Clinical Research Hemodynamic and Clinical Benefits Associated With Chronic Sildenafil Therapy in Advanced Heart Failure: Experience of the Montréal Heart Institute
Bibliographic record
Abstract
Background: Pulmonary hypertension is highly prevalent in advanced heart failure (HF) despite optimal medical and device therapies. The objective of this investigation was to report on a single centre’s experience of open-label chronic sildenafil therapy in patients with advanced HF. Methods: We conducted a retrospective systematic medical record review of all patients evaluated at our institution for heart transplantation who had also been treated with chronic sildenafil therapy. Baseline demographics, comorbidities, and concomitant medications, as well as the results of laboratory investigations and physiological testing, were abstracted from patient medical records. Change in systolic and mean pulmonary artery pressure (PAP), transpulmonary gradient, cardiac output and cardiac index, and selected laboratory parameters was analyzed by means of the Wilcoxon rank sum test. Outcomes of interest included New York Heart Association (NYHA) functional class after 6 months of therapy and adverse effects attributable to sildenafil. Results: The 16 patients undergoing evaluation for cardiac transplantation combined for 4166 patient-days on sildenafil, with a mean dose of 102.5 54.0 mg/d. None discontinued because of side effects. At 6 months, there was an improvement in the cardiac index (P 0.014)
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".