Hepatic and portal vein Dopplers in the clinical management of patients with right-sided heart failure: two case reports
Bibliographic record
Abstract
BACKGROUND: Patients with right heart failure pose significant volume management challenges for hemodynamic optimization. We present two cases in which point of care ultrasound (POCUS) of the hepatic and portal veins contributed to the venous hypertension assessment and decongestive strategy for patients with right-sided heart failure. CASE PRESENTATION: Patient A was 91 years old with known pulmonary hypertension and right ventricular systolic dysfunction who presented in septic shock requiring vasopressor support. Hepatic and portal vein Dopplers were consistent with right heart failure and significant venous congestion, therefore, diuresis was initiated which resulted in portal flow normalization, renal recovery, and cessation of vasopressor support. Patient B was 82 years old with severe idiopathic pulmonary fibrosis on home oxygen who presented in decompensated right heart failure. Despite aggressive diuresis, a negative fluid balance was not achieved. The patient continued to deteriorate and prior to their death portal vein, Doppler showed significant flow reversal. CONCLUSION: Hepatic and portal vein Doppler ultrasounds are venous hypertension assessment tools that can be readily used at the bedside by clinicians trained in POCUS that may contribute holistically to the hemodynamic profiling for patients with right heart failure and direct therapeutic interventions.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".