Longitudinal Changes in Multiple Cardiac Biomarkers in Transthyretin Amyloidosis Cardiomyopathy Patients Treated Vs Untreated with Tafamidis
Bibliographic record
Abstract
Background Tafamidis is an oral transthyretin stabilizer that improves survival in transthyretin amyloidosis cardiomyopathy (ATTR-CM), however there is limited real-world data describing serial cardiac biomarker changes following treatment initiation. The primary objective of this study was to characterize longitudinal changes across multiple cardiac biomarker domains in tafamidis-treated ATTR-CM patients, to describe how these parameters evolve over time in routine clinical practice. We also report the same outcomes in untreated patients to reflect the natural disease history in a modern real-world cohort. Methods Clinical, biochemical, and cardiac imaging parameters were serially assessed at baseline and 1-year follow-up for 145 ATTR-CM patients, both treated and untreated with tafamidis. Results The median age was 80-years [73– 86] and eighty (55%) patients received tafamidis. At baseline, the treated group was younger and exhibited less advanced disease relative to the untreated group. Treatment with tafamadis was associated with stabilization in N-terminal pro-B-type natriuretic peptide (NTproBNP), troponin-T, and New York Heart Association (NYHA) functional class at 1-year follow-up, while the untreated group demonstrated worsening (all comparisons p<0.05). Tafamidis treatment status was not significantly associated with National Amyloidosis Center (NAC) and Mayo Clinic disease stage. Conclusion NTproBNP, troponin-T, and NYHA functional class remain stable over 1-year in a real-world cohort of tafamidis-treated ATTR-CM patients. These results may help inform therapeutic monitoring strategies in clinical practice.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".