A two-centre study investigating the association between brain natriuretic peptides & outcomes in continuous flow left ventricular assist device recipients
Bibliographic record
Abstract
Abstract Background Natriuretic peptides are useful prognostic markers in patients with heart failure and this study aims to evaluate the association between N-terminal pro-brain natriuretic peptide and outcomes in patients with a continuous-flow left ventricular assist device. Methods Adult patients with a continuous-flow left ventricular assist device as bridge to transplant or destination therapy and discharged from hospital were included in the study. Multi-variable Cox regression models with natriuretic peptide as a time-dependent covariate modelling multiple measures per patient, and cubic spline analysis were used to evaluate the association between natriuretic peptides and patient outcomes, taking median N-terminal pro-brain natriuretic peptide of 244 pmol/L as the reference value. Heart transplant was considered a competing event for mortality analysis, while death was considered a competing event for transplantation analysis. A multivariable cause-specific Cox regression model evaluated the relationship between natriuretic peptides and heart failure hospitalizations while considering heart failure hospitalizations as recurring events and adjusting for competing risks of death and transplant. Results This retrospective cohort study included 161 adults. During a median follow-up of 4.7 years, 49 patients died, 79 received a heart transplant and 66 were hospitalized for heart failure. In comparison to the median N-terminal pro-brain natriuretic peptide level, patients exceeding 350 pmol/L had a 19% increased mortality (HR 1.19, 95%CI 1.01–1.15) while patients exceeding 330 pmol/L had a 16% higher risk of hospitalization (HR 1.16, 95%CI 1.01–1.12). Conclusion In patients with a continuous-flow left ventricular assist device, serial assessments of natriuretic peptides may help provide personalized patient care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".