Prospective Study of Ultrasound Markers of Organ Congestion in Critically Ill Patients With Acute Kidney Injury
Bibliographic record
Abstract
IntroductionOrgan congestion may be a mediator of adverse outcomes in critically ill patients with severe acute kidney injury (AKI). The presence of abnormal venous Doppler waveforms could identify patients with clinically significant organ congestion who may benefit from a decongestive strategy.MethodsThis prospective multicenter cohort study enrolled patients with severe AKI defined as KDIGO stage 2 or higher. Patients were not eligible if they received renal replacement therapy (RRT) for more than 72 hours at the time of screening. Participants underwent serial Doppler ultrasound examinations of the portal, hepatic and intra-renal veins during the week following enrolment. We calculated the Venous Excess UltraSound (VExUS) score based on these data. The primary outcome studied was major adverse kidney events at 30 days (MAKE30) defined as death, RRT dependence, or a persistent decrease in kidney function.ResultsA total of 125 patients were included for whom 291 ultrasound assessments were performed. Severely abnormal venous waveforms were documented in 14.4% of portal vein assessments, 6.5% of intra-renal venous assessments, and 14.4% of hepatic vein assessments. The individual ultrasound markers were not associated with MAKE30. The VExUS score (Grade 0-1: Ref, Grade 2 – adjusted hazard ratio (aHR): 4.03, CI: 1.81; 8.99, Grade 3 – aHR: 2.70, CI: 1.10; 6.65, p=0.03), as well as severely abnormal portal, hepatic and intra-renal vein Doppler were each independently associated with mortality.ConclusionsWhile not significantly associated with MAKE30, venous Doppler abnormalities suggestive of venous congestion were associated with higher mortality in critically ill patients with severe AKI.Trial registrationClinicaltrials.gov identifier: NCT04095143 (https://clinicaltrials.gov/ct2/show/NCT04095143), registered on September 19, 2019 (retrospectively registered)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".