Detection of transthyretin amyloid cardiomyopathy by automated data extraction from electronic health records

Bibliographic Details
Title: Detection of transthyretin amyloid cardiomyopathy by automated data extraction from electronic health records
Authors: Ana Moya, Clara L. Oeste, Monika Beles, Sofie Verstreken, Riet Dierckx, Ward Heggermont, Jozef Bartunek, Eline Bogaerts, Imke Masuy, Dries Hens, Dario Bertolone, Marc Vanderheyden
Source: ESC Heart Failure, Vol 10, Iss 6, Pp 3483-3492 (2023)
Publisher Information: Wiley, 2023.
Publication Year: 2023
Collection: LCC:Diseases of the circulatory (Cardiovascular) system
Subject Terms: Transthyretin amyloid cardiomyopathy, Heart failure, Diagnosis, Phenotype, Diseases of the circulatory (Cardiovascular) system, RC666-701
More Details: Abstract Aims Transthyretin amyloid cardiomyopathy (ATTR‐CM), a progressive and fatal cardiomyopathy, is frequently misdiagnosed or entails diagnostic delays, hindering patients from timely treatment. This study aimed to generate a systematic framework based on data from electronic health records (EHRs) to assess patients with ATTR‐CM in a real‐world population of heart failure (HF) patients. Predictive factors or combinations of predictive factors related to ATTR‐CM in a European population were also assessed. Methods and results Retrospective unstructured and semi‐structured data from EHRs of patients from OLV Hospital Aalst, Belgium (2012–20), were processed using natural language processing (NLP) to generate an Observational Medical Outcomes Partnership Common Data Model database. NLP model performance was assessed on a random subset of EHRs by comparing algorithm outputs to a physician‐generated standard (using precision, recall, and their harmonic mean, or F1‐score). Of the 3127 HF patients, 103 potentially had ATTR‐CM (age 78 ± 9 years; male 55%; ejection fraction of 48% ± 16). The mean diagnostic delay between HF and ATTR‐CM diagnosis was 1.8 years. Besides HF and cardiomyopathy‐related phenotypes, the strongest cardiac predictor was atrial fibrillation (AF; 72% in ATTR‐CM vs. 60% in non‐ATTR‐CM, P = 0.02), whereas the strongest non‐cardiac predictor was carpal tunnel syndrome (21% in ATTR‐CM vs. 3% in non‐ATTR‐CM, P
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2055-5822
Relation: https://doaj.org/toc/2055-5822
DOI: 10.1002/ehf2.14517
Access URL: https://doaj.org/article/c6ce75b94ab64243a968f0a0fd0a2328
Accession Number: edsdoj.6ce75b94ab64243a968f0a0fd0a2328
Database: Directory of Open Access Journals
More Details
ISSN:20555822
DOI:10.1002/ehf2.14517
Published in:ESC Heart Failure
Language:English