Use of biomarkers to diagnose and manage cardiac amyloidosis
Bibliographic record
Abstract
Amyloidoses are characterized by the tissue accumulation of misfolded proteins into insoluble fibrils. The two most common types of systemic amyloidosis result from the deposition of immunoglobulin light chains (AL) and wild-type or variant transthyretin (ATTRwt/ATTRv). Cardiac involvement is the main determinant of outcome in both AL and ATTR, and cardiac amyloidosis (CA) is increasingly recognized as a cause of heart failure. In CA, circulating biomarkers are important diagnostic tools, allow to refine risk stratification at baseline and during follow-up, help to tailor the therapeutic strategy and monitor the response to treatment. Among amyloid precursors, free light chains are established biomarkers in AL amyloidosis, while the plasma transthyretin assay is currently being investigated as a tool for supporting the diagnosis of ATTRv amyloidosis, predicting outcome and monitor response to novel tetramer stabilizers or small interfering RNA drugs in ATTR CA. Natriuretic peptides (NPs) and troponins are consistently elevated in patients with AL and ATTR CA. Plasma NPs, troponins and free light chains hold prognostic significance in AL amyloidosis, and are evaluated for therapy decision-making and follow-up, while the value of NPs and troponins in ATTR is less well established. Biomarkers can be usefully integrated with clinical and imaging variables at all levels of the clinical algorithm of systemic amyloidosis, from screening to diagnosis and prognosis, and treatment tailoring.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".