Evaluation of Venous Congestion Using Beside Ultrasonography by the Nephrology Consultant: The VExUS Nexus
Bibliographic record
Abstract
In patients with heart failure and cardiorenal syndrome, lingering congestion is associated with worse outcomes. As such, titrating diuretic or ultrafiltration therapy based on objective assessment of volume status plays a crucial role in the management of these patients. Conventional physical examination findings and parameters such as daily weight measurement are not always reliable in this setting. Recently, point of care ultrasonography (POCUS) has emerged as an attractive enhancement to bedside clinical examination in assessing fluid volume status. Specifically, Doppler ultrasound of the major abdominal veins gives additional information about end-organ congestion when used in conjunction with inferior vena cava ultrasound. Moreover, these Doppler waveforms can be monitored in real time to gauge the efficacy of decongestive therapy. Herein, we present a case that illustrates the utility of POCUS in the management of a patient with heart failure exacerbation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".