJC) codes

  • Health Informatics
  • Critical Care and Intensive Care Medicine
  • Anesthesiology and Pain Medicine

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