Tricuspid valve replacement after cardiac transplantation
Bibliographic record
Abstract
BACKGROUND: Tricuspid regurgitation (TR) occurs commonly in transplanted hearts. Although theoretically attractive, tricuspid valve replacement (TVR) has not been widely investigated as a possible therapy in post-transplant patients. The purpose of this study was to determine the safety of TVR in heart transplant patients and its effects on measurable clinical endpoints. METHODS: We acquired data by both retrospective chart review and prospective data collection in all patients who underwent TVR after cardiac transplantation. RESULTS: Nine patients were identified and followed for a period of six months. The age of patients at time of TVR was 62 +/- 6.1 yr and their average time since transplantation was 12 +/- 3.2 yr. Most patients demonstrated a reduction in their furosemide dose (105 +/- 63 mg/d pre-TVR vs. 67.5 +/- 65 mg/d post-TVR, p = 0.001) with a reduction in serum creatinine levels (188 +/- 72 micromol/L pre-TVR vs. 143 +/- 42 micromol/L post-TVR, p = 0.06). Additionally, we found a significant improvement in albumin values (32 +/- 5 g/L pre-TVR vs. 42 +/- 3 g/L post-TVR, p = 0.002) as well as an improvement in total bilirubin (35 +/- 18 micromol/L pre-TVR vs. 18 +/- 5 micromol/L post-TVR, p = 0.05). There was only one death in our series, in the only patient with known severe graft atherosclerosis. CONCLUSIONS: TVR appears to be a safe procedure in patients without severe graft atherosclerosis with improvements in serum creatinine, albumin and total bilirubin values, in addition to a reduction in furosemide dose. This may reflect improved forward flow, improved symptomatology from TR as well as possible beneficial effects on nutritional status.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".