Chagas disease is not associated with diabetes, metabolic syndrome, insulin resistance and beta cell dysfunction at baseline of Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

Resende, Bruna Araújo Martins; Du, Huiyun; Ribeiro, Antônio Luiz Pinho; Duncan, Bruce Bartholow; Schmidt, María Inês; Mill, José Geraldo; Goulart, Alessandra Carvalho; Pereira, Alexandre da Costa; Barreto, Sandhi Maria; Diniz, Maria de Fátima Haueisen Sander

doi:10.1016/j.parint.2021.102440

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…The baseline evaluation was performed in 2008-2010 and recruited active and retired civil servants from five universities and research institutes from 6 different Brazilian states. ChD serological status and standardized ECG were obtained from all participants [36,37].…”

Section: Reds-iimentioning

confidence: 99%

Screening for Chagas disease from the electrocardiogram using a deep neural network

et al. 2023

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Background Worldwide, it is estimated that over 6 million people are infected with Chagas disease (ChD). It is a neglected disease that can lead to severe heart conditions in its chronic phase. While early treatment can avoid complications, the early-stage detection rate is low. We explore the use of deep neural networks to detect ChD from electrocardiograms (ECGs) to aid in the early detection of the disease. Methods We employ a convolutional neural network model that uses 12-lead ECG data to compute the probability of a ChD diagnosis. Our model is developed using two datasets which jointly comprise over two million entries from Brazilian patients: The SaMi-Trop study focusing on ChD patients, enriched with data from the CODE study from the general population. The model’s performance is evaluated on two external datasets: the REDS-II, a study focused on ChD with 631 patients, and the ELSA-Brasil study, with 13,739 civil servant patients. Findings Evaluating our model, we obtain an AUC-ROC of 0.80 (CI 95% 0.79-0.82) for the validation set (samples from CODE and SaMi-Trop), and in external validation datasets: 0.68 (CI 95% 0.63-0.71) for REDS-II and 0.59 (CI 95% 0.56-0.63) for ELSA-Brasil. In the latter, we report a sensitivity of 0.52 (CI 95% 0.47-0.57) and 0.36 (CI 95% 0.30-0.42) and a specificity of 0.77 (CI 95% 0.72-0.81) and 0.76 (CI 95% 0.75-0.77), respectively. Additionally, when considering only patients with Chagas cardiomyopathy as positive, the model achieved an AUC-ROC of 0.82 (CI 95% 0.77-0.86) for REDS-II and 0.77 (CI 95% 0.68-0.85) for ELSA-Brasil. Interpretation The neural network detects chronic Chagas cardiomyopathy (CCC) from ECG—with weaker performance for early-stage cases. Future work should focus on curating large higher-quality datasets. The CODE dataset, our largest development dataset includes self-reported and therefore less reliable labels, limiting performance for non-CCC patients. Our findings can improve ChD detection and treatment, particularly in high-prevalence areas.

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Section: Reds-iimentioning

confidence: 99%

Screening for Chagas disease from the electrocardiogram using a deep neural network

et al. 2023

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“…These results suggest that T. cruzi infection in AT and the pancreas in CD patients is not related to important glycemic changes. 58…”

Section: Metabolic and Parasitic Diseasesmentioning

confidence: 99%

“…These results suggest that T. cruzi infection in AT and the pancreas in CD patients is not related to important glycemic changes. 58 Cutaneous leishmaniasis (CL) caused by Leishmania brasiliensis (L. brasiliensis) was studied in patients with obesity associated with glucocorticoid therapy. In this study, the authors stated that obesity modified the clinical characteristics of CL via the host immune response, as patients developed hypertrophic ulcers instead of typical oval ulcers.…”

Section: Metabolic Diseases Associated With Protozoan Infectionsmentioning

confidence: 99%

Comorbidities involving parasitic diseases: A look at the benefits and complications

Oliveira

Cruz

Pinheiro

et al. 2022

Exp Biol Med (Maywood)

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Parasitic infections acquired by the population cause substantial morbidity worldwide, with individuals from developing countries being most affected. Some parasites remain in the host for long periods, settling in different organs, manipulating the flow of nutrients and metabolites, and influencing the immune response, favoring their adaptation. The host attempts to counteract the metabolic and immunological alterations and the possible damage caused by infection. These metabolic and immunological changes experienced by the host can influence the progression of other existing morbidities or those that will be acquired in the future. Cancer and metabolic diseases are also frequent causes of morbidity in the world population. The large numbers of individuals affected by cancer and metabolic diseases and the high prevalence of morbidity caused by parasitic diseases favor the development of comorbidity involving these pathologies. This review provides an overview of major advances in research on cancer and metabolic diseases associated with parasitic infections. Information about hosts and parasites such as alterations of the immune response, metabolism and adaptation mechanisms of the parasites, and parasitic molecules with therapeutic potential is provided, as well as the beneficial results or complications related to the comorbidities discussed herein. We emphasize the need to conduct additional studies addressing comorbidities associated with parasitic infections to improve the understanding of the impact of this association on the progression of morbidities, as well as the possibility of the therapeutic use of and therapeutic approaches involving parasites.

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Dynamics of the Trypanosoma cruzi infection in adipose tissue: Assessing gene expression of PNPLA2, FASN, and ACAT1 under Benzonidazole treatment and indirect mononuclear immune cells interaction

da Silva,

Moreira,

Oliveira

et al. 2024

Molecular and Biochemical Parasitology

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Chagas disease is not associated with diabetes, metabolic syndrome, insulin resistance and beta cell dysfunction at baseline of Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

Cited by 4 publications

References 27 publications

Screening for Chagas disease from the electrocardiogram using a deep neural network

Screening for Chagas disease from the electrocardiogram using a deep neural network

Comorbidities involving parasitic diseases: A look at the benefits and complications

Dynamics of the Trypanosoma cruzi infection in adipose tissue: Assessing gene expression of PNPLA2, FASN, and ACAT1 under Benzonidazole treatment and indirect mononuclear immune cells interaction

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