ClinicalTrials.gov
public full text
Public Domain
Renal Doppler to Predict Acute Kidney Injury (AKI) in ARDS Patients. (RED-AKI Study)
This is a multicenter international observational prospective cohort study. The main questions it aims to answer are: * PRIMARY AIM: To describe the capability of IRVF demodulation at diagnosis of ARDS to predict development of AKI within 7 days from the ARDS onset * SECONDARY AIMS: A)Describe the capability of IRVF demodulation or pattern of IRVF (continuous, pulsatility, biphasic, monophasic) to predict development of AKI within 14 days from the ARDS onset. B) To describe the RD parameters and VexUS in the AKI and no AKI patients over time. C) Describe the impact of invasive mechanical ventilation (IMV) on the intrarenal venous congestion and VexUS., D) Evaluation of effect of CRRT on IRVF pattern, VexUS and parameters. E) Describe the feasibility of renal doppler to assess IRVF in critically ill respiratory patients. F) Evaluate the incidence of AKD and CKD Participants will Adult patients with diagnosis of ARDS admitted to intensive care unit and undergoing invasive mechanical ventilation
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Incidence and Spectrum of Acute Kidney Injury in Cirrhotics and Assessment of New Biomarkers as Early Predictors of Acute Kidney Injury#1323496
- Protocol to Assess the Severity of Acute Kidney Injury#1058138
- The Optimal Mode of Renal Replacement Therapy in Acute Kidney Injury (OMAKI) Study#883665
- Acute Kidney Injury in Polytrauma Patients in Intensive Care Unit#966555
- Establishment of a Perioperative Dynamic Prediction Model for Cardiac Surgery-associated Acute Kidney Injury#1093147
Record · ID 1197378
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive