Assessment of potential transthyretin amyloid cardiomyopathy cases in the Brazilian public health system using a machine learning model.
<h4>Objectives</h4>To identify and describe the profile of potential transthyretin cardiac amyloidosis (ATTR-CM) cases in the Brazilian public health system (SUS), using a predictive machine learning (ML) model.<h4>Methods</h4>This was a retrospective descriptive database stu...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2024-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0278738&type=printable |
| _version_ | 1797301372216934400 |
|---|---|
| author | Isabella Zuppo Laper Cecilia Camacho-Hubner Rafaela Vansan Ferreira Claudenice Leite Bertoli de Souza Marcus Vinicius Simões Fabio Fernandes Edileide de Barros Correia Ariane de Jesus Lopes de Abreu Guilherme Silva Julian |
| author_facet | Isabella Zuppo Laper Cecilia Camacho-Hubner Rafaela Vansan Ferreira Claudenice Leite Bertoli de Souza Marcus Vinicius Simões Fabio Fernandes Edileide de Barros Correia Ariane de Jesus Lopes de Abreu Guilherme Silva Julian |
| author_sort | Isabella Zuppo Laper |
| collection | DOAJ |
| description | <h4>Objectives</h4>To identify and describe the profile of potential transthyretin cardiac amyloidosis (ATTR-CM) cases in the Brazilian public health system (SUS), using a predictive machine learning (ML) model.<h4>Methods</h4>This was a retrospective descriptive database study that aimed to estimate the frequency of potential ATTR-CM cases in the Brazilian public health system using a supervised ML model, from January 2015 to December 2021. To build the model, a list of ICD-10 codes and procedures potentially related with ATTR-CM was created based on literature review and validated by experts.<h4>Results</h4>From 2015 to 2021, the ML model classified 262 hereditary ATTR-CM (hATTR-CM) and 1,581 wild-type ATTR-CM (wtATTR-CM) potential cases. Overall, the median age of hATTR-CM and wtATTR-CM patients was 66.8 and 59.9 years, respectively. The ICD-10 codes most presented as hATTR-CM and wtATTR-CM were related to heart failure and arrythmias. Regarding the therapeutic itinerary, 13% and 5% of hATTR-CM and wtATTR-CM received treatment with tafamidis meglumine, respectively, while 0% and 29% of hATTR-CM and wtATTR-CM were referred to heart transplant.<h4>Conclusion</h4>Our findings may be useful to support the development of health guidelines and policies to improve diagnosis, treatment, and to cover unmet medical needs of patients with ATTR-CM in Brazil. |
| first_indexed | 2024-03-07T23:20:39Z |
| format | Article |
| id | doaj.art-28fa030aa5054a48be3439ac69f9cbaf |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-03-07T23:20:39Z |
| publishDate | 2024-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-28fa030aa5054a48be3439ac69f9cbaf2024-02-21T05:31:51ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-01192e027873810.1371/journal.pone.0278738Assessment of potential transthyretin amyloid cardiomyopathy cases in the Brazilian public health system using a machine learning model.Isabella Zuppo LaperCecilia Camacho-HubnerRafaela Vansan FerreiraClaudenice Leite Bertoli de SouzaMarcus Vinicius SimõesFabio FernandesEdileide de Barros CorreiaAriane de Jesus Lopes de AbreuGuilherme Silva Julian<h4>Objectives</h4>To identify and describe the profile of potential transthyretin cardiac amyloidosis (ATTR-CM) cases in the Brazilian public health system (SUS), using a predictive machine learning (ML) model.<h4>Methods</h4>This was a retrospective descriptive database study that aimed to estimate the frequency of potential ATTR-CM cases in the Brazilian public health system using a supervised ML model, from January 2015 to December 2021. To build the model, a list of ICD-10 codes and procedures potentially related with ATTR-CM was created based on literature review and validated by experts.<h4>Results</h4>From 2015 to 2021, the ML model classified 262 hereditary ATTR-CM (hATTR-CM) and 1,581 wild-type ATTR-CM (wtATTR-CM) potential cases. Overall, the median age of hATTR-CM and wtATTR-CM patients was 66.8 and 59.9 years, respectively. The ICD-10 codes most presented as hATTR-CM and wtATTR-CM were related to heart failure and arrythmias. Regarding the therapeutic itinerary, 13% and 5% of hATTR-CM and wtATTR-CM received treatment with tafamidis meglumine, respectively, while 0% and 29% of hATTR-CM and wtATTR-CM were referred to heart transplant.<h4>Conclusion</h4>Our findings may be useful to support the development of health guidelines and policies to improve diagnosis, treatment, and to cover unmet medical needs of patients with ATTR-CM in Brazil.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0278738&type=printable |
| spellingShingle | Isabella Zuppo Laper Cecilia Camacho-Hubner Rafaela Vansan Ferreira Claudenice Leite Bertoli de Souza Marcus Vinicius Simões Fabio Fernandes Edileide de Barros Correia Ariane de Jesus Lopes de Abreu Guilherme Silva Julian Assessment of potential transthyretin amyloid cardiomyopathy cases in the Brazilian public health system using a machine learning model. PLoS ONE |
| title | Assessment of potential transthyretin amyloid cardiomyopathy cases in the Brazilian public health system using a machine learning model. |
| title_full | Assessment of potential transthyretin amyloid cardiomyopathy cases in the Brazilian public health system using a machine learning model. |
| title_fullStr | Assessment of potential transthyretin amyloid cardiomyopathy cases in the Brazilian public health system using a machine learning model. |
| title_full_unstemmed | Assessment of potential transthyretin amyloid cardiomyopathy cases in the Brazilian public health system using a machine learning model. |
| title_short | Assessment of potential transthyretin amyloid cardiomyopathy cases in the Brazilian public health system using a machine learning model. |
| title_sort | assessment of potential transthyretin amyloid cardiomyopathy cases in the brazilian public health system using a machine learning model |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0278738&type=printable |
| work_keys_str_mv | AT isabellazuppolaper assessmentofpotentialtransthyretinamyloidcardiomyopathycasesinthebrazilianpublichealthsystemusingamachinelearningmodel AT ceciliacamachohubner assessmentofpotentialtransthyretinamyloidcardiomyopathycasesinthebrazilianpublichealthsystemusingamachinelearningmodel AT rafaelavansanferreira assessmentofpotentialtransthyretinamyloidcardiomyopathycasesinthebrazilianpublichealthsystemusingamachinelearningmodel AT claudeniceleitebertolidesouza assessmentofpotentialtransthyretinamyloidcardiomyopathycasesinthebrazilianpublichealthsystemusingamachinelearningmodel AT marcusviniciussimoes assessmentofpotentialtransthyretinamyloidcardiomyopathycasesinthebrazilianpublichealthsystemusingamachinelearningmodel AT fabiofernandes assessmentofpotentialtransthyretinamyloidcardiomyopathycasesinthebrazilianpublichealthsystemusingamachinelearningmodel AT edileidedebarroscorreia assessmentofpotentialtransthyretinamyloidcardiomyopathycasesinthebrazilianpublichealthsystemusingamachinelearningmodel AT arianedejesuslopesdeabreu assessmentofpotentialtransthyretinamyloidcardiomyopathycasesinthebrazilianpublichealthsystemusingamachinelearningmodel AT guilhermesilvajulian assessmentofpotentialtransthyretinamyloidcardiomyopathycasesinthebrazilianpublichealthsystemusingamachinelearningmodel |