Revista da Sociedade Brasileira de Medicina Tropical最新文献

Background: Chagas disease cardiomyopathy is characterized by intense immune activation, with double-negative (DN) T cells as key producers of inflammatory cytokines. CD1d is an antigen-presenting molecule involved in the activation of DN T cells.

Methods: We characterized CD1d+ monocytes from patients with cardiac (CARD) and indeterminate (IND) disease using flow cytometry.

Results: CARD CD1d+ monocytes exhibited higher expression of TNF, TNF-receptor, PDL-1, and Fas-L compared to those from IND. These monocytes correlated with TNF expression by DN T-cells in CARD but not in IND.

Conclusions: CD1d+ monocytes from CARD are inflammatory and associated with DN T-cell activation, confirming that CD1d is a target for modulating inflammation in Chagas cardiomyopathy.

Chromoblastomycosis is a skin infection caused by melanized fungi that primarily affects rural workers. This study aimed to analyze the clinical and epidemiological manifestations of chromoblastomycosis in Brazil through an extensive literature review. A review of case reports or series of cases in English and Portuguese was conducted using the SciELO, LILACS, SCOPUS, PubMed, and Web of Science databases from 1963 to 2022. A total of 46 articles involving 450 patients were identified, among which, 83.1% were male rural workers with a mean age of 52.2 years. The clinical manifestations were most commonly observed in the lower extremities (78.7%). The most frequent clinical presentations of the disease were verrucous lesions and plaques. Fonsecaea and Rhinocladiella spp. were the most common agents responsible for chromoblastomycosis. Most cured cases were treated with itraconazole, either as monotherapy or in combination with other antifungals, surgery, or cryosurgery. Chromoblastomycosis affects hundreds of rural workers in Brazil, leading to financial disabilities as well as personal and family losses. It is essential to prioritize epidemiological surveillance and ensure the early diagnosis of this disease to reveal its true prevalence, guide resource allocation, improve diagnosis, ensure early treatment, and implement preventive measures.

Rickettsiosis is a disease caused by bacteria belonging to the genus Rickettsia, and is a potentially fatal zoonotic disease of great medical and veterinary importance. Given the urgent need to develop new diagnostic methods for detecting this disease, the present review aimed to evaluate the number of publications dedicated to the identification of Rickettsia spp. in human samples using molecular methods, such as polymerase chain reaction and its variations. To this end, a bibliographical survey covering articles published in the past ten years was conducted using the PudMed platform with the keywords "spotted fever" and "Rickettsia," both combined with "diagnosis." A growing number of publications in this area reflects an increasing interest in research, especially since 2015. From 2015 to February 2024, several promising results were tested and many studies were able to detect the genetic sequences of interest. Therefore, the absence of a standard diagnosis method highlights the critical need for developing an effective technique capable of accurately detecting the etiological agent and ensuring accurate diagnosis of the disease.

Acute rheumatic fever (ARF) is a complex disease with several clinical manifestations. Its most significant long-term complication is valvular heart damage, commonly referred to as chronic rheumatic heart disease. The risk of ARF varies globally, with over 80% of cases occurring in low- and middle-income countries, highlighting the role of socioeconomic factors. A comprehensive understanding of the risk factors associated with ARF and its clinical, genetic, and sociodemographic mediators can help clinicians identify high-risk individuals, develop effective management strategies, enhance target screening and active case-finding initiatives, and ultimately improve patient outcomes. This review aimed to provide an overview of ARF and its global burden, focusing on the established and potential risk factors associated with its development.

Background: Malaria is an acute febrile parasitic disease that significantly impacts global public health. In Brazil, the most studied endemic area for the disease is the Amazon region. This study aims to analyze temporal, spatial, and spatiotemporal patterns of malaria in the extra-Amazon region of Brazil over a 22-year period.

Methods: We conducted a time-series study from 2001 to 2022, encompassing both autochthonous and imported cases. Time trend analysis was employed to assess fluctuations in incidence rates over the years. Spatial clusters of infection risk were identified using the Local Moran Index and Kulldorff's scan.

Results: A total of 18,633 malaria cases were identified in the extra-Amazon region, including 1,980 autochthonous, 13,836 imported, and 2,817 of unknown origin. During the first period (2001-2011), 1,348 autochthonous and 9,124 imported cases were reported. In the second period (2012-2022), there were 632 autochthonous and 4,712 imported cases. The state of Espírito Santo exhibited a decreasing trend but maintained the highest incidence rates throughout the study. The number of municipalities at high risk for autochthonous cases declined, with Espírito Santo, Minas Gerais, and Piauí having the most municipalities with high rates. For imported cases, the federative units with the highest numbers in both periods were Ceará, Distrito Federal, Goiás, Minas Gerais, Piauí, and Paraná.

Conclusions: The data reveal the areas most affected by malaria and thus of highest priority for implementing control strategies.

Background: This study aimed to identify COVID-19 cases among people living with HIV (PLWH) in Brazil in 2020, describe their clinical, sociodemographic, and epidemiological profiles, and evaluate the factors associated with disease severity.

Methods: This cross-sectional study used secondary data obtained from the Brazilian healthcare system. Probabilistic and deterministic data linkage methods were used to identify coinfected patients. Descriptive statistical analysis was conducted, and factors associated with severe cases were evaluated using Pearson's chi-squared test, Student's t-test, and logistic regression.

Results: In 2020, 36,746 coinfections were identified, making it one of the largest coinfection databases described worldwide. In total, 4,502 (12.25%) patients had severe cases and 32,244 (87.75%) had non-severe cases. The covariates age (OR=1.05; 95% CI: 1.05-1.06), nonwhite ethnicity (OR=1.68; 95% CI: 1.56-1.81), history of AIDS diagnosis (OR=1.17; 95% CI: 1.08-1.28), recent HIV diagnosis (OR=5.47; 95% CI: 4.25-7.02), absence of antiretroviral therapy (OR=1.70; 95% CI: 1.57-1.84), CD4+ < 200 (OR=6.41; 95% CI: 5.09-8.08), detectable HIV viral load (OR=2.61; 95% CI: 2.21-3.05), ≥ 1 comorbidity (OR=4.09; 95% CI: 3.79-4.41), and ≥ 4 symptoms were associated with increased severity.

Conclusions: Multiple factors were linked to severe COVID-19, including uncontrolled HIV infection, age > 50 years, comorbidities, and racial disparities. This study reinforces the importance of maintaining public policies focused on early HIV diagnosis, access and adherence to treatment, especially for minority ethnic groups, and focusing on premature aging in PLWH.

Background: In 2022, Mato Grosso (MT, Brazil) reported the highest detection rate of new leprosy cases (66.20 per 100,000 inhabitants) among all Brazilian states. Monitoring of leprosy indicators is an important control strategy in hyperendemic areas. We aimed to describe the temporal trends and identify clusters of municipalities according to leprosy surveillance indicators in MT between 2008 and 2022.

Methods: Data from the Notifiable Diseases Information System were used to analyze new case detection rate of leprosy (NCDR), new case detection rate of leprosy among children aged <15 years (NCD15), and rate of new cases with grade 2 physical disability (G2DR). Spatial scan statistics with pure spatial analysis and spatial autocorrelation maps were used to analyze the spatial patterns. Joinpoint regression was used to estimate the annual percentage change (APC) in these indicators.

Results: The NCDR decreased (APC: -20.2%, 95% confidence interval (CI): -38.7% to -7.4%) between 2019 and 2021. The NCD15 also decreased (APC: -19.2%, 95% CI: -36.4% to -10.3%) between 2018 and 2022. Conversely, the G2DR remained stable throughout the study (APC: 3.2%, 95% CI: -0.1% to 6.7%). Global Moran's index (Moran's I) confirmed the existence of spatial dependence among the municipalities for NCDR (Moran's I=0.348), NCD15 (Moran's I=0.269), and G2DR (Moran's I=0.275). Clusters with high NCDR levels included 13 municipalities in the northern and eastern macroregions, while clusters with high G2DR levels included 12 municipalities in the northwestern, northern, and eastern macroregions.

Conclusions: The NCDR and NCD15 decreased, but the G2DR remained stable between 2018 and 2022. The coronavirus disease 2019 (COVID-19) pandemic had a potential negative impact on leprosy case detection, highlighting the need to strengthen leprosy surveillance efforts. The identified clusters of MT municipalities can significantly assist in this task.

A 34-year-old man developed severe envenomation after being bitten by a Crotalus durissus (rattlesnake), which was treated with anticrotalic serum. Three weeks later, the patient reported paresthesia and neuropathic pain in the left hand, which had progressed to all four limbs. Electroneuromyography revealed asymmetric axonal sensorimotor multiple mononeuropathy. The patient was treated with prednisone, and six months later there was significant improvement in sensorimotor conduction. This is the first reported case of multiple mononeuropathy associated with C. durissus envenomation. Post-snake envenomation peripheral neuropathy is a rare complication requiring prompt recognition and treatment to optimize nerve function and enhance patient outcomes.

[This corrects the article doi: 10.1590/0037-8682-0190-2024].