Decompensated high‐output congestive heart failure in a patient with <scp>AVF</scp> and the role of right heart catheterization: A case study
Bibliographic record
Abstract
A 70-year-old Caucasian male presented 8 months postcadaveric renal transplant with slowly progressive shortness of breath, abdominal distention, and cough for a duration of a few days. Thorough evaluation found him to have severe pulmonary hypertension (PH) on echocardiogram with decompensated high-output congestive heart failure. A right heart catheterization was done, which confirmed elevated right-sided pressures and high cardiac output. The mean pulmonary artery pressure, on a Swan-Ganz catheter, improved from 37 to 30 mmHg on partial manual occlusion of his still functioning hemodialysis arteriovenous fistula. Subsequently, the patient underwent ligation of the fistula and this led to gradual improvement in his symptoms. Follow-up right heart catheterization and echocardiogram showed marked improvement and normalization of right heart pressures. We recommend that patients with arteriovenous fistula should undergo close monitoring for development of early signs and symptoms of congestive heart failure and screening for PH by echocardiography post-kidney transplant. Right heart catheterization should be considered if screening is positive. Risk and benefit of fistula closure should be weighed in face of reduced survival from PH in dialysis patients and closure should be considered in post-transplant 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| 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".