Heart failure & cardiomyopathies
Transthyretin amyloid cardiomyopathy among patients hospitalized for heart failure and performance of an adapted wild-type ATTR-CM machine learning model: Findings from GWTG-HF
Authors' conclusion
Among US patients hospitalized for HF, the number of patients with ATTR-CM defined by diagnosis codes on an inpatient/outpatient claim within 6 months of admission was low. Most factors within the prior 11-factor model were associated with greater odds of ATTR-CM diagnosis. In this population, the ATTR-CM model demonstrated modest discrimination.
Study context
- Population
- Medicare beneficiaries aged ≥65 years hospitalized for heart failure (HF) in the GWTG-HF Registry, 2008–2019
- Participants
- 205,545 beneficiaries608 hospitals
- Exposure
- ATTR-CM diagnosis vs no ATTR-CM diagnosis; performance of an 11-factor random forest wtATTR-CM model
- ATTR-CMn = 627
- Outcome
- Prevalence of ATTR-CM diagnosis; 11-factor model performance
Methodological detailsregistry-based, matched 1:1 by age and sex
- Registry-based
- Matched 1:1 by age and sex
Main finding
As reported in the abstract
ATTR-CM
0.31%
627
- 11-factor model discrimination (c-statistic), matched cohort
- 0.65
Observational data: associations, not effects.
Original publication
Transthyretin amyloid cardiomyopathy among patients hospitalized for heart failure and performance of an adapted wild-type ATTR-CM machine learning model: Findings from GWTG-HF. Am Heart J. Published 1 July 2023. doi:10.
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