Annual Cardiovascular-Related Hospitalization Days Avoided with Tafamidis in Patients with Transthyretin Amyloid Cardiomyopathy
Bibliographic record
Abstract
BACKGROUND: Patients with transthyretin amyloid cardiomyopathy (ATTR-CM) experience infiltrative cardiomyopathy and heart failure symptoms requiring costly hospitalizations. The Transthyretin Amyloidosis Cardiomyopathy Clinical Trial (ATTR-ACT) demonstrated the efficacy of tafamidis on the frequency of cardiovascular (CV)-related hospitalizations in patients with ATTR-CM. PURPOSE: As length of stay can affect the total hospitalization burden, our study aimed to better understand the impact of tafamidis on the number of CV-related hospital days avoided in the management of ATTR-CM patients. METHODS: Data from ATTR-ACT were used to calculate the total burden of CV-related hospitalization (days) by treatment arm in this post hoc analysis. RESULTS: In the total trial population, patients receiving tafamidis had significantly fewer CV-related hospitalizations per year (relative risk reduction [RRR] 0.68; 0.4750 vs. 0.7025, p < 0.0001) and a shorter mean length of stay per CV-related hospitalization event (8.6250 vs. 9.5625 days) than patients receiving placebo. Taken together, tafamidis prevented 2.62 CV-related hospitalization days per patient per year. A subgroup analysis showed that with earlier treatment initiation of tafamidis, the annual number of CV-related hospitalizations was significantly lowered by 52% compared with placebo (RRR 0.48; 0.3378 vs. 0.7091, p < 0.0001). With 1.14 fewer days per hospitalization, tafamidis reduced the annual number of CV-related hospitalization days by 3.96 days per New York Heart Association class I/II patient. CONCLUSIONS: In patients with ATTR-CM, tafamidis was associated with a lower rate of CV-related hospitalizations and shorter length of hospital stay. Timely diagnosis and treatment with tafamidis could further decrease the total number of CV-related hospitalization days per year. GOV IDENTIFIER: NCT01994889.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.001 | 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".