Portal Vein Doppler is a sensitive marker for evaluating venous congestion in End Stage Kidney Disease
Bibliographic record
Abstract
INTRODUCTION: Determining ultrafiltration volume in patients undergoing intermittent hemodialysis (IHD) is an essential component in the assessment and management of volume status. Venous excess ultrasound (VExUS) is a novel tool used to quantify the severity of venous congestion at the bedside. Given the high prevalence of pulmonary hypertension in patients with end-stage kidney disease (ESKD), venous Doppler could represent a useful tool to monitor decongestion in these patients. METHODS: This is a prospective observational study conducted in ESKD patients who were admitted to the hospital requiring IHD and ultrafiltration. Inferior vena cava maximum diameter (IVCd), portal vein Doppler (PVD), and hepatic vein Doppler (HVD) were performed in all patients before and after a single IHD session. RESULTS: Forty-one patients were included. The prevalence of venous congestion was 88% based on IVCd and 63% based on portal vein pulsatility fraction (PVPF). Both mean IVCd and PVPF displayed a significant improvement after ultrafiltration. The percent decrease in PVPF was significantly larger than the percent decrease in IVCd. HVD alterations did not significantly improve after ultrafiltration. CONCLUSIONS: Our study revealed a high prevalence of venous congestion in hospitalized ESKD patients undergoing hemodialysis. After a single IHD session, there was a significant improvement in both IVCd and PVPF. HVD showed no significant improvement with one IHD session. PVPF changes were more sensitive than IVCd changes during volume removal. This study suggests that, due to its rapid response to volume removal, PVD, among the various components of the VExUS grading system, could be more effective in monitoring real-time decongestion in patients undergoing IHD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".