Baseline Predictors of Adverse Outcomes for Transthyretin Amyloidosis Cardiomyopathy Patients Treated and Untreated with Tafamidis: A Canadian Referral Center Experience
Bibliographic record
Abstract
Background: Tafamidis is a costly therapy that improves outcomes for patients with transthyretin amyloidosis cardiomyopathy (ATTR-CM), although significant knowledge gaps exist for predicting longer-term response to treatment. The purpose of this study was to examine baseline predictors of adverse outcomes and their association with tafamidis treatment in comparison with those untreated in a clinical cohort from a Canadian ATTR-CM referral center. Methods: Patients with a confirmed diagnosis of ATTR-CM were included. Multivariable modeling was used to identify baseline variables associated with the primary outcome of all-cause mortality and secondary outcomes of cardiovascular mortality or hospitalization. Cox proportional hazard and competing risk analyses were used, with tafamidis modeled as a time-varying covariate. Results: In total, 139 ATTR-CM patients were included, with a median age of 80.9 years [74.3–86.6 years], from 2011 to 2022. The mean follow-up was 2.9 ± 1.8 years. Eighty (55%) patients were treated with tafamidis. All-cause mortality and cardiovascular mortality alone were associated with the following baseline variables: age, clinical frailty scale, systolic blood pressure, renal function, and right ventricular size and function (all p < 0.05), with no identified interactions with tafamidis treatment. Only baseline renal function was associated with cardiovascular hospitalization (p < 0.05). Conclusion: Important baseline variables associated with adverse ATTR-CM disease outcomes included renal function, systolic blood pressure, frailty, and right ventricular size and function. The risk factors were independent of treatment with tafamidis. These findings may help improve risk stratification for determining eligibility for ATTR-CM therapies.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".