Heart failure & cardiomyopathies
Detection of Transthyretin Amyloid Cardiomyopathy by Automated Data Extraction from Electronic Health Records
Main finding · Predictors of ATTR-CMResult — go to the resultOdds ratio 2.03 95% CI 1.28–3.22Authors' conclusion
Not only well-known variables associated with ATTR-CM but also unique combinations of cardiac and non-cardiac phenotypes are able to predict ATTR-CM in a real-world HF population, aiding in early identification of ATTR-CM patients.
Study context
- Population
- Heart Failure (HF) patients, OLV Hospital Aalst, Belgium (2012–20)
- Participants
- 3,127 HF patients
- Exposure
- ATTR-CM vs non-ATTR-CM
- ATTR-CMn = 103
- Outcome
- Predictors of ATTR-CM
Methodological detailssingle-centre, natural language processing of electronic health records (EHRs)
- Single-centre
- Natural language processing of EHRs
Main finding
As reported in the abstract
Odds ratio
2.03
95% CI 1.28–3.22
ATTR-CMvs non-ATTR-CM
OR 2.03 (95% CI 1.28–3.22)
- Atrial fibrillation (AF) (strongest cardiac predictor): 72% vs 60%
- P = 0.02
- Carpal tunnel syndrome (strongest non-cardiac predictor): 21% vs 3%
- P < 0.001
Observational data: associations, not effects.
Further findings
- Diagnostic delay between HF and ATTR-CM diagnosis
- 1.8 · mean · years
Original publication
Detection of Transthyretin Amyloid Cardiomyopathy by Automated Data Extraction from Electronic Health Records. ESC Heart Fail. Published 19 September 2023. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →