Detalhe da pesquisa
1.
Machine learning algorithms using national registry data to predict loss to follow-up during tuberculosis treatment.
BMC Public Health
; 24(1): 1385, 2024 May 23.
Artigo
em Inglês
| MEDLINE | ID: mdl-38783264
2.
Causes of death in children with congenital Zika syndrome in Brazil, 2015 to 2018: A nationwide record linkage study.
PLoS Med
; 20(2): e1004181, 2023 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-36827251
3.
The Effect of Diabetes and Prediabetes on Antituberculosis Treatment Outcomes: A Multicenter Prospective Cohort Study.
J Infect Dis
; 225(4): 617-626, 2022 02 15.
Artigo
em Inglês
| MEDLINE | ID: mdl-34651642
4.
Machine learning algorithms using national registry data to predict loss to follow- up during tuberculosis treatment.
Res Sq
; 2023 Dec 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-38168296
5.
Tuberculosis treatment outcomes of diabetic and non-diabetic TB/HIV co-infected patients: A nationwide observational study in Brazil.
Front Med (Lausanne)
; 9: 972145, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-36186793
6.
Tuberculosis Burden and Determinants of Treatment Outcomes According to Age in Brazil: A Nationwide Study of 896,314 Cases Reported Between 2010 and 2019.
Front Med (Lausanne)
; 8: 706689, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-34386510
7.
Prevalence and Clinical Profiling of Dysglycemia and HIV Infection in Persons With Pulmonary Tuberculosis in Brazil.
Front Med (Lausanne)
; 8: 804173, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-35127760
8.
Novel stepwise approach to assess representativeness of a large multicenter observational cohort of tuberculosis patients: The example of RePORT Brazil.
Int J Infect Dis
; 103: 110-118, 2021 Feb.
Artigo
em Inglês
| MEDLINE | ID: mdl-33197582
9.
Effect of acute and chronic exposure to ammonia on different larval instars of Anopheles darlingi (Diptera: Culicidae).
J Vector Ecol
; 44(1): 112-118, 2019 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-31124231