Revista da Sociedade Brasileira de Medicina Tropical最新文献

Background: In this study, we aimed to describe the mutations associated with first-line drug resistance in Mycobacterium tuberculosis complex (MTBC) isolates from São Paulo, Brazil, between 2019 and 2021.

Methods: Mutations in the coding regions of rpoB and katG genes and in the promoter region of the inhA gene in MTBC clinical isolates were detected using the GenoType MTBDRplus assay (LPA). All mutations inferred by LPA were sequenced.

Results: Of the 13,489 MTBC isolates with valid LPA results, 657 (4.9%) harbored mutations. The overall prevalence rates of rifampicin-resistant (RIF-R) tuberculosis (TB), isoniazid-resistant (INH-R) TB, and multidrug-resistant (MDR) TB were 1.5, 2.0, and 1.2%, respectively. A significant proportion of RIF-R isolates presented inferred rpoB mutations (89.1%), most of which were the borderline H445N mutation. The inhA promoter C-15T mutation was predominant among the INH-R isolates (52.8%). Most MDR isolates presented rpoB S450L + katG S315T1 mutations. Gene sequencing identified mutations not included in the catalogue of mutations published by the World Health Organization. Phenotypic drug susceptibility testing on isolates with inferred rpoB mutations revealed that the 0.5 µg/mL critical concentration of RIF failed to detect most borderline mutations when using the BACTEC MGIT 960 system.

Conclusions: These findings emphasize the need for continuous surveillance and the integration of molecular and phenotypic methods to ensure an accurate detection and management of drug-resistant TB in high-burden settings.

Background: Latent tuberculosis infection (LTBI) is a significant concern among migrant populations, particularly Venezuelans, due to its adverse health and social conditions. This study aimed to construct and validate a predictive model of LTBI among Venezuelan migrants.

Methods: This cross-sectional study utilized data from the project "TB and migrants in BRICS countries: The case of Brazil", carried out in Boa Vista, Roraima, in 2020. The final sample included 427 participants. For the analysis, 22 variables were selected, and simple and multiple logistic regression analyses were applied. General measures (Nagalkerke's R2 and Brier's score), discriminative capacity (accuracy, receiver operating characteristic curve, and area under the curve [AUC]), and calibration measures (Hosmer-Lemeshow test and calibration graph) were used to evaluate the model. The model was internally validated using bootstrapping. Finally, a nomogram and a clinical decision curve were constructed.

Results: Six LTBI predictors (marital status, social benefit, documentation status, smoking status, presence of comorbidities, and fever) were included in the final model. The predictive model demonstrated moderate discriminatory capacity (AUC: 0.676), good calibration, and was also validated with an AUC of 0.678. Additionally, a clinical decision analysis revealed that the use of the model offers superior benefits compared with traditional treatment strategies.

Conclusions: The predictive model and nomogram proved to be useful tools for LTBI screening in migrants, potentially guiding border health surveillance actions in this population.

We report the case of a 17-year-old girl who was initially diagnosed with multiple sclerosis based on clinical and radiological findings and later confirmed to have neurobrucellosis via cerebrospinal fluid Brucella polymerase chain reaction positivity. Magnetic resonance imaging revealed demyelinating lesions consistent with multiple sclerosis, and Brucella infection due to epidemiological exposure was suspected. To the best of our knowledge, this is the first pediatric report of coexisting neurobrucellosis and multiple sclerosis. It underscores the diagnostic challenges in distinguishing between infectious and autoimmune demyelinating disorders, particularly in endemic regions, and highlights the importance of a comprehensive evaluation of atypical presentations.

Background: Chagas disease, an anthropozoonosis endemic to Latin America, is caused by Trypanosoma cruzi and is a serious public health concern.

Methods: We investigated the natural infection of triatomine bugs, genotyped T. cruzi, and identified the blood meal sources of the infected vectors in the Medio Araguaia region of Mato Grosso, Brazil.

Results: In total, 235 triatomines were identified. The highest triatomine occurrence (95.7%) was observed in the municipality of Barra do Garças. The most prevalent species was Triatoma williami (89.7%), followed by Rhodnius neglectus (8.8%), Panstrongylus geniculatus (0.88%), and Panstrongylus diasi (0.44%). Barra do Garças showed a high rate of natural infection by T. cruzi (65.7%). Four discrete typing units were identified in the infected insects: TcIV and TcII strains in T. williami, and TcI and TcIII associated with R. neglectus and P. geniculatus, respectively. Regarding blood meal sources, T. williami, P. geniculatus, and R. neglectus predominantly fed on birds and rodents. However, human blood was detected in 32.8% of the insects.

Conclusion: Overall, these findings indicate a high risk of Chagas disease vector transmission in the municipality of Barra do Garças, highlighting the need for innovative approaches to control and prevent this disease.

Background: Leptospirosis is a serious zoonosis. In 2024, Rio Grande do Sul (RS) experienced floods affecting 93% of the municipalities and 8.8% of the population. In this study, we reviewed the leptospirosis notifications post-flooding.

Methods: Descriptive quantitative study using secondary data from the RS Health Department Epidemiological Report.

Results: A total of 7,129 suspected cases were reported, of which 788 were confirmed. Porto Alegre had the highest number of cases and Travesseiro had the highest incidence rate. Epidemiological weeks 20-24 peaked in cases and deaths (47 total cases), with significant municipal variation.

Conclusions: The 2024 floods caused a significant increase in leptospirosis, underscoring the need for a One Health approach and strengthening public health policies.

Background: Patients with chronic Chagas cardiomyopathy (CCC) may present with fatigue and dyspnea, which contribute to functional impairment. However, simple and inexpensive methods for evaluation of functional impairment and identification of left ventricular (LV) systolic dysfunction in patients with CCC are lacking. The Human Activity Profile (HAP) has potential in functional evaluation of patients with CCC. This study was conducted to analyze the association between HAP, functional parameters, and LV systolic dysfunction in patients with CCC, and to demonstrate the accuracy of HAP in identifying LV systolic dysfunction in patients with CCC.

Methods: One hundred and twenty-six patients with CCC (NYHA I-III, 18.9% with LV systolic dysfunction) were evaluated using echocardiography, the 60-second sit-to-stand test (STS60, for lower limb strength and endurance), and the HAP questionnaire. In addition, the gait speed and handgrip strength of each patient was measured.

Results: HAP score was correlated with gait speed (r=-0.206; p=0.023), STS60 score (r=0.199, p=0.030), and handgrip strength (r=0.315, p<0.01). Binary logistic regression showed that HAP score was the only functional variable associated with LV systolic dysfunction. Patients with LV systolic dysfunction (n=24) had lower HAP scores than those without LV systolic dysfunction (n=102) (p <0.01). The area under the ROC curve indicated that HAP score had an acceptable discriminatory ability to identify LV systolic dysfunction in patients with CCC (AUC=0.713). The optimal cut-off HAP score for identifying these patients was <56 points.

Conclusion: HAP score is associated with LV systolic dysfunction in patients with CCC.