Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add more filters










Language
Publication year range
1.
PLos ONE ; 19(2): e0278738, fev.2024. ilus, tab
Article in English | CONASS, Sec. Est. Saúde SP, SESSP-IDPCPROD, Sec. Est. Saúde SP | ID: biblio-1531135

ABSTRACT

OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.


Subject(s)
Humans , Amyloid Neuropathies , Cardiomyopathies , Brazil/epidemiology , Prealbumin , Public Health , Machine Learning , Amyloidosis
2.
PLoS One ; 19(2): e0278738, 2024.
Article in English | MEDLINE | ID: mdl-38359001

ABSTRACT

OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.


Subject(s)
Amyloid Neuropathies, Familial , Amyloidosis , Cardiomyopathies , Humans , Brazil/epidemiology , Prealbumin , Public Health , Retrospective Studies , Machine Learning , Cardiomyopathies/diagnosis , Cardiomyopathies/epidemiology , Amyloid Neuropathies, Familial/diagnosis , Amyloid Neuropathies, Familial/epidemiology
SELECTION OF CITATIONS
SEARCH DETAIL
...