VExUS to Guide Ultrafiltration in Hemodialysis: Exploring a Novel Dimension of Point of Care Ultrasound
Bibliographic record
Abstract
Venous Excess Ultrasound (VExUS) is a valuable bedside tool for nephrologists within a multi-organ point of care ultrasound (POCUS) framework. VExUS can address limitations of conventional physical examination in identifying hemodynamic congestion and monitoring treatment efficacy. A 53-year-old man with heart failure and end-stage kidney disease on hemodialysis presented with elevated liver function tests. Despite an unremarkable right upper quadrant ultrasound done by radiology, the review of images by the nephrology team uncovered severe venous congestion, evidenced by a dilated inferior vena cava (IVC) and abnormal hepatic and portal vein flow. Follow-up assessments included VExUS scans and daily ultrafiltration that resulted in a notable 8-liter fluid removal. The dynamic changes in IVC shape and improvement in Doppler waveforms underscored successful decongestion. This case demonstrates the clinical utility of VExUS in guiding therapy for fluid overload in complex patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 source (direct Gemma or distilled Codex), 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".